SettingWithCopyWarning, even when using loc (?)

Question

I get SettingWithCopyWarning errors in cases where I would not expect them:

N.In <38>: # Column B does not exist yet
N.In <39>: df['B'] = df['A']/25
N.In <40>: df['B'] = df['A']/50

/Users/josh/anaconda/envs/py27/lib/python2.7/site-packages/pandas/core/indexing.py:389: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_index,col_indexer] = value instead
  self.obj[item] = s

and

N.In <41>: df.loc[:,'B'] = df['A']/50

/Users/josh/anaconda/envs/py27/lib/python2.7/site-packages/pandas/core/indexing.py:389: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_index,col_indexer] = value instead
  self.obj[item] = s

Why does it happen in case 1 and 2?

I've never understood why this needs to be so complicated and therefore created a simpler data table library, *tabel* https://github.com/BastiaanBergman/tabel. For simple use cases it's faster as well. — Bastiaan, Sep 13 '18 at 15:35

kxsong · Accepted Answer · 2015-01-22T02:58:35.413

19

In case 1, df['A'] creates a copy of df. As explained by the Pandas documentation, this can lead to unexpected results when chaining, thus a warning is raised. Case 2 looks correct, but false positives are possible:

Warning: The chained assignment warnings / exceptions are aiming to inform the user of a possibly invalid assignment. There may be false positives; situations where a chained assignment is inadvertantly reported.

To turn off SettingWithCopyWarning for a single dataframe, use

df.is_copy = False

To turn off chained assignment warnings altogether, use

options.mode.chained_assignment = None

edited Jan 22 '15 at 02:58

answered Jan 22 '15 at 02:52

kxsong

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Use the following like to disable the warning: `pd.set_option('chained_assignment',None)` – Melroy van den Berg Jan 20 '17 at 12:28

score 7 · Answer 2 · answered Jun 02 '16 at 16:44

7

Another solution that should suppress the warning:

df = df.copy()
df['B'] = df['A']/25
df['B'] = df['A']/50

answered Jun 02 '16 at 16:44

Charlie Haley

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3

This does indeed work. Not fully understand if this is now faster or more memory consuming. I don't know the impact of the copy() command. Since in fact the copy is reassign again to df.. It looks like nothing is changed at the end. – Melroy van den Berg Jan 20 '17 at 12:24

SettingWithCopyWarning, even when using loc (?)

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