Cookbook
Data wrangling
Prepare and preprocess your data. You will find here code recipes for data joining, spliting, filtering and more!
DataFrame info
Check information about DataFrame columns, non-nulls, types and memory usageDataFrame describe
Display statistical description for numeric columns in DataFrameDisplay DataFrame
Display rows from Pandas DataFrameSelect X,y
Select training attributes and target for Machine Learning model trainingSelect Columns
Select columns from dataframeFilter rows
Filter rows in Pandas DataFrame based on conditionDelete Column
Use `drop()` function from Pandas package to delete column in DataFrame. You can ...Split to train/test
Split data into train and test subsetsCheck missing values
Check and count missing values in Pandas DataFrameFill missing values
Fill missing values in Pandas DataFrameUse imputer on new data
Use previously fitted imputer on new dataCategorical to integer
Convert features with non-numeric values (categoricals) to integersUse encoder on new data
Use previously fitted categoricals encoder on new data
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