Populate 1 dataframe based on values in another

Question

I am trying to append values into a new pandas dataframe (df_t2) by looping over df. Assign does not seem to work. Is there any other way to achieve this?

values = {'No': ['123','456'],
        'data1': [22000,25000]}

df = pd.DataFrame(values, columns = ['No', 'data1'])

Code to loop over dataframe (df) and copy it to df_t2:

for index, row in df.iterrows():
   df_t2["No"] = row['No']
   df_t2[str(row['point1']) = row['data1']

You should add a minimum working example including code to generate your dataframes and code showing your desired output. — DocBuckets, Nov 23 '20 at 22:57
You should have a clear example of what the output should be, it is very hard to understand what are you trying to do. - 'point1' does not even exist, check if your example code even run.. — Oren, Nov 23 '20 at 23:23

Oren · Answer 1 · 2020-11-23T23:32:11.700

0

Try reading here: https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html

import pandas as pd
values = {'No1': ['123','4562'], 'data1': [22000,21000] }

df_1 = pd.DataFrame(values , columns = ['No1', 'data1'])

values = {'No2': ['1231','456'], 'data2': [24000,25000] }
df_2 = pd.DataFrame(values , columns = ['No2', 'data2'])

all_values = np.concatenate([df_1.values,df_2.values])
new_df_2 = pd.DataFrame(all_values, columns = df_2.columns)

edited Nov 23 '20 at 23:32

answered Nov 23 '20 at 23:19

Oren

4,711
4
37
63

Its not a direct copy, column names are different in both – user3447653 Nov 23 '20 at 23:21
Mayeb this? @user3447653 – Oren Nov 23 '20 at 23:32

Populate 1 dataframe based on values in another

1 Answers1