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Runtime error
Runtime error
some more changes, ready to run
Browse files- app.py +22 -15
- data/topic_synonyms.txt +0 -43
- data/topic_synonyms_copy.txt +347 -0
app.py
CHANGED
@@ -1,19 +1,20 @@
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import numpy as np
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from matplotlib import pyplot as plt, use as plt_use
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from textclassifier import TextClassifier as tc
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import pandas as pd
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import regex as re
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from
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import
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plt_use('Agg')
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# from functions import functions as f
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# import time
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SELECTED_COLUMN_DICT = {
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-
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'sentiment': ['tweet', 'sentiment'],
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'merged_target': ['tweet', 'target', 'synonym_target', 'cos_sim_target', 'merged_target']
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}
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@@ -28,16 +29,16 @@ CHOICE_LIST = ['Topic', 'Sentiment', 'Target']
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# PLOT_CHOICES_DICT = {'Topic': 'sub_topic', 'Sentiment': 'sentiment', 'Target': 'target'} I just changed its pavue
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# to merged target and merged topic
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PLOT_CHOICES_DICT = {'Topic':
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PLOT_CHOICES_REVERSE_DICT = {
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# PLOT_CHOICES_REVERSE_DICT= {'sub_topic':'Topic', 'sentiment':'Sentiment' , 'target':'Target'}
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UserNameDict = dict(zip(['Jimmie Åkesson', 'Ebba Busch', 'Annie Lööf', 'Johan Pehrson', 'Per Bolund',
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'Märta Stenevi', 'Magdalena Andersson', 'Nooshi Dadgostar'], USER_LIST))
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Columns = ['username', 'nlikes', 'nreplies', 'nretweets', 'main_topic', 'sub_topic', 'sentiment', 'target', 'tweet',
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'date', 'urls', 'id', 'class_tuple', 'user_id']
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NUM_TWEETS = 1000
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LIMIT = 0.
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def show_all_stats(see_full_stats):
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@@ -79,6 +80,7 @@ def main(from_date,
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):
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save_file_bool = s1, s2, s3, s4, s5, s6, s7, s8
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# Describe what save_file_bool is for: if you want to save the dataframe to a file, this is the boolean for that
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def add_pie_chart(df, leaders, plot_choices):
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@@ -122,7 +124,6 @@ def main(from_date,
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all_targets = ['v', 'mp', 's', 'c', 'l', 'kd', 'm', 'sd', 'Red-Greens', 'The opposition']
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db_new = db.loc[db["merged_target"] != "other"] # dataframe with other category removed
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percent_target = (len(db_new) / len(db)) * 100
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targets = db_new["merged_target"].value_counts().keys().to_list()
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positive = [0] * len(all_targets)
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negative = [0] * len(all_targets)
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neutral = [0] * len(all_targets)
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@@ -181,9 +182,15 @@ def main(from_date,
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dataframe = pd.read_csv("{}/data/twitterdata.csv".format(tc.ROOT_PATH))
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# choose subset between from_date and to_date and username is in usr_name_choices
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df = dataframe.loc[(dataframe['date'] >= from_date) & (dataframe['date'] <= to_date) & \
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# Sort df by date
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df.sort_values(by=['date'], inplace=True)
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if save_selected:
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user_list = match_name_lower_case(usr_name_choices)
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df_l = []
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@@ -393,8 +400,8 @@ if __name__ == "__main__":
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with gr.Row():
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with gr.Column():
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with gr.Row():
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date1 = gr.Textbox(label="from_date", value='2022-
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date2 = gr.Textbox(label="to_date", value='2022-05-
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leaders = gr.Checkboxgroup(choices=USER_NAMES,
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label="")
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plot_choices = gr.CheckboxGroup(choices=CHOICE_LIST, label='Choose what to show')
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import glob
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from pathlib import Path
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import numpy as np
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import pandas as pd
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import regex as re
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from matplotlib import pyplot as plt, use as plt_use
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from textclassifier import TextClassifier as tc
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plt_use('Agg')
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# from functions import functions as f
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# import time
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TOPIC = "merged_topic"
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SELECTED_COLUMN_DICT = {
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TOPIC: ['tweet', 'main_topic', 'sub_topic', 'synonym_topic', 'cos_sim_topic', 'merged_topic'],
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'sentiment': ['tweet', 'sentiment'],
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'merged_target': ['tweet', 'target', 'synonym_target', 'cos_sim_target', 'merged_target']
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}
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# PLOT_CHOICES_DICT = {'Topic': 'sub_topic', 'Sentiment': 'sentiment', 'Target': 'target'} I just changed its pavue
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# to merged target and merged topic
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PLOT_CHOICES_DICT = {'Topic': TOPIC, 'Sentiment': 'sentiment', 'Target': 'merged_target'}
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PLOT_CHOICES_REVERSE_DICT = {TOPIC: 'Topic', 'sentiment': 'Sentiment', 'merged_target': 'Target'}
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# PLOT_CHOICES_REVERSE_DICT= {'sub_topic':'Topic', 'sentiment':'Sentiment' , 'target':'Target'}
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UserNameDict = dict(zip(['Jimmie Åkesson', 'Ebba Busch', 'Annie Lööf', 'Johan Pehrson', 'Per Bolund',
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'Märta Stenevi', 'Magdalena Andersson', 'Nooshi Dadgostar'], USER_LIST))
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Columns = ['username', 'nlikes', 'nreplies', 'nretweets', 'main_topic', 'sub_topic', 'sentiment', 'target', 'tweet',
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'date', 'urls', 'id', 'class_tuple', 'user_id']
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# NUM_TWEETS = 1000
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LIMIT = 0.04
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def show_all_stats(see_full_stats):
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):
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save_file_bool = s1, s2, s3, s4, s5, s6, s7, s8
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+
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# Describe what save_file_bool is for: if you want to save the dataframe to a file, this is the boolean for that
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def add_pie_chart(df, leaders, plot_choices):
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all_targets = ['v', 'mp', 's', 'c', 'l', 'kd', 'm', 'sd', 'Red-Greens', 'The opposition']
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db_new = db.loc[db["merged_target"] != "other"] # dataframe with other category removed
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percent_target = (len(db_new) / len(db)) * 100
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positive = [0] * len(all_targets)
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negative = [0] * len(all_targets)
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neutral = [0] * len(all_targets)
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dataframe = pd.read_csv("{}/data/twitterdata.csv".format(tc.ROOT_PATH))
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# choose subset between from_date and to_date and username is in usr_name_choices
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df = dataframe.loc[(dataframe['date'] >= from_date) & (dataframe['date'] <= to_date) & \
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(dataframe['username'].isin(match_name_lower_case(usr_name_choices)))].copy()
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# Sort df by date
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df.sort_values(by=['date'], inplace=True)
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# Remove entries from df where 'tweet' starts with '@'
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df = df[df['tweet'].str.startswith('@') == False]
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# change 'merged_topic' to 'Other' if it is 'ERROR_9000' or 'ERROR_496'
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df['merged_topic'] = df['merged_topic'].apply(lambda x: "other" if x == "ERROR_9000" or x == "ERROR_496" else x)
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# change 'merged_topic' to 'Government' if it is 's'
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df['merged_topic'] = df['merged_topic'].apply(lambda x: "The Government" if x == "s" else x)
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if save_selected:
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user_list = match_name_lower_case(usr_name_choices)
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df_l = []
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with gr.Row():
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with gr.Column():
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with gr.Row():
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date1 = gr.Textbox(label="from_date", value='2022-01-01')
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date2 = gr.Textbox(label="to_date", value='2022-05-31')
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leaders = gr.Checkboxgroup(choices=USER_NAMES,
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label="")
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plot_choices = gr.CheckboxGroup(choices=CHOICE_LIST, label='Choose what to show')
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data/topic_synonyms.txt
CHANGED
@@ -297,49 +297,6 @@ Valet 2022
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Almedalen
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Järvaveckan
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Partiledardebatt####
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v
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Nooshi Dadgostar
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Jonas Sjöstedt
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rooftop cats play physics with cardboard fire####
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mp
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Per Bolund
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Märta Stenevi
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ice piano flies with pencil as direction####
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s
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Magdalena Andersson
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Stefan Löfven
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Morgan Johansson
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Mikael Damberg
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Peter Hultqvist
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Khashayar Farmanbar
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Anders Ygeman
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Annika Strandhäll
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Lena Hallengren
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Ardalan Shekarabi
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Ann Linde
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The government
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the swedish government
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Regeringen
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Statsministern
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Prime minister
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lamp of fire walks bird gladly tomorrow####
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c
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Annie Lööf
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differential donuts program sunny waters####
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l
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Johan Pehrson
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Nyamko Sabuni
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Jan Björklund
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red weather jokes with music and the mathematician####
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kd
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Ebba Busch
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cauchy-riemann met sunglasses after rolling yellow####
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m
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Ulf Kristersson
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parrot computer is swimming as screen time####
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sd
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Jimmie Åkesson
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keyboard can hire the yellow elephant in cosmos####
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ERROR_9000
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sweden####
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ERROR_496
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Almedalen
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Järvaveckan
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Partiledardebatt####
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ERROR_9000
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sweden####
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ERROR_496
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data/topic_synonyms_copy.txt
ADDED
@@ -0,0 +1,347 @@
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1 |
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Act of Crime
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2 |
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Gang violence
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3 |
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Robbing
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4 |
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Riots
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Murder
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6 |
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Misshandel
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7 |
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Assault
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Drug trafficking####
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9 |
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Central government administration
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development of services and efficiency
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regional coordination in the counties
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the responsibility of the state as an employer
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maintenance of state properties
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administration of state properties####
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15 |
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Children’s rights
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child protection
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interests of children
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18 |
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Care of Young Persons Act
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19 |
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Lagen om vård av unga
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20 |
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LVU####
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21 |
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Civil society and sport
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22 |
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non-profit organisations
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football
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24 |
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soccer
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25 |
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hockey
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tennis
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skiing
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registered faith communities####
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29 |
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Combating terrorism
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30 |
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money laundering
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31 |
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Counterterrorism
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Isis
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33 |
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Bombs
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mass shootings####
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35 |
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Consumer affairs
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36 |
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Consumers right####
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37 |
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Culture
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38 |
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Dance
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39 |
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Music
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40 |
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Art
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41 |
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Jul
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42 |
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Midsummer
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43 |
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Carnival
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44 |
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Food
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45 |
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Celebration
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46 |
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Tradition
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47 |
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Påsk
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48 |
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Easter
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Halloween
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50 |
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Valborg
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51 |
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Festivity
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52 |
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Christmas
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53 |
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New years eve####
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54 |
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Defense and military
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55 |
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Försvarsmakten
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56 |
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Lumpen
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57 |
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Värnplikt
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58 |
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Artillery
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59 |
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Airstrike
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Offensive front
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61 |
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Coast Guard
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62 |
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Ground Troops
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63 |
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Drone strike
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64 |
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Security Service
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65 |
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Navy
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66 |
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Säpo####
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67 |
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Democracy and human rights
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68 |
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Freedom of speech
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69 |
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Freedom of press
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70 |
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Humanity
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71 |
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Abortion
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72 |
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Mänskliga rättigheter####
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73 |
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Regulation of media and electronics and communication
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74 |
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Digital policy
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75 |
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Digitalisation
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76 |
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Digital infrastructure
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77 |
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Network and information security
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78 |
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Broadband access
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79 |
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Electronic identification
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80 |
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Technology####
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81 |
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Economic policy
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82 |
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Inflation
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83 |
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Fuel cost
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84 |
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Cost of living
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85 |
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Budget
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86 |
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Rate of interest
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87 |
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Ränta
|
88 |
+
Debt
|
89 |
+
Skuld
|
90 |
+
Income
|
91 |
+
Expenditures
|
92 |
+
Taxes and tariffs
|
93 |
+
carbon tax
|
94 |
+
VAT and excise duties
|
95 |
+
Distribution of wealth
|
96 |
+
Tax control
|
97 |
+
Audit####
|
98 |
+
Education and research
|
99 |
+
University
|
100 |
+
Utbildning
|
101 |
+
Skola
|
102 |
+
School
|
103 |
+
Dagis
|
104 |
+
Förskola
|
105 |
+
Lågstadiet
|
106 |
+
Mellanstadiet
|
107 |
+
Högstadiet
|
108 |
+
Undervisning
|
109 |
+
Högskola
|
110 |
+
CSN
|
111 |
+
Centrala Studienämnden
|
112 |
+
Doktoranden####
|
113 |
+
Emergency preparedness
|
114 |
+
Wildfire
|
115 |
+
Crises
|
116 |
+
Naturkatastrofer
|
117 |
+
Underground shelters####
|
118 |
+
Energy
|
119 |
+
Nuclear Power
|
120 |
+
Solar
|
121 |
+
Wind
|
122 |
+
Hydropower
|
123 |
+
Turbine
|
124 |
+
Kraftvärme
|
125 |
+
Kärnkraft
|
126 |
+
Solkraft
|
127 |
+
Vindkraft
|
128 |
+
Vattenkraft
|
129 |
+
Electricity production
|
130 |
+
Energy production
|
131 |
+
Thermal Power####
|
132 |
+
Enterprise and industry####
|
133 |
+
Environment and climate
|
134 |
+
Climate change
|
135 |
+
Global warming
|
136 |
+
Emission
|
137 |
+
Hazardous toxins
|
138 |
+
Animals and nature
|
139 |
+
Sustainability
|
140 |
+
Waste
|
141 |
+
Paris agreement
|
142 |
+
Extreme weather
|
143 |
+
Heatwaves
|
144 |
+
Droughts
|
145 |
+
Natural disaster
|
146 |
+
Pollution####
|
147 |
+
Family law
|
148 |
+
Gode man
|
149 |
+
Inheritance####
|
150 |
+
Foreign policy
|
151 |
+
eu
|
152 |
+
European Union
|
153 |
+
Nato
|
154 |
+
Un
|
155 |
+
United Nations
|
156 |
+
foreign affairs####
|
157 |
+
Gambling policy####
|
158 |
+
Gender equality
|
159 |
+
women's rights
|
160 |
+
Equal pay
|
161 |
+
Equal salaries
|
162 |
+
Equal opportunities####
|
163 |
+
Housing and community planning
|
164 |
+
Property information
|
165 |
+
Housing Market
|
166 |
+
Community planning####
|
167 |
+
Innovation
|
168 |
+
improved solutions####
|
169 |
+
Integration
|
170 |
+
Anti-segregation policy
|
171 |
+
Nyanländas etablering
|
172 |
+
Utanförskapsområde
|
173 |
+
Introduction of new arrivals
|
174 |
+
SFI####
|
175 |
+
International development cooperation
|
176 |
+
Improvement of life of poor people####
|
177 |
+
International law####
|
178 |
+
Judicial system
|
179 |
+
legal security
|
180 |
+
Court
|
181 |
+
Law and legal security
|
182 |
+
Prosecutor
|
183 |
+
Judge
|
184 |
+
Correctional treatment
|
185 |
+
Custody
|
186 |
+
Prison
|
187 |
+
Police
|
188 |
+
Enforcing sentences
|
189 |
+
punishment####
|
190 |
+
Labour
|
191 |
+
Work environment
|
192 |
+
Conditions in working life
|
193 |
+
Fair working conditions
|
194 |
+
Mediation in labour disputes
|
195 |
+
working environment
|
196 |
+
Labour market
|
197 |
+
Matching of jobseekers and vacancies
|
198 |
+
Unemployment
|
199 |
+
Arbetsförmedlingen####
|
200 |
+
LGBTQ
|
201 |
+
non-binary####
|
202 |
+
Media
|
203 |
+
SVT
|
204 |
+
TV5
|
205 |
+
TV4
|
206 |
+
Sveriges radio
|
207 |
+
Television
|
208 |
+
The daily press
|
209 |
+
Film
|
210 |
+
Twitter
|
211 |
+
Facebook
|
212 |
+
Instagram####
|
213 |
+
Migration and asylum
|
214 |
+
Refugee
|
215 |
+
Citizenship
|
216 |
+
Immigrants
|
217 |
+
Residence permit####
|
218 |
+
Municipalities and regions
|
219 |
+
County councils
|
220 |
+
County administrative boards
|
221 |
+
Municipal council
|
222 |
+
local government
|
223 |
+
Municipal matters####
|
224 |
+
Public health and medical care
|
225 |
+
Hospitals
|
226 |
+
Treatment
|
227 |
+
Alcohol and Tobacco consumption
|
228 |
+
Mortality
|
229 |
+
Diseases
|
230 |
+
Pandemic
|
231 |
+
Covid-19
|
232 |
+
Vaccines####
|
233 |
+
Public procurement
|
234 |
+
Offentlig upphandling####
|
235 |
+
Racial discrimination
|
236 |
+
Racist
|
237 |
+
Nazi
|
238 |
+
Fascist
|
239 |
+
Hatred against ethnic groups
|
240 |
+
Xenophobia
|
241 |
+
Anti-Semitism
|
242 |
+
Brunskjorta####
|
243 |
+
Regional development####
|
244 |
+
Rural affairs
|
245 |
+
Livestock
|
246 |
+
Fisheries
|
247 |
+
Hunting and game management
|
248 |
+
Agriculture
|
249 |
+
Forestry
|
250 |
+
Food access and security####
|
251 |
+
Social insurance
|
252 |
+
Financial security
|
253 |
+
Sickness insurance
|
254 |
+
Pensions
|
255 |
+
Parental insurance
|
256 |
+
Benefits for parents####
|
257 |
+
Social services including care for older people
|
258 |
+
Individual care
|
259 |
+
Family care
|
260 |
+
Support for people with disabilities
|
261 |
+
Elderly care####
|
262 |
+
The Constitution and personal privacy
|
263 |
+
Instrument of Government
|
264 |
+
Act of Succession
|
265 |
+
Freedom of the Press Act
|
266 |
+
Freedom of Expression
|
267 |
+
Official documents
|
268 |
+
Personal privacy of individuals####
|
269 |
+
Transport and infrastructure
|
270 |
+
transport services
|
271 |
+
Railways
|
272 |
+
Roads
|
273 |
+
shipping and aviation
|
274 |
+
transport and infrastructure research
|
275 |
+
Vehicle
|
276 |
+
Car
|
277 |
+
Trains
|
278 |
+
Airport
|
279 |
+
Transit
|
280 |
+
Highways
|
281 |
+
Aviation
|
282 |
+
Maritime
|
283 |
+
Tunnels
|
284 |
+
Water management
|
285 |
+
Bridges
|
286 |
+
Urban planning
|
287 |
+
Coastal engineering
|
288 |
+
Road safety####
|
289 |
+
Youth policy
|
290 |
+
Young people conditions
|
291 |
+
Young people
|
292 |
+
Youth issues
|
293 |
+
Opportunities for young people####
|
294 |
+
Election
|
295 |
+
Val
|
296 |
+
Valet 2022
|
297 |
+
Almedalen
|
298 |
+
Järvaveckan
|
299 |
+
Partiledardebatt####
|
300 |
+
v
|
301 |
+
Nooshi Dadgostar
|
302 |
+
Jonas Sjöstedt
|
303 |
+
rooftop cats play physics with cardboard fire####
|
304 |
+
mp
|
305 |
+
Per Bolund
|
306 |
+
Märta Stenevi
|
307 |
+
ice piano flies with pencil as direction####
|
308 |
+
s
|
309 |
+
Magdalena Andersson
|
310 |
+
Stefan Löfven
|
311 |
+
Morgan Johansson
|
312 |
+
Mikael Damberg
|
313 |
+
Peter Hultqvist
|
314 |
+
Khashayar Farmanbar
|
315 |
+
Anders Ygeman
|
316 |
+
Annika Strandhäll
|
317 |
+
Lena Hallengren
|
318 |
+
Ardalan Shekarabi
|
319 |
+
Ann Linde
|
320 |
+
The government
|
321 |
+
the swedish government
|
322 |
+
Regeringen
|
323 |
+
Statsministern
|
324 |
+
Prime minister
|
325 |
+
lamp of fire walks bird gladly tomorrow####
|
326 |
+
c
|
327 |
+
Annie Lööf
|
328 |
+
differential donuts program sunny waters####
|
329 |
+
l
|
330 |
+
Johan Pehrson
|
331 |
+
Nyamko Sabuni
|
332 |
+
Jan Björklund
|
333 |
+
red weather jokes with music and the mathematician####
|
334 |
+
kd
|
335 |
+
Ebba Busch
|
336 |
+
cauchy-riemann met sunglasses after rolling yellow####
|
337 |
+
m
|
338 |
+
Ulf Kristersson
|
339 |
+
parrot computer is swimming as screen time####
|
340 |
+
sd
|
341 |
+
Jimmie Åkesson
|
342 |
+
keyboard can hire the yellow elephant in cosmos####
|
343 |
+
ERROR_9000
|
344 |
+
sweden####
|
345 |
+
ERROR_496
|
346 |
+
n/a
|
347 |
+
none####
|