Data Transformation

For the most recent list of transformation functions offered by bamboolib, we recommend installing the latest version of bamboolib, opening it on your computer and clicking on the "Search transformation" dropdown. All available transformations are listed there.

List of Transformations - Aug 28th, 2020

  • Select or drop columns

    Select/delete one or multiple columns

  • Filter

    Select/delete rows based on a condition

  • Sort

    Sort rows beased on values in one or more columns

  • Group by and aggregate (default)

    Group rows by columns and calculate MULTIPLE aggregations (no renaming possible)

  • Group by and aggregate (with renaming)

    Group rows by columns and calculate a SINGLE aggregation that can be named

  • Join / Merge dataframes

    Add columns from another dataframe based on keys

  • Change data type

    Change the data type of a column

  • To Integer

    Convert a column to integer

  • To Unsigned Integer

    Convert a column to unsigned integer

  • To Float

    Convert a column to float

  • To String

    Convert a column to string

  • To Object

    Convert a column to dtype Object

  • To Datetime

    Convert a column to datetime

  • To Timedelta

    Convert a column to timedelta

  • To Category

    Convert a column to category

  • To Bool

    Convert a column to boolean

  • Rename columns

    Rename one or more columns

  • Replace value

    Replace cell values in one or all columns

  • Set or update values

    Replace cell values based on column condition

  • String manipulations

    Manipulate string values

  • Change datetime frequency

    EITHER expand timeseries column and fill it with values OR group by and calculate aggregations (also known as: resample or expand grid)

  • Extract datetime attributes

    Extract datetime features from a datetime column

  • Move columns / Change column order

    Move / Re-order one or multiple columns

  • Bin column

    Form discrete categories from a numeric column

  • Concatenate

    Concatenate (union / stack) multiple dataframes vertically or horizontally

  • Pivot/Spread

    Reshape the dataframe from long to wide format

  • Unpivot/Melt

    Reshape the dataframe from wide to long format

  • OneHotEncoder

    Create a column for each unique value indicating its presence or absence

  • LabelEncoder

    Turn a categoric column into numeric integer codes (factorize)

  • Drop missing values

    Remove rows with missing values (NAs) in one or more columns

  • Drop/Remove duplicates

    Remove duplicated rows in a dataframe, i.e. only keep distinct rows

  • Replace missing values

    Fill / Impute missing values (NAs) in one or more columns

  • New column formula

    Create a new column from a formula

  • Add Python Code

    Add custom Python code as a transformation

  • Explore and visualize dataframe

    Explore and visualize the current dataframe

  • Plot dataframe

    Create custom visualizations through the plot creator

  • Create pivot table

    Create a pivot table