Drop all data in a pandas dataframe

Question

I would like to drop all data in a pandas dataframe, but am getting TypeError: drop() takes at least 2 arguments (3 given). I essentially want a blank dataframe with just my columns headers.

import pandas as pd

web_stats = {'Day': [1, 2, 3, 4, 2, 6],
             'Visitors': [43, 43, 34, 23, 43, 23],
             'Bounce_Rate': [3, 2, 4, 3, 5, 5]}
df = pd.DataFrame(web_stats)

df.drop(axis=0, inplace=True)
print df

I do like @ayhan's solution, but I think `df = pd.DataFrame(columns=df.columns)` would be faster and more efficient... — MaxU - stand with Ukraine, Aug 26 '16 at 20:55
Agree with @MaxU -- it's actually about 100x faster (test dataframe with 1M rows and 10 cols) — exp1orer, Aug 26 '16 at 23:18
`df.iloc[0:0]` is faster than the df construction actually. I guess you are comparing it to drop rather than iloc? — ayhan, Aug 27 '16 at 04:31
Wouldn't it be a good idea to use `gc.collect()` afterwards? — Mohd, Jul 04 '20 at 11:53

ayhan · Accepted Answer · 2017-11-05T18:41:57.993

159

You need to pass the labels to be dropped.

df.drop(df.index, inplace=True)

By default, it operates on axis=0.

You can achieve the same with

df.iloc[0:0]

which is much more efficient.

edited Nov 05 '17 at 18:41

answered Aug 26 '16 at 20:12

ayhan

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Should it not be df = df.iloc[0:0] ? – DISC-O May 28 '22 at 17:45

score 23 · Answer 2 · answered Oct 13 '17 at 18:35

23

My favorite:

df = df.iloc[0:0]

But be aware df.index.max() will be nan. To add items I use:

df.loc[0 if math.isnan(df.index.max()) else df.index.max() + 1] = data

answered Oct 13 '17 at 18:35

tomatom

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score 16 · Answer 3 · edited May 21 '20 at 19:29

16

My favorite way is:

df = df[0:0]

edited May 21 '20 at 19:29

β.εηοιτ.βε

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answered May 21 '20 at 12:41

Raul Menendez

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short and sweet, easy to remember! – wisbucky Jul 21 '21 at 19:26

score 9 · Answer 4 · answered Jun 11 '20 at 07:34

9

Overwrite the dataframe with something like that

import pandas as pd

df = pd.DataFrame(None)

or if you want to keep columns in place

df = pd.DataFrame(columns=df.columns)

answered Jun 11 '20 at 07:34

Zisis F

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score 0 · Answer 5 · answered Nov 12 '20 at 01:30

If your goal is to drop the dataframe, then you need to pass all columns. For me: the best way is to pass a list comprehension to the columns kwarg. This will then work regardless of the different columns in a df.

import pandas as pd

web_stats = {'Day': [1, 2, 3, 4, 2, 6],
             'Visitors': [43, 43, 34, 23, 43, 23],
             'Bounce_Rate': [3, 2, 4, 3, 5, 5]}
df = pd.DataFrame(web_stats)

df.drop(columns=[i for i in check_df.columns])

score -4 · Answer 6 · answered Sep 30 '20 at 08:38

-4

This code make clean dataframe:

df = pd.DataFrame({'a':[1,2], 'b':[3,4]})
#clean
df = pd.DataFrame()

answered Sep 30 '20 at 08:38

Sergey Svetloff

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OP wrote: _I essentially want a blank dataframe with just my columns headers._ – AMC Oct 03 '20 at 00:45

Drop all data in a pandas dataframe

6 Answers6

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