Spaces:
Sleeping
Sleeping
konstantinG
commited on
Commit
•
dee4d19
1
Parent(s):
e9d239e
Upload 12 files
Browse files- .gitattributes +1 -0
- app.py +164 -0
- automl.py +1 -0
- classification.py +20 -0
- config_default.yaml +217 -0
- config_minimal.yaml +217 -0
- dataset.csv +0 -0
- dt_pipeline.pkl +3 -0
- get_profile.py +8 -0
- logs.log +3 -0
- metrics_info.csv +16 -0
- model_info.csv +25 -0
- requirements.txt +431 -0
.gitattributes
CHANGED
@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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logs.log filter=lfs diff=lfs merge=lfs -text
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app.py
ADDED
@@ -0,0 +1,164 @@
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1 |
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import streamlit as st
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from streamlit_option_menu import option_menu
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from pandas_profiling import ProfileReport
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from streamlit_pandas_profiling import st_profile_report
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import os
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import pandas as pd
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from pycaret.classification import *
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from classification import prep_and_train
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import time
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from get_profile import get_profile
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from classification import tuning
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# if os.path.exists('./dataset.csv'):
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# df = pd.read_csv('dataset.csv', index_col=None)
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s = ClassificationExperiment()
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with st.sidebar: #Side bar config
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selected = option_menu(menu_title=None,options=["Home", 'Classification','Regression', 'Time Series'],
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icons=['house', 'file-binary','graph-up','bezier2'], menu_icon="cast", default_index=0)
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st.title("Upload Your Dataset")
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file = st.file_uploader("Upload Your Dataset")
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if file:
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st.session_state.df = pd.read_csv(file, index_col=None)
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st.session_state.df.to_csv('dataset.csv', index=None)
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if selected == 'Home':
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nones = ['None' for i in range(5)]
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section= option_menu(None, ["Info", "Data profile",'AutoML'],
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default_index=0, icons=nones,orientation="horizontal")
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if section== 'Info':
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st.title('Main info about service')
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st.write('Some Text about service')
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if section == 'Data profile':
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st.title('This section will give you main information about uploaded dataset')
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st.write('Simply click "Generate new profile" if you want to generate new profile data and click "View old report to load previous profile"')
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if st.checkbox('Huge Dataset'):
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speedup = 'config_minimal.yaml'
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else:
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speedup= 'config_default.yaml'
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if st.button('Generate report'):
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try:
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st_profile_report(get_profile(st.session_state.df, speedup))
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except NameError:
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st.error('Please upload dataset first')
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if selected == 'Classification':
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section = option_menu(None, ["Prep & Train",'Tune & Analyse','Predict'],
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default_index=0,icons=['1-square','1-square','1-square'],orientation="horizontal")
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if section == 'Prep & Train':
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col1, col2 = st.columns([3,1.6])
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with col2:
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try:
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st.title("Prepare you data and train best model")
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st.session_state.targ = st.selectbox('Choose target', st.session_state.df.columns)
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# time = st.slider('budget_time', 0.3, 1.5, 0.5, 0.1)
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dic ={
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'lr':'LogReg',
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'ridge':'Ridge Classifier',
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'lda':'Linear Discriminant Analysis',
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'et':'Extra Trees Classifier',
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'nb':'Naive Bayes',
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'qda':'Quadratic Discriminant Analysis',
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'rf':'Random Forest Classifier',
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'gbc':'Gradient Boosting Classifier',
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'lightgbm':'Light Gradient Boosting Machine',
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'catboost':'CatBoost Classifier',
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'ada':'Ada Boost Classifier',
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'dt':'Decision Tree Classifier',
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'knn':'K Neighbors Classifier',
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'dummy':'Dummy Classifier',
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'svm':'SVM - Linear Kernel'
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}
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model = st.multiselect('Choose model',
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['lr',
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'ridge',
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'lda',
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'et',
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'nb',
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'qda',
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'rf',
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'gbc',
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'lightgbm',
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'catboost',
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'ada',
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'dt',
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'knn',
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'dummy',
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'svm'], help='Blablabla', format_func=lambda x: dic.get(x))
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if st.button('Try model'):
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try:
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st.session_state.best, st.session_state.model_info, st.session_state.metrics_info = prep_and_train(st.session_state.targ, st.session_state.df, model)
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save_model(st.session_state.best, 'dt_pipeline')
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# model_info.to_csv('model_info.csv', index=None)
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# metrics_info.to_csv('metrics_info.csv',index=None)
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with col1:
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st.subheader('Actual Model')
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st.session_state.model_info_last = st.session_state.model_info
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st.session_state.metrics_info_last = st.session_state.metrics_info
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col1, col2 = st.columns([3.5,1.8])
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with col1:
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st.dataframe(st.session_state.metrics_info)
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with col2:
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st.dataframe(st.session_state.model_info)
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except ValueError:
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st.error('Please choose target with binary labels')
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else:
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try:
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with col1:
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st.subheader('Your last teached model')
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col1, col2 = st.columns([3.5,1.8])
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with col1:
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st.dataframe(st.session_state.metrics_info_last)
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with col2:
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st.dataframe(st.session_state.model_info_last)
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except AttributeError:
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st.write('teach the first model')
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except AttributeError:
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st.error('Please load dataset first')
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if section == 'Tune & Analyse':
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st.title('Choose parameters to tune your model')
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metrics_info_last = pd.read_csv('metrics_info.csv', index_col=None)
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st.subheader('Current model')
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st.table(st.session_state.metrics_info_last.head(1))
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col1,col2,col3 = st.columns(3)
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with col1:
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plot_model(st.session_state.best, plot = 'auc', display_format='streamlit')
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with col2:
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plot_model(st.session_state.best, plot = 'threshold', display_format='streamlit')
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with col3:
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plot_model(st.session_state.best, plot = 'confusion_matrix', display_format='streamlit')
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col1, col2 = st.columns([2,4])
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with col2:
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option = st.selectbox(
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'Choose the tuning engine',
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('scikit-learn', 'optuna', 'scikit-optimize'))
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st.session_state.optimize = st.selectbox('Choose metric to optimize', ('Accuracy','AUC','F1'))
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st.session_state.iters = st.slider('n_estimators', 5, 20, 5, 1)
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if st.button('Tune'):
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clf1 = setup(data = st.session_state.df, target = st.session_state.targ)
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st.session_state.tuned_dt = tune_model(estimator=st.session_state.best,n_iter=st.session_state.iters,choose_better=True,optimize=st.session_state.optimize)
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st.session_state.info_df = pull()
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148 |
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with col1:
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try:
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st.dataframe(st.session_state.info_df)
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st.write('Last best params')
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st.write(st.session_state.tuned_dt)
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except AttributeError:
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pass
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automl.py
ADDED
@@ -0,0 +1 @@
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from pycaret.classification import *
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classification.py
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from pycaret.classification import *
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import streamlit as st
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@st.cache_data
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def prep_and_train(targ, data, models=None):
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s = setup(data, target = targ, session_id = 12)
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s_df = pull()
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best = compare_models(include=models)
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best_df = pull()
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return best, s_df, best_df
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@st.cache_resource
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def tuning(_model, n_iters, search_lib):
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tuned_dt = tune_model(estimator=_model, n_iter=n_iters, search_library=search_lib, choose_better=True)
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info_df = pull()
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return tuned_dt, info_df
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config_default.yaml
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1 |
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# Title of the document
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title: "Pandas Profiling Report"
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# Metadata
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dataset:
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description: ""
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creator: ""
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author: ""
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copyright_holder: ""
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copyright_year: ""
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url: ""
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variables:
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descriptions: {}
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# infer dtypes
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infer_dtypes: true
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# Show the description at each variable (in addition to the overview tab)
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show_variable_description: true
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# Number of workers (0=multiprocessing.cpu_count())
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pool_size: 0
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# Show the progress bar
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progress_bar: true
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# Per variable type description settings
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vars:
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num:
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quantiles:
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- 0.05
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- 0.25
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- 0.5
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- 0.75
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- 0.95
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skewness_threshold: 20
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38 |
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low_categorical_threshold: 5
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39 |
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# Set to zero to disable
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40 |
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chi_squared_threshold: 0.999
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41 |
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cat:
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length: true
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43 |
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characters: true
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words: true
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cardinality_threshold: 50
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46 |
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n_obs: 5
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47 |
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# Set to zero to disable
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48 |
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chi_squared_threshold: 0.999
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49 |
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coerce_str_to_date: false
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50 |
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redact: false
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51 |
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histogram_largest: 50
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52 |
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stop_words: []
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53 |
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bool:
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54 |
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n_obs: 3
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55 |
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# string to boolean mapping dict
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56 |
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mappings:
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57 |
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t: true
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58 |
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f: false
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59 |
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yes: true
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60 |
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no: false
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y: true
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n: false
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63 |
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true: true
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false: false
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65 |
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file:
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active: false
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67 |
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image:
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active: false
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exif: true
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hash: true
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71 |
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path:
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active: false
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73 |
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url:
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74 |
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active: false
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75 |
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timeseries:
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76 |
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active: false
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77 |
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autocorrelation: 0.7
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78 |
+
lags: [1, 7, 12, 24, 30]
|
79 |
+
significance: 0.05
|
80 |
+
pacf_acf_lag: 100
|
81 |
+
|
82 |
+
# Sort the variables. Possible values: "ascending", "descending" or null (leaves original sorting)
|
83 |
+
sort: null
|
84 |
+
|
85 |
+
# which diagrams to show
|
86 |
+
missing_diagrams:
|
87 |
+
bar: true
|
88 |
+
matrix: true
|
89 |
+
heatmap: true
|
90 |
+
|
91 |
+
correlations:
|
92 |
+
pearson:
|
93 |
+
calculate: false
|
94 |
+
warn_high_correlations: true
|
95 |
+
threshold: 0.9
|
96 |
+
spearman:
|
97 |
+
calculate: false
|
98 |
+
warn_high_correlations: false
|
99 |
+
threshold: 0.9
|
100 |
+
kendall:
|
101 |
+
calculate: false
|
102 |
+
warn_high_correlations: false
|
103 |
+
threshold: 0.9
|
104 |
+
phi_k:
|
105 |
+
calculate: false
|
106 |
+
warn_high_correlations: false
|
107 |
+
threshold: 0.9
|
108 |
+
cramers:
|
109 |
+
calculate: false
|
110 |
+
warn_high_correlations: true
|
111 |
+
threshold: 0.9
|
112 |
+
auto:
|
113 |
+
calculate: true
|
114 |
+
warn_high_correlations: true
|
115 |
+
threshold: 0.9
|
116 |
+
|
117 |
+
|
118 |
+
# Bivariate / Pairwise relations
|
119 |
+
interactions:
|
120 |
+
targets: []
|
121 |
+
continuous: true
|
122 |
+
|
123 |
+
# For categorical
|
124 |
+
categorical_maximum_correlation_distinct: 100
|
125 |
+
|
126 |
+
report:
|
127 |
+
precision: 10
|
128 |
+
|
129 |
+
# Plot-specific settings
|
130 |
+
plot:
|
131 |
+
# Image format (svg or png)
|
132 |
+
image_format: "svg"
|
133 |
+
dpi: 800
|
134 |
+
|
135 |
+
scatter_threshold: 1000
|
136 |
+
|
137 |
+
correlation:
|
138 |
+
cmap: 'RdBu'
|
139 |
+
bad: '#000000'
|
140 |
+
|
141 |
+
missing:
|
142 |
+
cmap: 'RdBu'
|
143 |
+
# Force labels when there are > 50 variables
|
144 |
+
# https://github.com/ResidentMario/missingno/issues/93#issuecomment-513322615
|
145 |
+
force_labels: true
|
146 |
+
|
147 |
+
cat_frequency:
|
148 |
+
show: true # if false, the category frequency plot is turned off
|
149 |
+
type: 'bar' # options: 'bar', 'pie'
|
150 |
+
max_unique: 10
|
151 |
+
colors: null # use null for default or give a list of matplotlib recognised strings
|
152 |
+
|
153 |
+
histogram:
|
154 |
+
x_axis_labels: true
|
155 |
+
|
156 |
+
# Number of bins (set to 0 to automatically detect the bin size)
|
157 |
+
bins: 50
|
158 |
+
|
159 |
+
# Maximum number of bins (when bins=0)
|
160 |
+
max_bins: 250
|
161 |
+
|
162 |
+
# The number of observations to show
|
163 |
+
n_obs_unique: 5
|
164 |
+
n_extreme_obs: 5
|
165 |
+
n_freq_table_max: 10
|
166 |
+
|
167 |
+
# Use `deep` flag for memory_usage
|
168 |
+
memory_deep: false
|
169 |
+
|
170 |
+
# Configuration related to the duplicates
|
171 |
+
duplicates:
|
172 |
+
head: 10
|
173 |
+
key: "# duplicates"
|
174 |
+
|
175 |
+
# Configuration related to the samples area
|
176 |
+
samples:
|
177 |
+
head: 10
|
178 |
+
tail: 10
|
179 |
+
random: 0
|
180 |
+
|
181 |
+
# Configuration related to the rejection of variables
|
182 |
+
reject_variables: true
|
183 |
+
|
184 |
+
# When in a Jupyter notebook
|
185 |
+
notebook:
|
186 |
+
iframe:
|
187 |
+
height: '800px'
|
188 |
+
width: '100%'
|
189 |
+
# or 'src'
|
190 |
+
attribute: 'srcdoc'
|
191 |
+
|
192 |
+
html:
|
193 |
+
# Minify the html
|
194 |
+
minify_html: true
|
195 |
+
|
196 |
+
# Offline support
|
197 |
+
use_local_assets: true
|
198 |
+
|
199 |
+
# If true, single file, else directory with assets
|
200 |
+
inline: true
|
201 |
+
|
202 |
+
# Show navbar
|
203 |
+
navbar_show: true
|
204 |
+
|
205 |
+
# Assets prefix if inline = true
|
206 |
+
assets_prefix: null
|
207 |
+
|
208 |
+
# Styling options for the HTML report
|
209 |
+
style:
|
210 |
+
theme: null
|
211 |
+
logo: ""
|
212 |
+
primary_colors:
|
213 |
+
- "#ff4b4b"
|
214 |
+
- "#ff4b4b"
|
215 |
+
- "#ff4b4b"
|
216 |
+
|
217 |
+
full_width: false
|
config_minimal.yaml
ADDED
@@ -0,0 +1,217 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# Title of the document
|
2 |
+
title: "Pandas Profiling Report"
|
3 |
+
|
4 |
+
# Metadata
|
5 |
+
dataset:
|
6 |
+
description: ""
|
7 |
+
creator: ""
|
8 |
+
author: ""
|
9 |
+
copyright_holder: ""
|
10 |
+
copyright_year: ""
|
11 |
+
url: ""
|
12 |
+
|
13 |
+
variables:
|
14 |
+
descriptions: {}
|
15 |
+
|
16 |
+
# infer dtypes
|
17 |
+
infer_dtypes: false
|
18 |
+
|
19 |
+
# Show the description at each variable (in addition to the overview tab)
|
20 |
+
show_variable_description: true
|
21 |
+
|
22 |
+
# Number of workers (0=multiprocessing.cpu_count())
|
23 |
+
pool_size: 0
|
24 |
+
|
25 |
+
# Show the progress bar
|
26 |
+
progress_bar: true
|
27 |
+
|
28 |
+
# Per variable type description settings
|
29 |
+
vars:
|
30 |
+
num:
|
31 |
+
quantiles:
|
32 |
+
- 0.05
|
33 |
+
- 0.25
|
34 |
+
- 0.5
|
35 |
+
- 0.75
|
36 |
+
- 0.95
|
37 |
+
skewness_threshold: 20
|
38 |
+
low_categorical_threshold: 5
|
39 |
+
# Set to zero to disable
|
40 |
+
chi_squared_threshold: 0.0
|
41 |
+
cat:
|
42 |
+
length: false
|
43 |
+
characters: false
|
44 |
+
words: false
|
45 |
+
cardinality_threshold: 50
|
46 |
+
n_obs: 5
|
47 |
+
# Set to zero to disable
|
48 |
+
chi_squared_threshold: 0.0
|
49 |
+
coerce_str_to_date: false
|
50 |
+
redact: false
|
51 |
+
histogram_largest: 10
|
52 |
+
stop_words: []
|
53 |
+
|
54 |
+
bool:
|
55 |
+
n_obs: 3
|
56 |
+
# string to boolean mapping dict
|
57 |
+
mappings:
|
58 |
+
t: true
|
59 |
+
f: false
|
60 |
+
yes: true
|
61 |
+
no: false
|
62 |
+
y: true
|
63 |
+
n: false
|
64 |
+
true: true
|
65 |
+
false: false
|
66 |
+
path:
|
67 |
+
active: false
|
68 |
+
file:
|
69 |
+
active: false
|
70 |
+
image:
|
71 |
+
active: false
|
72 |
+
exif: false
|
73 |
+
hash: false
|
74 |
+
url:
|
75 |
+
active: false
|
76 |
+
timeseries:
|
77 |
+
active: false
|
78 |
+
autocorrelation: 0.7
|
79 |
+
lags: [1, 7, 12, 24, 30]
|
80 |
+
significance: 0.05
|
81 |
+
pacf_acf_lag: 100
|
82 |
+
|
83 |
+
# Sort the variables. Possible values: "ascending", "descending" or null (leaves original sorting)
|
84 |
+
sort: null
|
85 |
+
|
86 |
+
# which diagrams to show
|
87 |
+
missing_diagrams:
|
88 |
+
bar: false
|
89 |
+
matrix: false
|
90 |
+
heatmap: false
|
91 |
+
|
92 |
+
correlations:
|
93 |
+
pearson:
|
94 |
+
calculate: false
|
95 |
+
warn_high_correlations: true
|
96 |
+
threshold: 0.9
|
97 |
+
spearman:
|
98 |
+
calculate: false
|
99 |
+
warn_high_correlations: false
|
100 |
+
threshold: 0.9
|
101 |
+
kendall:
|
102 |
+
calculate: false
|
103 |
+
warn_high_correlations: false
|
104 |
+
threshold: 0.9
|
105 |
+
phi_k:
|
106 |
+
calculate: false
|
107 |
+
warn_high_correlations: false
|
108 |
+
threshold: 0.9
|
109 |
+
cramers:
|
110 |
+
calculate: false
|
111 |
+
warn_high_correlations: true
|
112 |
+
threshold: 0.9
|
113 |
+
auto:
|
114 |
+
calculate: false
|
115 |
+
warn_high_correlations: true
|
116 |
+
threshold: 0.9
|
117 |
+
|
118 |
+
|
119 |
+
# Bivariate / Pairwise relations
|
120 |
+
interactions:
|
121 |
+
targets: []
|
122 |
+
continuous: false
|
123 |
+
|
124 |
+
# For categorical
|
125 |
+
categorical_maximum_correlation_distinct: 100
|
126 |
+
|
127 |
+
report:
|
128 |
+
precision: 10
|
129 |
+
|
130 |
+
# Plot-specific settings
|
131 |
+
plot:
|
132 |
+
# Image format (svg or png)
|
133 |
+
image_format: "svg"
|
134 |
+
dpi: 800
|
135 |
+
|
136 |
+
scatter_threshold: 1000
|
137 |
+
|
138 |
+
correlation:
|
139 |
+
cmap: 'RdBu'
|
140 |
+
bad: '#000000'
|
141 |
+
|
142 |
+
missing:
|
143 |
+
cmap: 'RdBu'
|
144 |
+
# Force labels when there are > 50 variables
|
145 |
+
force_labels: true
|
146 |
+
|
147 |
+
cat_frequency:
|
148 |
+
show: true # if false, the category frequency plot is turned off
|
149 |
+
type: 'bar' # options: 'bar', 'pie'
|
150 |
+
max_unique: 0
|
151 |
+
colors: null # use null for default or give a list of matplotlib recognised strings
|
152 |
+
|
153 |
+
histogram:
|
154 |
+
x_axis_labels: true
|
155 |
+
|
156 |
+
# Number of bins (set to 0 to automatically detect the bin size)
|
157 |
+
bins: 50
|
158 |
+
|
159 |
+
# Maximum number of bins (when bins=0)
|
160 |
+
max_bins: 250
|
161 |
+
|
162 |
+
# The number of observations to show
|
163 |
+
n_obs_unique: 5
|
164 |
+
n_extreme_obs: 5
|
165 |
+
n_freq_table_max: 10
|
166 |
+
|
167 |
+
# Use `deep` flag for memory_usage
|
168 |
+
memory_deep: false
|
169 |
+
|
170 |
+
# Configuration related to the duplicates
|
171 |
+
duplicates:
|
172 |
+
head: 0
|
173 |
+
key: "# duplicates"
|
174 |
+
|
175 |
+
# Configuration related to the samples area
|
176 |
+
samples:
|
177 |
+
head: 0
|
178 |
+
tail: 0
|
179 |
+
random: 0
|
180 |
+
|
181 |
+
# Configuration related to the rejection of variables
|
182 |
+
reject_variables: true
|
183 |
+
|
184 |
+
# When in a Jupyter notebook
|
185 |
+
notebook:
|
186 |
+
iframe:
|
187 |
+
height: '800px'
|
188 |
+
width: '100%'
|
189 |
+
# or 'src'
|
190 |
+
attribute: 'srcdoc'
|
191 |
+
|
192 |
+
html:
|
193 |
+
# Minify the html
|
194 |
+
minify_html: true
|
195 |
+
|
196 |
+
# Offline support
|
197 |
+
use_local_assets: true
|
198 |
+
|
199 |
+
# If true, single file, else directory with assets
|
200 |
+
inline: true
|
201 |
+
|
202 |
+
# Show navbar
|
203 |
+
navbar_show: true
|
204 |
+
|
205 |
+
# Assets prefix if inline = true
|
206 |
+
assets_prefix: null
|
207 |
+
|
208 |
+
# Styling options for the HTML report
|
209 |
+
style:
|
210 |
+
theme: null
|
211 |
+
logo: ""
|
212 |
+
primary_colors:
|
213 |
+
- "#ff4b4b"
|
214 |
+
- "#ff4b4b"
|
215 |
+
- "#ff4b4b"
|
216 |
+
|
217 |
+
full_width: false
|
dataset.csv
ADDED
The diff for this file is too large to render.
See raw diff
|
|
dt_pipeline.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f2a7a8683de573281d47244bf3082084758449b707a5d29c9f2f0e59148372d4
|
3 |
+
size 1423
|
get_profile.py
ADDED
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
from pandas_profiling import ProfileReport
|
2 |
+
from streamlit_pandas_profiling import st_profile_report
|
3 |
+
import streamlit as st
|
4 |
+
|
5 |
+
@st.cache_resource
|
6 |
+
def get_profile(data, config):
|
7 |
+
profile_df = ProfileReport(data, config_file=config)
|
8 |
+
return profile_df
|
logs.log
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:281d935e21534745dfa0bc192d70b483205199074da960eae51398837b9a5cee
|
3 |
+
size 11045508
|
metrics_info.csv
ADDED
@@ -0,0 +1,16 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
Model,Accuracy,AUC,Recall,Prec.,F1,Kappa,MCC,TT (Sec)
|
2 |
+
Logistic Regression,0.8122,0.86,0.6701,0.8088,0.7308,0.5891,0.5969,0.268
|
3 |
+
Ridge Classifier,0.8121,0.0,0.6743,0.8075,0.7319,0.5897,0.5977,0.284
|
4 |
+
Linear Discriminant Analysis,0.8105,0.86,0.687,0.7978,0.7343,0.5888,0.5964,0.254
|
5 |
+
Extra Trees Classifier,0.8025,0.8548,0.6322,0.8124,0.7035,0.5617,0.5755,0.362
|
6 |
+
Quadratic Discriminant Analysis,0.732,0.7469,0.4694,0.7386,0.5536,0.3869,0.4118,0.284
|
7 |
+
Naive Bayes,0.7303,0.8206,0.4272,0.7762,0.5438,0.3769,0.4135,0.25
|
8 |
+
Random Forest Classifier,0.7238,0.853,0.3645,0.8078,0.4889,0.3449,0.3968,0.305
|
9 |
+
Light Gradient Boosting Machine,0.7046,0.7528,0.2973,0.8139,0.42,0.2867,0.3499,0.25
|
10 |
+
Ada Boost Classifier,0.7031,0.8223,0.3226,0.7584,0.4363,0.2908,0.339,0.3
|
11 |
+
Decision Tree Classifier,0.703,0.6303,0.3183,0.7848,0.4332,0.2894,0.3408,0.27
|
12 |
+
CatBoost Classifier,0.703,0.8354,0.31,0.7986,0.4337,0.2887,0.3486,0.483
|
13 |
+
Gradient Boosting Classifier,0.7014,0.7813,0.2931,0.8077,0.4142,0.2793,0.3421,0.302
|
14 |
+
K Neighbors Classifier,0.6485,0.6318,0.4143,0.5685,0.4721,0.2197,0.2294,0.293
|
15 |
+
Dummy Classifier,0.6164,0.5,0.0,0.0,0.0,0.0,0.0,0.277
|
16 |
+
SVM - Linear Kernel,0.5988,0.0,0.3672,0.6084,0.3292,0.1146,0.1667,0.26
|
model_info.csv
ADDED
@@ -0,0 +1,25 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
Description,Value
|
2 |
+
Session id,12
|
3 |
+
Target,Survived
|
4 |
+
Target type,Binary
|
5 |
+
Original data shape,"(891, 12)"
|
6 |
+
Transformed data shape,"(891, 14)"
|
7 |
+
Transformed train set shape,"(623, 14)"
|
8 |
+
Transformed test set shape,"(268, 14)"
|
9 |
+
Ordinal features,1
|
10 |
+
Numeric features,6
|
11 |
+
Categorical features,5
|
12 |
+
Rows with missing values,79.5%
|
13 |
+
Preprocess,True
|
14 |
+
Imputation type,simple
|
15 |
+
Numeric imputation,mean
|
16 |
+
Categorical imputation,mode
|
17 |
+
Maximum one-hot encoding,25
|
18 |
+
Encoding method,
|
19 |
+
Fold Generator,StratifiedKFold
|
20 |
+
Fold Number,10
|
21 |
+
CPU Jobs,-1
|
22 |
+
Use GPU,False
|
23 |
+
Log Experiment,False
|
24 |
+
Experiment Name,clf-default-name
|
25 |
+
USI,53c2
|
requirements.txt
ADDED
@@ -0,0 +1,431 @@
|
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|
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|
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|
|
|
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|
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|
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|
|
|
|
|
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|
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|
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|
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|
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|
|
|
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|
|
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|
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|
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|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
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|
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|
|
|
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|
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|
|
|
|
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|
|
|
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|
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|
|
|
|
|
|
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|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
aiogram==2.25.1
|
2 |
+
aiohttp==3.8.4
|
3 |
+
aiosignal==1.3.1
|
4 |
+
alabaster @ file:///home/ktietz/src/ci/alabaster_1611921544520/work
|
5 |
+
alembic==1.10.3
|
6 |
+
altair==4.2.2
|
7 |
+
anaconda-client==1.11.0
|
8 |
+
anaconda-navigator==2.3.1
|
9 |
+
anaconda-project @ file:///opt/conda/conda-bld/anaconda-project_1660339890420/work
|
10 |
+
ansi2html==1.8.0
|
11 |
+
anyio @ file:///tmp/build/80754af9/anyio_1644463572971/work/dist
|
12 |
+
appdirs==1.4.4
|
13 |
+
argon2-cffi @ file:///opt/conda/conda-bld/argon2-cffi_1645000214183/work
|
14 |
+
argon2-cffi-bindings @ file:///tmp/build/80754af9/argon2-cffi-bindings_1644569679365/work
|
15 |
+
arrow @ file:///opt/conda/conda-bld/arrow_1649166651673/work
|
16 |
+
astroid @ file:///tmp/abs_e5wkt48jiz/croots/recipe/astroid_1659023120113/work
|
17 |
+
astropy @ file:///opt/conda/conda-bld/astropy_1657786094003/work
|
18 |
+
async-timeout==4.0.2
|
19 |
+
atomicwrites==1.4.0
|
20 |
+
attrs @ file:///opt/conda/conda-bld/attrs_1642510447205/work
|
21 |
+
Automat @ file:///tmp/build/80754af9/automat_1600298431173/work
|
22 |
+
autopep8 @ file:///opt/conda/conda-bld/autopep8_1650463822033/work
|
23 |
+
Babel @ file:///tmp/build/80754af9/babel_1620871417480/work
|
24 |
+
backcall @ file:///home/ktietz/src/ci/backcall_1611930011877/work
|
25 |
+
backports.functools-lru-cache @ file:///tmp/build/80754af9/backports.functools_lru_cache_1618170165463/work
|
26 |
+
backports.tempfile @ file:///home/linux1/recipes/ci/backports.tempfile_1610991236607/work
|
27 |
+
backports.weakref==1.0.post1
|
28 |
+
bcrypt @ file:///tmp/abs_6fpe92qzzo/croots/recipe/bcrypt_1659554336150/work
|
29 |
+
beautifulsoup4 @ file:///opt/conda/conda-bld/beautifulsoup4_1650462163268/work
|
30 |
+
binaryornot @ file:///tmp/build/80754af9/binaryornot_1617751525010/work
|
31 |
+
bitarray @ file:///opt/conda/conda-bld/bitarray_1657739645104/work
|
32 |
+
bkcharts==0.2
|
33 |
+
black @ file:///opt/conda/conda-bld/black_1660237809219/work
|
34 |
+
bleach @ file:///opt/conda/conda-bld/bleach_1641577558959/work
|
35 |
+
blinker==1.5
|
36 |
+
bokeh @ file:///tmp/abs_34854e1f-d7d3-4f22-85d9-1075588e4ecdga64o0qg/croots/recipe/bokeh_1658136654619/work
|
37 |
+
boto3 @ file:///tmp/abs_ae3c72db-af47-4298-baea-7270430e2c96scbpg1_h/croots/recipe/boto3_1657820109150/work
|
38 |
+
botocore @ file:///opt/conda/conda-bld/botocore_1657739486257/work
|
39 |
+
Bottleneck @ file:///opt/conda/conda-bld/bottleneck_1657175564434/work
|
40 |
+
brotlipy==0.7.0
|
41 |
+
cachetools==5.3.0
|
42 |
+
catboost==1.1.1
|
43 |
+
category-encoders==2.6.0
|
44 |
+
certifi @ file:///opt/conda/conda-bld/certifi_1663615672595/work/certifi
|
45 |
+
cffi @ file:///tmp/abs_98z5h56wf8/croots/recipe/cffi_1659598650955/work
|
46 |
+
chardet==3.0.4
|
47 |
+
charset-normalizer @ file:///tmp/build/80754af9/charset-normalizer_1630003229654/work
|
48 |
+
click @ file:///tmp/build/80754af9/click_1646056590078/work
|
49 |
+
clip @ git+https://github.com/openai/CLIP.git@a9b1bf5920416aaeaec965c25dd9e8f98c864f16
|
50 |
+
clip-by-openai==1.1
|
51 |
+
cloudpickle @ file:///tmp/build/80754af9/cloudpickle_1632508026186/work
|
52 |
+
clyent==1.2.2
|
53 |
+
cmaes==0.9.1
|
54 |
+
colorama @ file:///opt/conda/conda-bld/colorama_1657009087971/work
|
55 |
+
colorcet @ file:///tmp/build/80754af9/colorcet_1651851439427/work
|
56 |
+
colorlog==6.7.0
|
57 |
+
conda==23.1.0
|
58 |
+
conda-build==3.22.0
|
59 |
+
conda-content-trust @ file:///tmp/abs_5952f1c8-355c-4855-ad2e-538535021ba5h26t22e5/croots/recipe/conda-content-trust_1658126371814/work
|
60 |
+
conda-pack @ file:///tmp/build/80754af9/conda-pack_1611163042455/work
|
61 |
+
conda-package-handling @ file:///opt/conda/conda-bld/conda-package-handling_1663598473529/work
|
62 |
+
conda-repo-cli==1.0.20
|
63 |
+
conda-token @ file:///Users/paulyim/miniconda3/envs/c3i/conda-bld/conda-token_1662660369760/work
|
64 |
+
conda-verify==3.4.2
|
65 |
+
constantly==15.1.0
|
66 |
+
cookiecutter @ file:///opt/conda/conda-bld/cookiecutter_1649151442564/work
|
67 |
+
cryptography @ file:///tmp/build/80754af9/cryptography_1652101588893/work
|
68 |
+
cssselect==1.1.0
|
69 |
+
cycler @ file:///tmp/build/80754af9/cycler_1637851556182/work
|
70 |
+
Cython @ file:///opt/conda/conda-bld/cython_1663692770955/work
|
71 |
+
cytoolz==0.11.0
|
72 |
+
daal4py==2021.6.0
|
73 |
+
dash==2.9.2
|
74 |
+
dash-core-components==2.0.0
|
75 |
+
dash-html-components==2.0.0
|
76 |
+
dash-table==5.0.0
|
77 |
+
dask @ file:///tmp/abs_994957d9-ec12-411f-b953-c010f9d489d10hj3gz4k/croots/recipe/dask-core_1658513209934/work
|
78 |
+
datashader @ file:///tmp/abs_aa58dfo4_s/croots/recipe/datashader_1659349033064/work
|
79 |
+
datashape==0.5.4
|
80 |
+
debugpy @ file:///tmp/build/80754af9/debugpy_1637091799509/work
|
81 |
+
decorator @ file:///opt/conda/conda-bld/decorator_1643638310831/work
|
82 |
+
defusedxml @ file:///tmp/build/80754af9/defusedxml_1615228127516/work
|
83 |
+
Deprecated==1.2.13
|
84 |
+
deprecation==2.1.0
|
85 |
+
diff-match-patch @ file:///Users/ktietz/demo/mc3/conda-bld/diff-match-patch_1630511840874/work
|
86 |
+
diffusers==0.14.0
|
87 |
+
dill @ file:///tmp/build/80754af9/dill_1623919422540/work
|
88 |
+
distlib==0.3.6
|
89 |
+
distributed @ file:///tmp/abs_593da390-bd12-4acc-ba49-4c9993cbe8abgqg_w3rb/croots/recipe/distributed_1658520746481/work
|
90 |
+
docutils @ file:///opt/conda/conda-bld/docutils_1657175430858/work
|
91 |
+
entrypoints @ file:///tmp/build/80754af9/entrypoints_1649926439650/work
|
92 |
+
et-xmlfile==1.1.0
|
93 |
+
faiss-cpu==1.7.3
|
94 |
+
fastjsonschema @ file:///opt/conda/conda-bld/python-fastjsonschema_1661371079312/work
|
95 |
+
filelock @ file:///opt/conda/conda-bld/filelock_1647002191454/work
|
96 |
+
flake8 @ file:///opt/conda/conda-bld/flake8_1648129545443/work
|
97 |
+
Flask @ file:///home/ktietz/src/ci/flask_1611932660458/work
|
98 |
+
fonttools==4.25.0
|
99 |
+
frozenlist==1.3.3
|
100 |
+
fsspec @ file:///opt/conda/conda-bld/fsspec_1659972197723/work
|
101 |
+
ftfy==6.1.1
|
102 |
+
future @ file:///tmp/build/80754af9/future_1607571303524/work
|
103 |
+
gensim @ file:///tmp/build/80754af9/gensim_1646806807927/work
|
104 |
+
gitdb==4.0.10
|
105 |
+
GitPython==3.1.31
|
106 |
+
glob2 @ file:///home/linux1/recipes/ci/glob2_1610991677669/work
|
107 |
+
gmpy2 @ file:///tmp/build/80754af9/gmpy2_1645438755360/work
|
108 |
+
googletrans==3.0.0
|
109 |
+
graphviz==0.20.1
|
110 |
+
greenlet @ file:///tmp/build/80754af9/greenlet_1628888132713/work
|
111 |
+
grpcio==1.53.0
|
112 |
+
h11==0.9.0
|
113 |
+
h2==3.2.0
|
114 |
+
h5py @ file:///tmp/abs_4aewd3wzey/croots/recipe/h5py_1659091371897/work
|
115 |
+
HeapDict @ file:///Users/ktietz/demo/mc3/conda-bld/heapdict_1630598515714/work
|
116 |
+
holoviews @ file:///tmp/abs_eecc808c-455e-4be4-9911-ecf8341b3a34jfwskiqe/croots/recipe/holoviews_1658171506757/work
|
117 |
+
hpack==3.0.0
|
118 |
+
hstspreload==2023.1.1
|
119 |
+
htmlmin==0.1.12
|
120 |
+
httpcore==0.9.1
|
121 |
+
httpx==0.13.3
|
122 |
+
huggingface-hub==0.13.2
|
123 |
+
hvplot @ file:///tmp/abs_6fcys5jcv1/croots/recipe/hvplot_1659026496554/work
|
124 |
+
hyperframe==5.2.0
|
125 |
+
hyperlink @ file:///tmp/build/80754af9/hyperlink_1610130746837/work
|
126 |
+
hyperopt==0.2.7
|
127 |
+
idna==2.10
|
128 |
+
imagecodecs @ file:///opt/conda/conda-bld/imagecodecs_1664561985385/work
|
129 |
+
ImageHash==4.3.1
|
130 |
+
imageio @ file:///tmp/abs_cd920173-f360-47c5-97b0-bf4d1076d5d4dvic0oys/croots/recipe/imageio_1658785036907/work
|
131 |
+
imageloader==0.0.5
|
132 |
+
imagesize @ file:///opt/conda/conda-bld/imagesize_1657179498843/work
|
133 |
+
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incremental @ file:///tmp/build/80754af9/incremental_1636629750599/work
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intake @ file:///opt/conda/conda-bld/intake_1647436631684/work
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isort @ file:///tmp/build/80754af9/isort_1628603791788/work
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itemadapter @ file:///tmp/build/80754af9/itemadapter_1626442940632/work
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jedi @ file:///tmp/build/80754af9/jedi_1644297102865/work
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jeepney @ file:///tmp/build/80754af9/jeepney_1627537048313/work
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jellyfish @ file:///tmp/build/80754af9/jellyfish_1647944426575/work
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jinja2-time @ file:///opt/conda/conda-bld/jinja2-time_1649251842261/work
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jmespath @ file:///Users/ktietz/demo/mc3/conda-bld/jmespath_1630583964805/work
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json5 @ file:///tmp/build/80754af9/json5_1624432770122/work
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jupyter-console @ file:///opt/conda/conda-bld/jupyter_console_1647002188872/work
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jupyter-kite==2.0.2
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jupyterlab @ file:///tmp/abs_12f3h01vmy/croots/recipe/jupyterlab_1658907535764/work
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jupyterlab-server @ file:///opt/conda/conda-bld/jupyterlab_server_1644500396812/work
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keyring @ file:///tmp/build/80754af9/keyring_1638531355686/work
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kiwisolver @ file:///opt/conda/conda-bld/kiwisolver_1653292039266/work
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lazy-object-proxy @ file:///tmp/build/80754af9/lazy-object-proxy_1616529027849/work
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libarchive-c @ file:///tmp/build/80754af9/python-libarchive-c_1617780486945/work
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libretranslatepy==2.1.1
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lightgbm==3.3.5
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llvmlite==0.38.0
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locket @ file:///opt/conda/conda-bld/locket_1652903118915/work
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lxml @ file:///opt/conda/conda-bld/lxml_1657545139709/work
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lz4 @ file:///tmp/build/80754af9/lz4_1619516502891/work
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magic-filter==1.0.9
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Markdown @ file:///tmp/build/80754af9/markdown_1614363852612/work
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markdown-it-py==2.2.0
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MarkupSafe @ file:///tmp/build/80754af9/markupsafe_1621523467000/work
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matplotlib @ file:///opt/conda/conda-bld/matplotlib-suite_1660167928326/work
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matplotlib-inline @ file:///opt/conda/conda-bld/matplotlib-inline_1662014470464/work
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mccabe @ file:///opt/conda/conda-bld/mccabe_1644221741721/work
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mistune @ file:///tmp/build/80754af9/mistune_1607364877025/work
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mkl-service==2.4.0
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mock @ file:///tmp/build/80754af9/mock_1607622725907/work
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mpmath==1.2.1
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msgpack @ file:///opt/conda/conda-bld/msgpack-python_1652362659880/work
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multidict==6.0.4
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multimethod==1.9.1
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multipledispatch @ file:///tmp/build/80754af9/multipledispatch_1607574243360/work
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munkres==1.1.4
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mypy-extensions==0.4.3
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navigator-updater==0.3.0
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nbclient @ file:///tmp/build/80754af9/nbclient_1650290509967/work
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nbconvert @ file:///opt/conda/conda-bld/nbconvert_1649751911790/work
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nbformat @ file:///opt/conda/conda-bld/nbformat_1663744952973/work
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networkx @ file:///opt/conda/conda-bld/networkx_1657784097507/work
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nltk @ file:///opt/conda/conda-bld/nltk_1645628263994/work
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nose @ file:///opt/conda/conda-bld/nose_1642704612149/work
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notebook @ file:///tmp/abs_abf6xa6h6f/croots/recipe/notebook_1659083654985/work
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numba @ file:///opt/conda/conda-bld/numba_1648040517072/work
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numexpr @ file:///opt/conda/conda-bld/numexpr_1656940300424/work
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numpydoc @ file:///opt/conda/conda-bld/numpydoc_1657529872251/work
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olefile @ file:///Users/ktietz/demo/mc3/conda-bld/olefile_1629805411829/work
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opencv-python==4.7.0.72
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openpyxl==3.0.10
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optuna==3.1.1
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orjson==3.8.10
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packaging @ file:///tmp/build/80754af9/packaging_1637314298585/work
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pandas==1.4.4
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pandas-profiling==3.6.6
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panel @ file:///tmp/abs_bb3d3b2f-b3ea-41c0-a72e-8f54852d5cdfs70inytz/croots/recipe/panel_1658133826470/work
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param @ file:///tmp/build/80754af9/param_1636647414893/work
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parsel @ file:///tmp/build/80754af9/parsel_1646722533460/work
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parso @ file:///opt/conda/conda-bld/parso_1641458642106/work
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partd @ file:///opt/conda/conda-bld/partd_1647245470509/work
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pathlib @ file:///Users/ktietz/demo/mc3/conda-bld/pathlib_1629713961906/work
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pathspec @ file:///tmp/abs_1foqurpsov/croots/recipe/pathspec_1659627126545/work
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patsy==0.5.2
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pep8==1.7.1
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pexpect @ file:///tmp/build/80754af9/pexpect_1605563209008/work
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phik==0.12.3
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pickleshare @ file:///tmp/build/80754af9/pickleshare_1606932040724/work
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pkginfo @ file:///tmp/build/80754af9/pkginfo_1643162084911/work
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platformdirs @ file:///opt/conda/conda-bld/platformdirs_1662711380096/work
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plotly @ file:///tmp/abs_7afcdfad-dbbb-49d2-adea-186abf525c45jbnd8p95/croots/recipe/plotly_1658160053621/work
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plotly-resampler==0.8.3.2
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pluggy @ file:///tmp/build/80754af9/pluggy_1648024445381/work
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ply==3.11
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pmdarima==2.0.3
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poyo @ file:///tmp/build/80754af9/poyo_1617751526755/work
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prometheus-client @ file:///tmp/abs_d3zeliano1/croots/recipe/prometheus_client_1659455100375/work
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prompt-toolkit @ file:///tmp/build/80754af9/prompt-toolkit_1633440160888/work
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248 |
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Protego @ file:///tmp/build/80754af9/protego_1598657180827/work
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protobuf==3.20.3
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psutil @ file:///opt/conda/conda-bld/psutil_1656431268089/work
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ptyprocess @ file:///tmp/build/80754af9/ptyprocess_1609355006118/work/dist/ptyprocess-0.7.0-py2.py3-none-any.whl
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py @ file:///opt/conda/conda-bld/py_1644396412707/work
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py4j==0.10.9.7
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pyaml==21.10.1
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pyarrow==11.0.0
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pyasn1 @ file:///Users/ktietz/demo/mc3/conda-bld/pyasn1_1629708007385/work
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pyasn1-modules==0.2.8
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pycaret==3.0.0
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pycodestyle @ file:///tmp/build/80754af9/pycodestyle_1636635402688/work
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pycosat==0.6.3
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pycparser @ file:///tmp/build/80754af9/pycparser_1636541352034/work
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pyct @ file:///tmp/abs_68a517ee-55fb-480e-82ab-1a8adb440a58x7qfc024/croots/recipe/pyct_1658500310800/work
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pycurl==7.45.1
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pydantic==1.10.7
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pydeck==0.8.0
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PyDispatcher==2.0.5
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pydocstyle @ file:///tmp/build/80754af9/pydocstyle_1621600989141/work
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pyerfa @ file:///tmp/build/80754af9/pyerfa_1621556109336/work
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pyfiglet==0.7
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pyflakes @ file:///tmp/build/80754af9/pyflakes_1636644436481/work
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Pygments==2.14.0
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PyHamcrest @ file:///tmp/build/80754af9/pyhamcrest_1615748656804/work
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PyJWT @ file:///opt/conda/conda-bld/pyjwt_1657544592787/work
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274 |
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pylint @ file:///tmp/abs_6fxmc66kyk/croots/recipe/pylint_1659110350161/work
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pyls-spyder==0.4.0
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276 |
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Pympler==1.0.1
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277 |
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pynndescent==0.5.8
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278 |
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pyod==1.0.9
|
279 |
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pyodbc @ file:///tmp/abs_d365zrcsdp/croots/recipe/pyodbc_1659513794382/work
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280 |
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pyOpenSSL @ file:///opt/conda/conda-bld/pyopenssl_1643788558760/work
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281 |
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pyparsing @ file:///opt/conda/conda-bld/pyparsing_1661452539315/work
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PyQt5-sip==12.11.0
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pyrsistent @ file:///tmp/build/80754af9/pyrsistent_1636110951836/work
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284 |
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PySocks @ file:///tmp/build/80754af9/pysocks_1605305812635/work
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pytest==7.1.2
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286 |
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python-dateutil @ file:///tmp/build/80754af9/python-dateutil_1626374649649/work
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287 |
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python-decouple==3.8
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288 |
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python-lsp-black @ file:///opt/conda/conda-bld/python-lsp-black_1661852031497/work
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289 |
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python-lsp-jsonrpc==1.0.0
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290 |
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python-lsp-server @ file:///opt/conda/conda-bld/python-lsp-server_1661813814476/work
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python-slugify @ file:///tmp/build/80754af9/python-slugify_1620405669636/work
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292 |
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python-snappy @ file:///tmp/build/80754af9/python-snappy_1610133040135/work
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293 |
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pytz @ file:///opt/conda/conda-bld/pytz_1654762638606/work
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294 |
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pytz-deprecation-shim==0.1.0.post0
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295 |
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pyviz-comms @ file:///tmp/build/80754af9/pyviz_comms_1623747165329/work
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PyWavelets @ file:///tmp/build/80754af9/pywavelets_1648710015787/work
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297 |
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pyxdg @ file:///tmp/build/80754af9/pyxdg_1603822279816/work
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PyYAML==6.0
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pyzmq @ file:///opt/conda/conda-bld/pyzmq_1657724186960/work
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QDarkStyle @ file:///tmp/build/80754af9/qdarkstyle_1617386714626/work
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301 |
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qstylizer @ file:///tmp/build/80754af9/qstylizer_1617713584600/work/dist/qstylizer-0.1.10-py2.py3-none-any.whl
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QtAwesome @ file:///tmp/build/80754af9/qtawesome_1637160816833/work
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qtconsole @ file:///opt/conda/conda-bld/qtconsole_1662018252641/work
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QtPy @ file:///opt/conda/conda-bld/qtpy_1662014892439/work
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305 |
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queuelib==1.5.0
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ray==2.3.1
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307 |
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regex @ file:///tmp/abs_41f5bce5-0a2e-45aa-b231-1fd2fbd57753gfpe6sjm/croots/recipe/regex_1658257178822/work
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requests @ file:///opt/conda/conda-bld/requests_1657734628632/work
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requests-file @ file:///Users/ktietz/demo/mc3/conda-bld/requests-file_1629455781986/work
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retrying==1.3.4
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311 |
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rfc3986==1.5.0
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312 |
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rich==13.3.1
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rope @ file:///opt/conda/conda-bld/rope_1643788605236/work
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Rtree @ file:///tmp/build/80754af9/rtree_1618420843093/work
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315 |
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ruamel-yaml-conda @ file:///tmp/build/80754af9/ruamel_yaml_1616016711199/work
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ruamel.yaml @ file:///croot/ruamel.yaml_1666304550667/work
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ruamel.yaml.clib @ file:///croot/ruamel.yaml.clib_1666302247304/work
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s3transfer @ file:///opt/conda/conda-bld/s3transfer_1654524197066/work
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schemdraw==0.16
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scikit-image @ file:///tmp/build/80754af9/scikit-image_1648214171611/work
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scikit-learn @ file:///tmp/build/80754af9/scikit-learn_1642617106979/work
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scikit-learn-intelex==2021.20221004.171807
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scikit-optimize==0.9.0
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324 |
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scikit-plot==0.3.7
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325 |
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scipy==1.9.3
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326 |
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Scrapy @ file:///tmp/abs_e3bmwi01y8/croots/recipe/scrapy_1659598696235/work
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seaborn @ file:///tmp/build/80754af9/seaborn_1629307859561/work
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328 |
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SecretStorage @ file:///tmp/build/80754af9/secretstorage_1614022780358/work
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semver==2.13.0
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330 |
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Send2Trash @ file:///tmp/build/80754af9/send2trash_1632406701022/work
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service-identity @ file:///Users/ktietz/demo/mc3/conda-bld/service_identity_1629460757137/work
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332 |
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shap==0.41.0
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333 |
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sip @ file:///tmp/abs_44cd77b_pu/croots/recipe/sip_1659012365470/work
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334 |
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six @ file:///tmp/build/80754af9/six_1644875935023/work
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335 |
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sktime==0.17.0
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slicer==0.0.7
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smart-open @ file:///opt/conda/conda-bld/smart_open_1651563547610/work
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338 |
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smmap==5.0.0
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sniffio @ file:///tmp/build/80754af9/sniffio_1614030464178/work
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snowballstemmer @ file:///tmp/build/80754af9/snowballstemmer_1637937080595/work
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sortedcollections @ file:///tmp/build/80754af9/sortedcollections_1611172717284/work
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sortedcontainers @ file:///tmp/build/80754af9/sortedcontainers_1623949099177/work
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soupsieve @ file:///tmp/build/80754af9/soupsieve_1636706018808/work
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Sphinx @ file:///opt/conda/conda-bld/sphinx_1657784123546/work
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sphinxcontrib-applehelp @ file:///home/ktietz/src/ci/sphinxcontrib-applehelp_1611920841464/work
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sphinxcontrib-devhelp @ file:///home/ktietz/src/ci/sphinxcontrib-devhelp_1611920923094/work
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sphinxcontrib-htmlhelp @ file:///tmp/build/80754af9/sphinxcontrib-htmlhelp_1623945626792/work
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sphinxcontrib-jsmath @ file:///home/ktietz/src/ci/sphinxcontrib-jsmath_1611920942228/work
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sphinxcontrib-qthelp @ file:///home/ktietz/src/ci/sphinxcontrib-qthelp_1611921055322/work
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sphinxcontrib-serializinghtml @ file:///tmp/build/80754af9/sphinxcontrib-serializinghtml_1624451540180/work
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spyder @ file:///opt/conda/conda-bld/spyder_1663056818299/work
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352 |
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spyder-kernels @ file:///opt/conda/conda-bld/spyder-kernels_1662457880976/work
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353 |
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SQLAlchemy @ file:///tmp/abs_18b3238f-9c23-4182-a392-63af30a93c1er8j_yw60/croots/recipe/sqlalchemy_1657867856580/work
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statsmodels @ file:///tmp/build/80754af9/statsmodels_1648015433305/work
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streamlit==1.21.0
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streamlit-aggrid==0.3.4.post3
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streamlit-option-menu==0.3.2
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streamlit-pandas-profiling==0.1.3
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streamlit-space==0.1.5
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streamlit-toggle==0.1.3
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streamlit-toggle-switch==1.0.2
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362 |
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sympy @ file:///tmp/build/80754af9/sympy_1647853653589/work
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363 |
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tables @ file:///tmp/build/80754af9/pytables_1607975397488/work
|
364 |
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tabulate @ file:///opt/conda/conda-bld/tabulate_1657784105888/work
|
365 |
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tangled-up-in-unicode==0.2.0
|
366 |
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tbats==1.1.2
|
367 |
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TBB==0.2
|
368 |
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tblib @ file:///Users/ktietz/demo/mc3/conda-bld/tblib_1629402031467/work
|
369 |
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tenacity @ file:///tmp/abs_9ca5cd06-f53b-4ea6-8eea-954e11157fddo5mhurpp/croots/recipe/tenacity_1657899103026/work
|
370 |
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tensorboardX==2.6
|
371 |
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terminado @ file:///tmp/build/80754af9/terminado_1644322582718/work
|
372 |
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testpath @ file:///opt/conda/conda-bld/testpath_1655908557405/work
|
373 |
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text-unidecode @ file:///Users/ktietz/demo/mc3/conda-bld/text-unidecode_1629401354553/work
|
374 |
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textdistance @ file:///tmp/build/80754af9/textdistance_1612461398012/work
|
375 |
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threadpoolctl @ file:///Users/ktietz/demo/mc3/conda-bld/threadpoolctl_1629802263681/work
|
376 |
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three-merge @ file:///tmp/build/80754af9/three-merge_1607553261110/work
|
377 |
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tifffile @ file:///tmp/build/80754af9/tifffile_1627275862826/work
|
378 |
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tinycss @ file:///tmp/build/80754af9/tinycss_1617713798712/work
|
379 |
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tldextract @ file:///opt/conda/conda-bld/tldextract_1646638314385/work
|
380 |
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tokenizers==0.13.2
|
381 |
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toml @ file:///tmp/build/80754af9/toml_1616166611790/work
|
382 |
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tomli @ file:///opt/conda/conda-bld/tomli_1657175507142/work
|
383 |
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tomlkit @ file:///tmp/abs_56_0lnnq5x/croots/recipe/tomlkit_1658946880479/work
|
384 |
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toolz @ file:///tmp/build/80754af9/toolz_1636545406491/work
|
385 |
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torch==1.7.1
|
386 |
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torchaudio==0.13.1
|
387 |
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torchutils==0.0.4
|
388 |
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torchvision==0.8.2
|
389 |
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tornado @ file:///tmp/build/80754af9/tornado_1606942317143/work
|
390 |
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tqdm @ file:///opt/conda/conda-bld/tqdm_1664392687731/work
|
391 |
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trace-updater==0.0.9.1
|
392 |
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traitlets @ file:///tmp/build/80754af9/traitlets_1636710298902/work
|
393 |
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transformers==4.27.4
|
394 |
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translate==3.6.1
|
395 |
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treeinterpreter==0.2.3
|
396 |
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tune-sklearn==0.4.5
|
397 |
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Twisted @ file:///tmp/abs_82802zpkox/croots/recipe/twisted_1659592759417/work
|
398 |
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typeguard==2.13.3
|
399 |
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types-PyYAML==6.0.12.9
|
400 |
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typing_extensions @ file:///tmp/abs_ben9emwtky/croots/recipe/typing_extensions_1659638822008/work
|
401 |
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tzdata==2022.7
|
402 |
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tzlocal==4.2
|
403 |
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ujson @ file:///opt/conda/conda-bld/ujson_1657544923770/work
|
404 |
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umap-learn==0.5.3
|
405 |
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Unidecode @ file:///tmp/build/80754af9/unidecode_1614712377438/work
|
406 |
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urllib3 @ file:///tmp/abs_5dhwnz6atv/croots/recipe/urllib3_1659110457909/work
|
407 |
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validators==0.20.0
|
408 |
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virtualenv==20.21.0
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409 |
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visions==0.7.5
|
410 |
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w3lib @ file:///Users/ktietz/demo/mc3/conda-bld/w3lib_1629359764703/work
|
411 |
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watchdog @ file:///tmp/build/80754af9/watchdog_1638367282716/work
|
412 |
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wcwidth @ file:///Users/ktietz/demo/mc3/conda-bld/wcwidth_1629357192024/work
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413 |
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webencodings==0.5.1
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414 |
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websocket-client @ file:///tmp/build/80754af9/websocket-client_1614803975924/work
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415 |
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Werkzeug @ file:///opt/conda/conda-bld/werkzeug_1645628268370/work
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416 |
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wget==3.2
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417 |
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whatthepatch @ file:///opt/conda/conda-bld/whatthepatch_1661795988879/work
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418 |
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widgetsnbextension @ file:///tmp/build/80754af9/widgetsnbextension_1644992802045/work
|
419 |
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wrapt @ file:///tmp/abs_c335821b-6e43-4504-9816-b1a52d3d3e1eel6uae8l/croots/recipe/wrapt_1657814400492/work
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420 |
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wurlitzer @ file:///tmp/build/80754af9/wurlitzer_1638368168359/work
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421 |
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xarray @ file:///opt/conda/conda-bld/xarray_1639166117697/work
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422 |
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xlrd @ file:///tmp/build/80754af9/xlrd_1608072521494/work
|
423 |
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XlsxWriter @ file:///opt/conda/conda-bld/xlsxwriter_1649073856329/work
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424 |
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xxhash==3.2.0
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425 |
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yapf @ file:///tmp/build/80754af9/yapf_1615749224965/work
|
426 |
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yarl==1.8.2
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427 |
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ydata-profiling==4.1.2
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428 |
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yellowbrick==1.5
|
429 |
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zict==2.1.0
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430 |
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zipp @ file:///opt/conda/conda-bld/zipp_1652341764480/work
|
431 |
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zope.interface @ file:///tmp/build/80754af9/zope.interface_1625036153595/work
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