/Python/Python pandas change column order

Python pandas change column order

Pandas reorder columns

# setting up a dummy dataframe
raw_data = {'name': ['Willard Morris', 'Al Jennings', 'Omar Mullins', 'Spencer McDaniel'],
        'age': [20, 19, 22, 21],
        'favorite_color': ['blue', 'red', 'yellow', "green"],
        'grade': [88, 92, 95, 70]}
df = pd.DataFrame(raw_data, index = ['Willard Morris', 'Al Jennings', 'Omar Mullins', 'Spencer McDaniel'])
df

#now 'age' will appear at the end of our df
df = df[['favorite_color','grade','name','age']]
df.head()

Pandas reorder columns

# Get column list in ['item1','item2','item3'] format 
df.columns
# [0]output: 
Index(['item1','item2','item3'], dtype='object')

# Copy just the list portion of the output and rearrange the columns 
cols = ['item3','item1','item2']

# Resave dataframe using new column order
df = df[cols]

Python pandas change column order

In [39]: df
Out[39]: 
          0         1         2         3         4  mean
0  0.172742  0.915661  0.043387  0.712833  0.190717     1
1  0.128186  0.424771  0.590779  0.771080  0.617472     1
2  0.125709  0.085894  0.989798  0.829491  0.155563     1
3  0.742578  0.104061  0.299708  0.616751  0.951802     1
4  0.721118  0.528156  0.421360  0.105886  0.322311     1
5  0.900878  0.082047  0.224656  0.195162  0.736652     1
6  0.897832  0.558108  0.318016  0.586563  0.507564     1
7  0.027178  0.375183  0.930248  0.921786  0.337060     1
8  0.763028  0.182905  0.931756  0.110675  0.423398     1
9  0.848996  0.310562  0.140873  0.304561  0.417808     1

In [40]: df = df[['mean', 4,3,2,1]]

-1

Source: stackoverflow.com

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