merge two series in a dataframe with special function for each column in python

You can use the merge function from pandas library to merge two series into a dataframe. To apply special function for each column, you can use apply method and pass the function as a parameter. Here's an example:


main.py
import pandas as pd

# create two series
s1 = pd.Series([1, 2, 3])
s2 = pd.Series([4, 5, 6])

# merge two series into a dataframe
df = pd.DataFrame({'s1': s1, 's2': s2})

# define special function for each column
def special_function_s1(x):
    return x * 2

def special_function_s2(x):
    return x ** 2

# apply special function to each column
df['s1'] = df['s1'].apply(special_function_s1)
df['s2'] = df['s2'].apply(special_function_s2)

print(df)
451 chars
22 lines

Output:


main.py
   s1  s2
0   2  16
1   4  25
2   6  36
40 chars
5 lines

In this example, we created two series s1 and s2, merged them into a dataframe df. We also defined two special functions special_function_s1 and special_function_s2 that are applied to each column of the dataframe using apply method. The result is a new dataframe with modified columns.

similar python code snippets

merge two series in a dataframe in python

iterate dataframe fast way in python

merge tables in python

append a line at the end of a dataframe in python

covnert all dataframe values from int to str in python

add a line in a dataframe in python

query data in panda dataframe in python

loop on a dataframe rows in python

initialize dataframe in python

dataframes in python

related categories