CODEWITHSUNDEEP
pythonpandasdataframereshape
orthoeng2
orthoeng2

Reputation: 140

Is there an way to reshape a column to a row, but the row is make by ID column

I'm trying to reshape a dataframe. Making my column to a row, but the first column controls the rows length.

i tried pandas pivot_table to reshape the column. Example: Would like it to look.

ID  Apex   max    min    angle
1   A1     30.1  -16.9    NA
2   A1     89     NA      NA
3   B1     100   26.3    68.9

ID  Parameter   Simulated
1   Apex            A1
1   max         30.1
1   min        -16.9
2   Apex            A1
2   max         89
3   Apex            B1
3   max         100
3   min         26.3
3   angle           68.9

df1 = pd.DataFrame({'ID': [1, 1, 1, 2, 2, 3, 3, 3, 3],
               'Parameter': ['Apex', 'max', 'min', 'Apex ', 'max',               
                            'Apex', 'max', 'min', 'angle'],
                'Simulated': ['A1', 30.1, -16.9, 'A1', 89,      
                            'B1', 100, 26.3, 68.9],
                },
                 index=[0, 1, 2, 3, 4, 5, 6, 7, 8])

pd.pivot_table(df1, index = 'ID', columns ='Parameter', values = 'Simulated')

I'm getting this Error - DataError: No numeric types to aggregate

Thank you for what ever help you can give me.

Upvotes: 2

Views: 57

Answers (2)

Scott Boston
Scott Boston

Reputation: 153500

Try:

df1.pivot(index='ID', columns='Parameter', values='Simulated')

Output:

Parameter Apex angle   max   min
ID                              
1           A1   NaN  30.1 -16.9
2           A1   NaN    89   NaN
3           B1  68.9   100  26.3

pivot_table assumes your are going to aggregate values, by default it will use 'mean', since you have strings, in your data to pivot it is causing the error.

Multiple entries:

df1.groupby(['ID','Parameter']).first()['Simulated'].unstack().reset_index()

Upvotes: 2

lexual
lexual

Reputation: 48752

In [43]: df1.set_index(['ID', 'Parameter']).unstack()
Out[43]: 
          Simulated                        
Parameter      Apex Apex  angle   max   min
ID                                         
1                A1   NaN   NaN  30.1 -16.9
2               NaN    A1   NaN    89   NaN
3                B1   NaN  68.9   100  26.3

Upvotes: 1

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