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Pandas: Create a new DataFrame based on existing Series and override the existing columns names

Pandas Joining and merging DataFrame: Exercise-11 with Solution

Write a Pandas program to create a new DataFrame based on existing series, using specified argument and override the existing columns names.

Sample Solution:

Python Code :

import pandas as pd
s1 = pd.Series([0, 1, 2, 3], name='col1')
s2 = pd.Series([0, 1, 2, 3])
s3 = pd.Series([0, 1, 4, 5], name='col3')
df = pd.concat([s1, s2, s3], axis=1, keys=['column1', 'column2', 'column3'])
print(df)

Sample Output:

    column1  column2  column3
0        0        0        0
1        1        1        1
2        2        2        4
3        3        3        5          

Python Code Editor:


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Python: Tips of the Day

How to sort a Python dict by value

Example:

x1 = {'a': 5, 'b': 7, 'c': 9, 'd': 1}

sorted(x1.items(), key=lambda x: x[1])
[('d', 1), ('c', 9), ('b', 7), ('a', 5)]

# Or:

import operator
print(sorted(x1.items(), key=operator.itemgetter(1)))

Output:

[('d', 1), ('a', 5), ('b', 7), ('c', 9)]