How to Rearrange Pandas DataFrame Columns?

How to Rearrange DataFrame Column Order

Changing the order of DataFrame columns may be necessary to group or present data in a specific way. Here's how to achieve this using pandas:

Using List Assignment:

One straightforward approach is to reassign the columns in the desired order. To move a column to the front, simply move its name to the beginning of a list that contains the column names. For example:

df = pd.DataFrame(np.random.rand(10, 5))
df['mean'] = df.mean(1)

# Rearrange columns
cols = df.columns.tolist()
cols = ['mean'] + cols[1:]
df = df[cols]

Using loc:

Alternatively, loc can be used to selectively assign rows and columns. To move a column to the beginning, use : for the rows and the desired column name as the first argument to loc. For example:

df = pd.DataFrame(np.random.rand(10, 5))
df['mean'] = df.mean(1)

# Rearrange columns
df = df.loc[:, ['mean']]

Using insert:

The insert method allows inserting a column at a specific position. To move a column to the front, use 0 as the position argument. For example:

df = pd.DataFrame(np.random.rand(10, 5))
df['mean'] = df.mean(1)

# Rearrange columns
df.insert(0, 'mean', df['mean'])

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