Exploratory Data Analysis

EDA.md

Exploratory Data Analysis

Automated python script for running preliminary exploratory data analysis on csv input.

Installation

Use the package manager pip to install cca_eda.

pip install cca_eda

Usage

import cca_eda

# returns prompt to upload csv dataset
cca_eda.choice("EDA")

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT

main.py

if choice == "EDA":
		st.subheader("Exploratory Data Analysis")

		data = st.file_uploader("Upload Dataset : ",type=["csv","txt"])
		if data is not None:
			df = pd.read_csv(data)
			st.dataframe(df.head())

            		# Show Shape
			if st.checkbox("Show Shape"):
				st.write(df.shape)


			# Show Columns
			if st.checkbox("Show Columns"):
				all_columns = df.columns = df.columns.to_list()
				st.write(all_columns)



           		 # Show Summary
			if st.checkbox("Show Summary"):
				st.write(df.describe())




            		# Show Value Counts
			if st.checkbox("Show Value Counts"):
				st.write(df.iloc[:,-1].value_counts())



			# Show Select Columns To Show
			if st.checkbox("Select Columns to Show"):
				selected_columns = st.multiselect("Select Columns ",all_columns)
				new_df = df[selected_columns]
				st.dataframe(new_df)

			# Show Percentage of Missing Values
			if st.checkbox("Show Percentage of Missing Values"):
				st.write((df.isna().mean().round(4) * 100))