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Pandas: Drop a list of rows from a specified DataFrame

Pandas: DataFrame Exercise-36 with Solution

Write a Pandas program to drop a list of rows from a specified DataFrame.

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
New DataFrame after removing 2nd & 4th rows:
col1 col2 col3
0 1 4 7
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(d)
print("Original DataFrame")
print(df)
print("New DataFrame after removing 2nd & 4th rows:")
df = df.drop(df.index[[2,4]])
print(df)

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
New DataFrame after removing 2nd & 4th rows:
   col1  col2  col3
0     1     4     7
1     4     5     8
3     4     7     0

Python Code Editor:


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Python: Tips of the Day

Creates a dictionary with the same keys as the provided dictionary and values generated by running the provided function for each value

Example:

def tips_map_values(obj, fn):
  ret = {}
  for key in obj.keys():
    ret[key] = fn(obj[key])
  return ret
users = {
  'Owen': { 'user': 'Owen', 'age': 29 },
  'Eddie': { 'user': 'Eddie', 'age': 15 }
}

print(tips_map_values(users, lambda u : u['age'])) # {'Owen': 29, 'Eddie': 15}

Output:

{'Owen': 29, 'Eddie': 15}