Create app.py

app.py

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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)