Changing value in data frame column in a loop python

Question

I am new to Python pandas library and using data frames. I am using Jupyter. I kind of lost with this syntax.

I want to loop through rows and set new value to column new_value. I thought I would do it like this, but it raises an error.

df_merged['new_value'] = 0

for i, row in df_merged.iterrows():
    df_merged['new_value'][i] = i

I also tried to do a calculation like:

 df_merged['new_value'][i] = df_merged['move_%'] * df_merged['value']

But it doesnt work.

I am getting this error:

/usr/lib/python3.4/site-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: http://pandas.pydata.org/pandas- docs/stable/indexing.html#indexing-view-versus-copy after removing the cwd from sys.path.

What I am doing wrong here?
Thanks.

Answer 1

You can use just this:

df_merged['new_value'] = df.index

You can also use apply method.

df_merged['new_value'] = df_merged.apply(lambda row : row.name, axis=1)

I am getting this error : A value is trying to be set on a copy of a slice from a DataFrame

It's not a error, it's just a warning message.

From this answer:

The SettingWithCopyWarning was created to flag potentially confusing "chained" assignments, such as the following, which don't always work as expected, particularly when the first selection returns a copy.

You can avoid this warning message using pd.DataFrame.loc method.

for i, row in df_merged.iterrows():
    df_merged.loc[i,'price_new']  = i