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import streamlit as st | |
import pandas as pd | |
import matplotlib.pyplot as plt | |
x = st.slider('Select a value') | |
st.write(x, 'squared is', x * x) | |
df = pd.read_csv('playing_cards/cards.csv').sort_values('class index') | |
df_test = df[df['data set']=='test'] | |
df_train = df[df['data set']=='train'] | |
df_validate = df[df['data set']=='validate'] | |
### HORIZONTAL BAR ### | |
# Get the value counts of the 'labels' column | |
value_counts = df.groupby('labels')['class index'].count().iloc[::-1] | |
fig, ax = plt.subplots(figsize=(10,10)) | |
# Create a bar chart of the value counts | |
ax = value_counts.plot.barh() | |
# Set the chart title and axis labels | |
ax.set_title('Value Counts of Labels') | |
ax.set_xlabel('Label') | |
ax.set_ylabel('Count') | |
# Show the chart | |
st.pyplot(fig) | |
### PIE CHART ### | |
# Get the value counts of the 'labels' column | |
value_counts = df.groupby('data set')['class index'].count().iloc[::-1] | |
value_counts =df['data set'].value_counts() | |
fig, ax = plt.subplots(figsize=(5,5) | |
) | |
# Create a bar chart of the value counts | |
ax = value_counts.plot.pie(autopct='%1.1f%%') | |
# Set the chart title and axis labels | |
ax.set_title('Train, Validate, Test Distribution') | |
# Show the chart | |
st.pyplot(fig) |