How to Join Data Frames in Pandas (Python)

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This video shows how to join pandas data frames using the merge function. Joining data that resides in different tables is a common data preparation task when creating an analytical data set from multiple sources. The merge function allows you to perform inner, outer, left and right joins by changing the how argument.

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Code used in this Python Code Clip:

import pandas as pd

data1 = pd.DataFrame({"character": ["Goku","Vegeta", "Nappa","Gohan","Piccolo"],
"power level": [12000, 16000, 4000, 1500, 3000],
"uniform color": ["orange", "blue", "black", "orange", "purple"]})

data2 = pd.DataFrame({"character": ["Gohan","Goku", "Tien","Krillin","Yamcha"],
"power level": [1500, 12000, 2000, 2000, 1500],
"unif_color": ["purple", "orange", "green", "orange", "orange"]})

data1
data2

how = "outer", # join type
on="character") # key column to join on

# Join on multiple key columns
how = "outer", # join type
on = ["character", "power level"]) # join on multiple cols

# Join columns with different names

# Rename columns so that they match

# Then join the data
how = "outer",
on = ["character", "power level", "uniform color"])

* 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. .