How to change the order of DataFrame columns?

Bringing key columns front and center

Make your star column take the lead with this magic trick:

# 'mean' has stage fright? Get it first in line!
df.insert(0, 'mean', df.pop('mean'))
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Using an older version of pandas (below 1.3)? Fear not and run this line instead:

# Who needs time machines when you have different Panda versions?
df.insert(0, 'mean', df['mean'])
df = df.drop(columns=['mean'], axis=1)
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Juggling columns like a pro

Need to rotate columns like a revolving sushi bar? Well, here you go:

# Your DataFrames will thank you for their new positions!
cols = list(df.columns)
df = df[cols[-1:] + cols[:-1]]  # Take a bow 'mean', you're the new starter!
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Be cool, use [] and avoid the outdated ix.

Adapting to dynamic orders

For those cases when column order depends on runtime conditions, use this dynamic piece of code:

#DynamicDay? Adapt on the fly!
desired_first_col = 'mean'
df = df.reindex(columns=[desired_first_col] + 
                [col for col in df.columns if col != desired_first_col])
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Expert level column shuffling

Handling complex reorders

For those tricky times when a single move won't cut it:

# Hogwarts hadn't such a complex order!
cols = ['mean', 'std', 'max', 'A', 'B']
df = df[cols]  # Now the DataFrame looks like a well-done spell!
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Dodging ordering pitfalls

Always verify the upcoming order to avoid repeating or missing columns:

# Asserting order: like looking where you step...but for DataFrames!
assert len(cols) == len(df.columns) and len(set(cols)) == len(df.columns)
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Keeping original order with a sprinkle of change

Modify column order without losing the original sensation:

# We keep it original here but with some added spice!
col_to_front = 'mean'
new_cols = [col_to_front] + [col for col in df.columns if col != col_to_front]
df = df[new_cols]
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Mastering column rearrangement in pandas

The art of pop() and insert()

Here's how to extract a column and insert it back to your desired place:

# Playing 'Hide and Seek' with DataFrames!
mean_col = df.pop('mean')
df.insert(0, 'mean', mean_col)
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Aligning semantic flow

For that extra clarity, place columns according to their logical relationship.

Efficient tricks for column reordering

Trim your columns reordering to fewer lines of code:

# We keep things short and sweet here!
df = df[new_cols]
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Always ensure there are no mismatches or missing columns!