How to Spread Columns in Pandas (Python)

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Published on ● Video Link: https://www.youtube.com/watch?v=YtFkSXXpMF4



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Duration: 3:14
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↓ Code Available Below! ↓

This video shows how to spread data using the pivot function in the pandas library for Python, which allows you transform data in a "long" format into data in a "wide" format. Manipulating data with gather and spread operations (also known as melt and pivot) is a common data preprocessing task.

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Code used in this Python Code Clip:

import pandas as pd

data = pd.DataFrame({"character": ["Goku","Vegeta", "Nappa","Gohan","Piccolo"],
"uniform color": ["orange", "blue", "black", "orange", "purple"],
"saiyan": [12000, 16000, 4000, 1500, 3000],
"frieza": [150000000, 3000000, 4000, 75000, 1200000],
"cell": [1000000000, 1000000000, 4000, 2000000000, 300000000],
"buu": [4000000000, 2500000000, 4000, 5000000000, 500000000]})

# Put data into a long format
data = data.melt(id_vars = ["character", "uniform color"],
value_vars = ["saiyan","frieza","cell","buu"],
var_name = "saga",
value_name = "power level")

data

# Spread a key column and its associated values with df.pivot()

data = data.pivot(index=["character", "uniform color"], # Columns that will not change
columns="saga", # Column holding new column names/categories
values="power level") # Name of value column to spread

data

# Remove the multi-index
data = data.reset_index()
data.columns.name = None

data

** Note: YouTube does not allow greater than or less than symbols in the text description, so the code above will not be exactly the same as the code shown in the video! I will use Unicode large < and > symbols in place of the standard sized ones. .


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