How to change the order of DataFrame columns?

Question

I have the following DataFrame (df):

import numpy as np
import pandas as pd

df = pd.DataFrame(np.random.rand(10, 5))

Answer 1

import numpy as np
import pandas as pd
df = pd.DataFrame()
column_names = ['x','y','z','mean']
for col in column_names: 
    df[col] = np.random.randint(0,100, size=10000)

You can try out the following solutions :

Solution 1:

df = df[ ['mean'] + [ col for col in df.columns if col != 'mean' ] ]

Solution 2:

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df = df[['mean', 'x', 'y', 'z']]

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Solution 3:

col = df.pop("mean")
df = df.insert(0, col.name, col)

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Solution 4:

df.set_index(df.columns[-1], inplace=True)
df.reset_index(inplace=True)

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Solution 5:

cols = list(df)
cols = [cols[-1]] + cols[:-1]
df = df[cols]

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solution 6:

order = [1,2,3,0] # setting column's order
df = df[[df.columns[i] for i in order]]

Time Comparison:

Solution 1:

CPU times: user 1.05 ms, sys: 35 µs, total: 1.08 ms Wall time: 995 µs

Solution 2:

CPU times: user 933 µs, sys: 0 ns, total: 933 µs Wall time: 800 µs

Solution 3:

CPU times: user 0 ns, sys: 1.35 ms, total: 1.35 ms Wall time: 1.08 ms

Solution 4:

CPU times: user 1.23 ms, sys: 45 µs, total: 1.27 ms Wall time: 986 µs

Solution 5:

CPU times: user 1.09 ms, sys: 19 µs, total: 1.11 ms Wall time: 949 µs

Solution 6:

CPU times: user 955 µs, sys: 34 µs, total: 989 µs Wall time: 859 µs