Update pages/1_Introduction to Data_Analysis.py

pages/1_Introduction to Data_Analysis.py

@@ -40,7 +40,7 @@ Examples of semi-structured data is - csv files, json files and xml files
 '''
 st.image("https://cdn-uploads.huggingface.co/production/uploads/66bde9bf3c885d04498227a0/Gz_AZKg8M7e9K96TsVenU.png")
 st.markdown(multi)
-st.header("**Steps in Data Analysis**")
+st.header("**Steps in Data Analysis**",divider="green")
 st.markdown('''Basically there are 7 steps involved to perform complete data analysis''')
 st.subheader(":blue[1.Problem Statement]")
 multi = '''Basically when the data is collected and need to perform data analysis the first step is problem statement - it is concise description for the problem needs to be solved.
@@ -53,7 +53,7 @@ Data needs to collected in differenr formats from many sources, websites etc...
 We can gather data or collect the data from previous one with the help of stake holders and domain experts.
 '''
 st.markdown(multi)
-st.subheader(":blue[3.Simple EDA(Exploratory Data Analysis)")
+st.subheader(":blue[3.Simple EDA(Exploratory Data Analysis]")
 multi = '''After collecting the data we need to check whether the collected data has any impurities or not.
 For that we need simple EDA which gives the information about collected data has any impurities or not.
 If the collected data doesn’t have any impurities then directly go for EDA phase else it goes to pre-processing phase