Inserting column with insert method of pandas dataframe generating error-CodePudding

I have below code

I am trying to insert new columns as specific positions with insert method. Below is my code,

import pandas as pd

(pd.DataFrame({'product name': ['laptop', 'printer', 'printer',], 'price': [1200, 150, 1200],  'price1': [1200, 150, 1200]})
    .insert(0, 'AAA', -1)
    .insert(1, 'BBB', -2)
)

With this I am getting below error,

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: 'NoneType' object has no attribute 'insert'
>>>

Could you please help to resolve this error.

Any pointer is highly appreciated.

CodePudding user response：

Cause of the error

DataFrame.insert is the inplace operation which modifies the original dataframe and returns None. After calling the first insert operation the return value is None hence the next insert throws an error complaining that 'NoneType' object has no attribute 'insert'.

Solution

df = pd.DataFrame({'product name': ['laptop', 'printer', 'printer',], 'price': [1200, 150, 1200],  'price1': [1200, 150, 1200]})
df.insert(0, 'AAA', -1)
df.insert(1, 'BBB', -2)

Hacky solution

df.pipe(lambda x: x.insert(0, 'AAA', -1) or x.insert(1, 'BBB', -2) or x)

CodePudding user response：

The insert method doesn't return a dataframe object. You can assign the dataframe object to a variable and apply the insert method to the variable:

df = pd.DataFrame({'product name': ['laptop', 'printer', 'printer',],
                   'price': [1200, 150, 1200],
                   'price1': [1200, 150, 1200]})
df.insert(0, 'AAA', -1)
df.insert(1, 'BBB', -2)

You can also use join to have it within the chain, but you have to know the number of rows:

pd.DataFrame({'AAA': [-1] * 3})\
    .join(pd.DataFrame({'BBB': [-2] * 3}))\
    .join(pd.DataFrame({'product name': ['laptop', 'printer', 'printer', ],
                        'price': [1200, 150, 1200],
                        'price1': [1200, 150, 1200]}))