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import streamlit as st | |
import pandas as pd | |
import matplotlib.pyplot as plt | |
import seaborn as sns | |
from io import StringIO | |
def main(): | |
st.title("PPDAC Data Analysis Toolkit") | |
# Problem | |
st.header("1. Problem") | |
problem = st.text_area("Define your problem:") | |
# Plan | |
st.header("2. Plan") | |
plan = st.text_area("Describe your plan:") | |
# Data | |
st.header("3. Data") | |
uploaded_file = st.file_uploader("Choose a CSV file", type="csv") | |
if uploaded_file is not None: | |
data = pd.read_csv(uploaded_file) | |
st.write(data.head()) | |
# Analysis | |
st.header("4. Analysis") | |
# EDA | |
st.subheader("Exploratory Data Analysis") | |
# Summary statistics | |
st.write("Summary Statistics:") | |
st.write(data.describe()) | |
# Correlation heatmap | |
st.write("Correlation Heatmap:") | |
fig, ax = plt.subplots(figsize=(10, 8)) | |
sns.heatmap(data.corr(), annot=True, cmap='coolwarm', ax=ax) | |
st.pyplot(fig) | |
# Pairplot | |
st.write("Pairplot:") | |
fig = sns.pairplot(data) | |
st.pyplot(fig) | |
# Histogram | |
st.write("Histograms:") | |
for column in data.select_dtypes(include=['float64', 'int64']).columns: | |
fig, ax = plt.subplots() | |
sns.histplot(data[column], kde=True, ax=ax) | |
st.pyplot(fig) | |
# Conclusion | |
st.header("5. Conclusion") | |
conclusion = st.text_area("Write your conclusion based on the analysis:") | |
if __name__ == "__main__": | |
main() |