SurajDataScientist/Exploratory_Data_Analysis_using_python_Libraries

1import streamlit as st2 3st.title("Exploratory Data Analysis")4 5st.write("As we have discussed earlier what is data analysis, let us look into detail what exactly is Exploratory Data Analysis - its types, lifecycle etc.. ")6 7 8st.header("Types of Data Analysis")9st.markdown("""101. Descriptive Data Analysis - what has happened112. Diagnostic Data Analysis - why all that happened12- Here the above 2 steps tells us about the past data why and how it happened.13- The below 2 steps pedicts the future based on past and recommends the future course of action.143. Predictive Data Analysis - what is going to happen using ML & DL154. Prescriptive Data Analysis - What decision should be taken based on the analysis16""")17st.image("https://hike2.com/wp-content/uploads/2023/02/4-Main-Areas-of-Data-Analytics-1536x768.jpg", width = 400)18 19st.header("Life Cycle of Data Analysis")20 21st.markdown("""221. Problem Statement - What is the purpose of Analysis232. Data Collection - Collection data by web,API,webscraping, manually or it is given by client243. Simple EDA - To undersatnd overview of data254. Pre-processing - Cleaning or converting raw data to pre-processed data. 265. Exploratory Data Analysis(EDA) - Detailed in-depth analysis using tools like numpy,panda etc..276. Dashboard / Visualization - Visualizing the analyzed data for better and easy understanding using seaborn, matplotlib etc..28 29""")30st.image("https://cdn.prod.website-files.com/6064b31ff49a2d31e0493af1/6683f897b1383d93497fbd5d_AD_4nXf2TNVVB852LMVmziIFuWAcZKErCKiNDZQcDEawDxod5eBFs9zENxqD4E6VKcK6jHFRs5WhlredNgeze6WVyPv-fXjrWijc5Pk3tj6EK3nw4vsi-T7zYnb0tSzAJPBpF6q4jfMEz8IZ-gIl7d5y1nFYeMdA.png", width = 400)31 32 33num = st.number_input("Enter number 0 for home page and 2 for numpy", min_value = 0, max_value = 2, step = 1, format = "%d")34if st.button("Go"):35    if num == 0:36        st.switch_page("home.py")37    elif num == 2:38        st.switch_page("pages/numpy.py")39