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Pandas: Add a prefix or suffix to all columns of a given DataFrame

Pandas: DataFrame Exercise-64 with Solution

Write a Pandas program to add a prefix or suffix to all columns of a given DataFrame.

Sample Solution :

Python Code :

import pandas as pd
df = pd.DataFrame({'W':[68,75,86,80,66],'X':[78,85,96,80,86], 'Y':[84,94,89,83,86],'Z':[86,97,96,72,83]});
print("Original DataFrame")
print(df)
print("\nAdd prefix:")
print(df.add_prefix("A_"))
print("\nAdd suffix:")
print(df.add_suffix("_1"))

Sample Output:

Original DataFrame
    W   X   Y   Z
0  68  78  84  86
1  75  85  94  97
2  86  96  89  96
3  80  80  83  72
4  66  86  86  83

Add prefix:
   A_W  A_X  A_Y  A_Z
0   68   78   84   86
1   75   85   94   97
2   86   96   89   96
3   80   80   83   72
4   66   86   86   83

Add suffix:
   W_1  X_1  Y_1  Z_1
0   68   78   84   86
1   75   85   94   97
2   86   96   89   96
3   80   80   83   72
4   66   86   86   83

Python-Pandas Code Editor:

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Python: Tips of the Day

Inserting if statements using conditional list comprehensions:

x = [1, 2, 3, 4, 5, 6]
result = []
for idx in range(len(x)):
    if x[idx] % 2 == 0:
        result.append(x[idx] * 2)
    else:
        result.append(x[idx])
result

Output:

[1, 4, 3, 8, 5, 12]
[(element * 2 if element % 2 == 0 else element) for element in x]

Output:

[1, 4, 3, 8, 5, 12]
[element * 2 for element in x if element % 2 == 0]

Output:

[4, 8, 12]