Pivot table in Pandas using Python
Pivot tables are a powerful tool for data analysis in pandas. Here's how you can create a pivot table in pandas using the pivot_table() function:
Load your data into a pandas DataFrame. You can use the read_csv() function to load a CSV file, or other file readers for different file formats.
import pandas as pd
data = pd.read_csv("data.csv")
Call the pivot_table() function on your DataFrame. You'll need to specify the columns to use as the row and column indices, as well as the values to aggregate. For example, let's say you have a DataFrame with columns "Product", "Region", and "Sales":
pivot_table = data.pivot_table(index='Product', columns='Region', values='Sales', aggfunc='sum')
Display the pivot table by printing the DataFrame:
print(pivot_table)
Here complete python code
import pandas as pd
data = pd.read_csv("data.csv")
pivot_table = data.pivot_table(index='Product', columns='Region', values='Sales', aggfunc='sum')
print(pivot_table)
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