Reshaping using pivot method

Rimodellare i dati con pandas

Maria Eugenia Inzaugarat

Data Scientist

From long to wide

Demonstrate relationship between two columns
Time series operations with the variables
Operation that requires columns to be the unique variable

¹ https://pandas.pydata.org/docs/user_guide/reshaping.html

From long to wide

DataFrame with a long format

Pivot method

Arrow pointing from a long to a wide format

the pandas pivot method call

Pivot method

Arrow pointing from a long to a wide format

The pivot call with arguments

Pivot method

Long and wide DataFrames with column and index highlighted

Highlighted index argument with column name

Pivot method

Long and wide DataFrames with column and column names highlighted

Highlighted columns argument with column name

Pivot method

Long and wide DataFrames with column and values highlighted

Highlighted values argument with column name

Pivot method

A NaN cell value highlighted

Highlighted arguments with column names

Pivoting a dataset

fifa = pd.read_csv('fifa_players.csv')
fifa.head()

                 name    variable  metric_system  imperial_system
0   Cristiano Ronaldo      weight             83           183.00
1            J. Oblak      weight             87           191.00
2   Cristiano Ronaldo      height            187             6.13
3     J. Oblak             height            188             6.16

Pivoting a dataset

fifa.pivot(index='name'                                            )

Pivoting a dataset

fifa.pivot(index='name', columns='variable'                        )

Pivoting a dataset

fifa.pivot(index='name', columns='variable', values='metric_system')

         variable  height   weight
             name        
Cristiano Ronaldo     187       83
         J. Oblak     188       87

Pivoting multiple columns

fifa.pivot(index='name', columns='variable', values=['metric_system', 'imperial_system'])

                     metric_system     imperial_system       
         variable   height  weight     height   weight
             name                                                         
Cristiano Ronaldo      187      83       6.13    183.0
         J. Oblak      188      87       6.16    191.0

Pivoting multiple columns

Arrow pointing from a long to a wide format with hierarchical column index

Highlighted index and columns argument with column names

Pivoting multiple columns

fifa.pivot(index="name", columns="variable")

                     metric_system     imperial_system       
         variable   height  weight     height   weight
             name                                                         
Cristiano Ronaldo      187      83       6.13    183.0
         J. Oblak      188      87       6.16    191.0

Duplicate entries error

another_fifa.head()

                 name    variable  metric_system  imperial_system
0   Cristiano Ronaldo      weight             83           183.00
1            J. Oblak      weight             87           191.00
2   Cristiano Ronaldo      height            187             6.13
3            J. Oblak      height            188             6.16
4   Cristiano Ronaldo      height            187             6.14

Duplicate entries error

another_fifa.head()

                 name    variable  metric_system  imperial_system
0   Cristiano Ronaldo      weight             83           183.00
1            J. Oblak      weight             87           191.00
  2   Cristiano Ronaldo      height            187             6.13 <--
3            J. Oblak      height            188             6.16
  4   Cristiano Ronaldo      height            187             6.14 <--

Duplicate entries error

another_fifa.pivot(index="name", columns="variable")

ValueError: Index contains duplicate entries, cannot reshape

another_fifa = another_fifa.drop(4, axis=0)
another_fifa.pivot(index="name", columns="variable")

                     metric_system     imperial_system       
         variable   height  weight     height   weight
             name                                                         
Cristiano Ronaldo      187      83       6.13    183.0
         J. Oblak      188      87       6.16    191.0

Let's practice!

Rimodellare i dati con pandas