adding first row for each group in pandas dataframe

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These are my dataframes:

df1 = pd.DataFrame({'sym': ['msft', 'msft', 'amd', 'amd'], 'close': [102, 100, 35, 30]})

df2 = pd.DataFrame({'sym': ['msft', 'amd'], 'close': [103, 36]})

I want to combine df1 and df2 in a way that a first row is added for each group of sym in df1. This is a simplified dataframe, my original has thousand of rows.

This is my desired outcome:

 sym  close
0  msft    103
1  msft    102
2  msft    100
3   amd     36
4   amd     35
5   amd     30
pandas python
4 Answers

You can do this using pd.Categorical() which lets you set the order of a categorical column.

m=df2.append(df1,ignore_index=True)
m=m.assign(sym=pd.Categorical(m.sym,df1.sym.unique(),ordered=True)).sort_values('sym')

    sym  close
0  msft    103
2  msft    102
3  msft    100
1   amd     36
4   amd     35
5   amd     30
user_98406370

We can use pd.concat with sort_values descending:

df = pd.concat([df1, df2]).sort_values(['sym', 'close'], 
                                       ascending=False).reset_index(drop=True)

    sym  close
0  msft    103
1  msft    102
2  msft    100
3   amd     36
4   amd     35
5   amd     30

2nd example

based on anky_91's comment

df1 = pd.DataFrame({'sym': ['msft', 'msft', 'amd', 'amd','cmd'], 'close': [102, 100, 35, 30,40]})
df2 = pd.DataFrame({'sym': ['msft', 'cmd','amd'], 'close': [103, 23,36]})

    sym  close
0  msft    102
1  msft    100
2   amd     35
3   amd     30
4   cmd     40

    sym  close
0  msft    103
1   cmd     23
2   amd     36

df = pd.concat([df1, df2]).sort_values(['sym', 'close'], 
                                        ascending=False).reset_index(drop=True)

    sym  close
0  msft    103
1  msft    102
2  msft    100
3   cmd     40
4   cmd     23
5   amd     36
6   amd     35
7   amd     30
user_90812670

First concat both dataframes
Sort by both columns in descending order

df3 = pd.concat([df1,df2],sort=False)
df3.sort_values(['close', 'sym'], ascending=False,inplace=True)
user_116079860

This should work:

import pandas as pd

df1 = pd.DataFrame({'sym': ['msft', 'msft', 'amd', 'amd'], 'close': [102, 100, 35, 30]})
df2 = pd.DataFrame({'sym': ['msft', 'amd'], 'close': [103, 36]})

df3 = df1.append(df2)
df3 = df3.sort_values(['close', 'sym'], ascending=False)

Output:

    sym close
0   msft    103
0   msft    102
1   msft    100
1   amd 36
2   amd 35
3   amd 30
user_101403100
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