Flatten multi-index columns in pandas DataFrames

Setup

# Import libraries
import pandas as pd
import seaborn as sns

# Load sample data in a DataFrame
df = (
    sns.load_dataset('iris')
    [['species', 'petal_length']]
    .groupby('species')
    .agg(['min', 'mean', 'max'])
)
df

	petal_length
	min	mean	max
species
setosa	1.0	1.462	1.9
versicolor	3.0	4.260	5.1
virginica	4.5	5.552	6.9

Drop a level

# Just drop the first level
df.droplevel(0, axis=1)

	min	mean	max
species
setosa	1.0	1.462	1.9
versicolor	3.0	4.260	5.1
virginica	4.5	5.552	6.9

Concatenate names

# Method chaining
df.set_axis(['_'.join(col).strip() for col in df.columns.values], axis=1)

	petal_length_min	petal_length_mean	petal_length_max
species
setosa	1.0	1.462	1.9
versicolor	3.0	4.260	5.1
virginica	4.5	5.552	6.9

# Classic way
df.columns = ['_'.join(col).strip() for col in df.columns.values]
df

	petal_length_min	petal_length_mean	petal_length_max
species
setosa	1.0	1.462	1.9
versicolor	3.0	4.260	5.1
virginica	4.5	5.552	6.9