How To Use .applymap() In Pandas (Python)

How To Use .applymap() In Pandas (Python)

This video shows how to apply functions to all the elements in a pandas data frame using .applymap(). The .applymap() only operates on data frames and runs a function on every single record in an elementwise fashion.

This video shows how to apply functions to all the elements in a pandas data frame using .applymap(). The .applymap() only operates on data frames and runs a function on every single record in an elementwise fashion. Since data frames often contain variables of different types, .applymap() may throw an error when using functions that expect certain input types, but with homogenous data types, it provides a quick way of running functions on all values.

Code used in this Python Code Clip:

import pandas as pd

data = pd.DataFrame({"power_level": [12000, 16000, 4000, 1500, 3000, 2000, 1600, 2000], "uniform color": ["orange", "blue", "black", "orange", "purple", "green", "orange", "orange"], "species": ["saiyan","saiyan","saiyan","half saiyan", "namak","human","human","human"]}, index = ["Goku","Vegeta", "Nappa","Gohan", "Piccolo","Tien","Yamcha", "Krillin"])

data

Apply a function to ALL elements in a Data Frame

def str_len(x): return(len(str(x)))

d2 = data.applymap(str_len) d2

If all data is numeric, math operations are broadcast elementwise by default!

d2 ** 2

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