Python Pandas Column Formation-CodePudding

Is there an easy way to reformat the columns from

2000-01-03 Location1 A1 B1 C1 A2 B2 C2 A3 B3 C3  
2000-01-04 Location2 A1 B1 C1 A2 B2 C2 A3 B3 C3  
2000-01-05 Location3 A1 B1 C1 A2 B2 C2 A3 B3 C3

2000-01-03 Location1 A1 A2 A3 B1 B2 B3 C1 C2 C3  
2000-01-04 Location2 A1 A2 A3 B1 B2 B3 C1 C2 C3  
2000-01-05 Location3 A1 A2 A3 B1 B2 B3 C1 C2 C3

Thanks

CodePudding user response：

To reorder columns dynamically based on value, here is a way to do it:

df.sort_values(df.index[0], axis=1)

This returns a dataframe with columns (axis=1) ordered based on sorted value of first row.

Here is a full example using your data sample:

import pandas as pd
from io import StringIO

sample=StringIO('''date location x1 y1 z1 x2 y2 z2 x3 y3 z3
2000-01-03 Location1 A1 B1 C1 A2 B2 C2 A3 B3 C3
2000-01-04 Location2 A1 B1 C1 A2 B2 C2 A3 B3 C3
2000-01-05 Location3 A1 B1 C1 A2 B2 C2 A3 B3 C3''')

df = pd.read_csv(sample, sep=' ')
print(df)

df2 = df.sort_values(df.index[0], axis=1)
initialCols = ['date','location']
restCols = [col for col in df2.columns if col not in initialCols]
dfFinal = df2[initialCols   restCols]
dfFinal

CodePudding user response：

One of the easiest ways to reorder the columns of Pandas DataFrame is to use indexing

reordered_col_list = ['Date', 'Location', 'A1', 'A2', 'A3', 'B1', 'B2', 'B3', 'C1', 'C2', 'C3']
df = df[reordered_col_list]