Pivot rows to columns

​​
​

Template request | Bug report​
Tags: #pandas #pivot #snippet #operations #utils #data
Author: Ismail Chihab​
Description: This notebook demonstrates how to use the Pandas library to transform data by pivoting rows into columns.
Input
Import library
import pandas as pd
Setup Data
data = {
    "LABEL": [
        "Sales",
        "Sales",
        "Sales",
        "Gross Profit",
        "Gross Profit",
        "Gross Profit",
        "EBIT",
        "EBIT",
        "EBIT",
    ],
    "DATE": ["Jan", "Feb", "Mar", "Jan", "Feb", "Mar", "Jan", "Feb", "Mar"],
    "VALUE": [0, 2, 3, 4, 5, 6, 7, 8, 9],
}
df = pd.DataFrame(data)
df
Setup Variables
# Name of the column you want to pivot
col_pivot = "DATE"
​
# Name of the column containing the values
col_value = "VALUE"
​
# List of columns not be pivot
cols_index = ["LABEL"]
Model:
def pivot_data(df_init, col_pivot, col_value, cols_index):
    # Drop duplicates
    df = df_init.copy()
    df = df.drop_duplicates()
    columns = df[col_pivot].unique().tolist()
​
    # Pivot
    df = pd.pivot(df, index=cols_index, values=col_value, columns=col_pivot)
    for col in cols_index:
        df.loc[:, col] = df.index.get_level_values(0)
    df = df.reset_index(drop=True)
    df = df.reindex(columns=cols_index + columns)
    return df
Output
Display result
table = pivot_data(df, col_pivot, col_value, cols_index)
table

Keep Columns

Pandasql

Last modified 1mo ago