Can I find alternative `.loc` alternative for replace function in pandas dataframe

Question

Previously, I'm asking How to update series based on other pandas dataframe, and there exist 3 answers, but 3 of them give caveats, usually I ignoring this, but this is for production purpose, so I'cant. Here's the answer and the caveat:

1

s = df2.set_index('Nation')['Capital City']
df1['Capital'] = df1['Country'].map(s).fillna(df1['Capital'])

caveat

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

2

df1['Capital'] = df1['Country'].replace(s)

caveat

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

3

s = df2.set_index('Nation')['Capital City']
df1['Capital'].update(df1['Country'].map(s))

caveat

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  exec(code_obj, self.user_global_ns, self.user_ns)
/home/ubuntu/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:1: 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

How to reduce the caveat

The code is working, but caveat on jupyter notebook, in my previous feature engineering deployment, usually caveat on jupyter notebook give problem on production — Nabih Bawazir, May 25 '18 at 07:18
This kind of error is very confused, because problem is one line before. Obviously if some filtering, then need `df = df1[df1['col'] == 10].copy()`. — jezrael, May 25 '18 at 07:20

score 1 · Accepted Answer · answered May 25 '18 at 07:29

Problem is obviously in one line before in filtering.

Solution is add copy like:

df1 = df[df['col'] == 10].copy()

Explanation:

If you modify values in df1 later you will find that the modifications do not propagate back to the original data (df), and that Pandas does warning.

Can I find alternative `.loc` alternative for replace function in pandas dataframe

1 Answers1