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Pandas DataFrame: Select rows from a given DataFrame based on values in some columns

Pandas: DataFrame Exercise-24 with Solution

Write a Pandas program to select rows from a given DataFrame based on values in some columns.

Sample data:
Original DataFrame
col1 col2 col3
0 1 4 7
1 4 5 8
2 3 6 9
3 4 7 0
4 5 8 1
Rows for colum1 value == 4
col1 col2 col3
1 4 5 8
3 4 7 0

Sample Solution :

Python Code :

import pandas as pd
import numpy as np
d = {'col1': [1, 4, 3, 4, 5], 'col2': [4, 5, 6, 7, 8], 'col3': [7, 8, 9, 0, 1]}
df = pd.DataFrame(data=d)
print("Original DataFrame")
print(df)
print('Rows for colum1 value == 4')
print(df.loc[df['col1'] == 4])

Sample Output:

      Original DataFrame
   col1  col2  col3
0     1     4     7
1     4     5     8
2     3     6     9
3     4     7     0
4     5     8     1
Rows for colum1 value == 4
   col1  col2  col3
1     4     5     8
3     4     7     0            

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]