Exploratory data analysis

Related tags

Data AnalysisEDA
Overview

Exploratory data analysis

An Exploratory data analysis APP

APP

TAPIWA CHAMBOKO

portfolio linkedin github

🚀 About Me

I'm a full stack developer experienced in deploying artificial intelligence powered apps

Authors

Acknowledgements

Demo

Live demo

Click here for Live demo

Installation

Install required packages

  pip install streamlit
  pip install pycaret
  pip insatll scikit-learn==0.23.2
  pip install numpy
  pip install seaborn 
  pip install pandas
  pip install matplotlib
  pip install plotly-express
  pip install streamlit-lottie

Datasets

  • Drop your Datasets in the app to get resuilts
  • you can use he exaple data provided in the app

Code

import streamlit as st
import pandas as pd  
import plotly.express as px  
import base64  
from io import StringIO, BytesIO  
import numpy as np
import pandas as pd
from sklearn import datasets
import matplotlib.pyplot as plt
from pandas_profiling import ProfileReport
from streamlit_pandas_profiling import st_profile_report

def app():
    st.markdown('''
# **Exploratory data analysis App**
Please upload your xlsx file or click the button below to use example dataset
---
''')

# Upload CSV data
    with st.sidebar.header('Upload your XLSX data'):
        uploaded_file = st.sidebar.file_uploader("Upload your input XLSX file", type=["xlsx"])
       

    # Pandas Profiling Report
    if uploaded_file is not None:
        @st.cache
        def load_csv():
            csv = pd.read_excel(uploaded_file,engine='openpyxl')
            #csv = pd.read_csv(uploaded_file,encoding='latin1', index_col=None,usecols = "A,B,C,D,E,F,H,G,H,I,J")
            return csv
        df = load_csv()
        pr = ProfileReport(df, explorative=True)
        st.header('**Input DataFrame**')
        st.write(df)
        st.write('---')
        st.header('**Exploratory data analysis Report**')
        st_profile_report(pr)
        
    else:
        st.info('Awaiting for XLSX file to be uploaded.')
        
        if st.button('Press to use Example Dataset'):
            # Example data
            @st.cache
            def load_data():
                a = pd.DataFrame(
                    np.random.rand(100, 5),
                    columns=['a', 'b', 'c', 'd', 'e']
                )
                return a
            df = load_data()
            pr = ProfileReport(df, explorative=True)
            st.header('**Input DataFrame**')
            st.write(df)
            st.write('---')
            st.header('**Exploratory data analysis Report**')
            st_profile_report(pr)

Deployment

To deploy this project we used streamlit to create Web App

  • Run this code below
  streamlit run app.py 

Appendix

Happy Coding!!!!!!

Owner
tapiwa chamboko
tapiwa chamboko
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