In python pandas 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

Purpose

Prevent the following warnings from appearing! (The code that gives this warning is shown below)

aa.py:5: 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 the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  d['col3']= d['col2'] * 3
   col1  col2  col3
0     1     2     6
2     1     2     6

For the time being, take a look at the written link

http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy

dfmi.loc[:,('one','second')] = value
# becomes
dfmi.loc.__setitem__((slice(None), ('one', 'second')), value)

It is written.

Code in question

aa.py

import pandas as pd

data = pd.DataFrame([[1,2],[2,3],[1,2],[2,3]], columns=['col1','col2'])
d = data[data['col1'] == 1]
d['col3']= d['col2'] * 3
print(d)

If you do this, you will get the above Warning.

The problem lies in the following line.

d = data[data['col1'] == 1]

If this is d = data, the above Warning is not available.

Cause & Solution 1

Since data has values other than col1 == 1, if you try to add a new Column to the DF that has been cut out by col1 == 1, it will be strange, so make it a copy and only col1 == 1 in advance Just make a DF.

Revised

d = data[data['aa'] == 2].copy()

Cause & Solution 2

As supported in the link above, use .loc and update only the corresponding part.

Revised

#Put Value (right side) in col3 (new Column) although col1 meets the condition of 1.
data.loc[data['col1'] == 1, 'col3'] = data['col2'] * 3
#Extract only the part where col1 is 1 from data
d = data[data['col1'] == 1]
print('data:\n %s' % data)
print('d:\n%s' % d)

result

data:
    col1  col2  col3
0     1     2     6
1     2     3   NaN
2     1     2     6
3     2     3   NaN
d:
   col1  col2  col3
0     1     2     6
2     1     2     6