Pandas: SettingWithCopyWarning:

Question

I tried the following code to convert a column to "date":

df.['DATE'] =  pd.to_datetime(df['DATE'])

or

df.DATE =  pd.to_datetime(df.DATE)

but I get the following error:

/Users/xyz/anaconda3/envs/sensor/lib/python3.6/site-packages/pandas/core/indexing.py:517: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy self.obj[item] = s

I changed the code to the following:

df.loc[:,'DATE'] =  pd.to_datetime(df.loc[:,'DATE'])

but I still get the same error.

same with this

for i in df.index:
    df.loc[i,'DATE'] =  pd.to_datetime(df.loc[i,'DATE'])

`df = data.loc[data.ID == 79]` – mallet Jul 18 '17 at 15:00 — mallet, Jul 18 '17 at 15:00

score 6 · Accepted Answer · answered Jul 18 '17 at 15:01

6

You need add copy:

df = data.loc[data.ID == 79]

to:

df = data.loc[data.ID == 79].copy()

If you modify values in df later you will find that the modifications do not propagate back to the original data (data), and that Pandas does warning.

answered Jul 18 '17 at 15:01

jezrael

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how to tell if the df is a `view` or a `copy`? – mallet Jul 18 '17 at 15:05
I think you can check it by `print (df.is_copy)`. – jezrael Jul 18 '17 at 15:12

score 2 · Answer 2 · answered Jul 18 '17 at 14:58

The problem is in the code you have not shown us. Somewhere, you have done something like this:

df = other.loc[something]

That is the root cause of this error message. You need to assign using .loc or similar directly into the original DataFrame:

other.loc[something, 'DATE'] = whatever

Pandas: SettingWithCopyWarning:

2 Answers2

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