CODEWITHSUNDEEP
pythonpandas
armin
armin

Reputation: 651

Select empty columns and drop them in Pandas?

This may be an easy process, but has been confusing me. Let's say I have the following df:

import pandas as pd
  
# creating a DataFrame
df = pd.DataFrame({'col1' :['A', 'B', 'B', 'C'], 
                   'col2' :['B', 'A', 'B', 'H'],
                   'col3' :['', '', '', ''],
                   'val' :['','','','']})
print(df)
 col1 col2 col3 val
0    A    B         
1    B    A         
2    B    B         
3    C    H

Now I wanna identify empty columns and drop them. Here is what I am doing:

empty_cols = [col for col in df if df[col].isnull().all()]
print(empty_cols)
[]
False

which returns [] and False. Am I making a mistake somewhere here? Thanks!

Upvotes: 1

Views: 2277

Answers (3)

Vova
Vova

Reputation: 38

I guess, you need to check '' instead of isnull(), because, null is None in Python, but you have just empty stings, so they are not None.

P.S my code to detect and drop.

empty = [df[col].name for col in df if not df[col].all()]
df = df.drop(empty, axis=1)

Upvotes: 1

Oddaspa
Oddaspa

Reputation: 888

You could try this

empty = []
for col in df.columns:
  if df[col].sum() == "":
    empty.append(col)

Alternatively like this, if you want a one liner:

empty = [col for col in df if df[col].sum() == ""]

Upvotes: 2

buzios
buzios

Reputation: 41

If by "empty" you mean and string with no charatchers like '', then you can chek for that instead of null values

empty_cols = [col for col in df if df[col].str.contains('').all()]

Upvotes: 1

Related Questions