How to Drop a Level from a MultiIndex in Pandas DataFrame

John D K -

Here are several approaches to drop levels of MultiIndex in a Pandas DataFrame:

  • droplevel - completely drop MultiIndex level
  • reset_index - remove levels of MultiIndex while storing data into columns/rows

If you want to find more about: What is a DataFrame MultiIndex in Pandas

Step 1: Pandas drop MultiIndex by method - droplevel

Pandas drop MultiIndex on index/rows

Method droplevel() will remove one, several or all levels from a MultiIndex. Let's check the default execution by next example:

import pandas as pd

cols = pd.MultiIndex.from_tuples([(0, 1), (0, 1)])
df = pd.DataFrame([[1,2], [3,4]], index=cols)
df
0 1
0 1 1 2
1 3 4

We can drop level 0 of the MultiIndex by:

df.droplevel(level=0)

which will result in:

0 1
1 1 2
1 3 4

or level 1:

df.droplevel(level=1)

Pandas drop MultiIndex on columns

If the hierarchical indexing is on the columns then we can drop levels by parameter axis:

df.droplevel(level=0, axis=1)

Get column names of the dropped columns

If you like to get the names of the columns which will be dropped you can use next syntax:

  • for columns:
df.columns.droplevel(level=0)
  • for rows:
df.index.droplevel(level=0)

which will result of single index:

Int64Index([1, 1], dtype='int64')

Pandas drop MultiIndex with .columns.droplevel(level=0)

So we can drop level of MultiIndex with a simple reset of the column names like:

df.columns = df.columns.droplevel(level=0)

Step 2: Pandas drop MultiIndex to column values by reset_index

Drop all levels of MultiIndex to columns

Use reset_index if you like to drop the MultiIndex while keeping the information from it. Let's do a quick demo:

import pandas as pd

cols = pd.MultiIndex.from_tuples([(0, 1), (0, 1)])
df = pd.DataFrame([[1,2], [3,4]], index=cols)
0 1
0 1 1 2
1 3 4

After reset of the MultiIndex we will get:

df.reset_index()
level_0 level_1 0 1
0 0 1 1 2
1 0 1 3 4

Reset single level of MultiIndex

df.reset_index(level=1)

Typical Errors on Pandas Drop MultiIndex

When the droplevel is invoked on wrong axis: columns or rows like:

cols = pd.MultiIndex.from_tuples([(0, 1), (0, 1)])
df = pd.DataFrame([[1,2], [3,4]], index=cols)

df.columns.droplevel()

error is raised:

ValueError: Cannot remove 1 levels from an index with 1 levels: at least one level must be left.

Another example is when the levels are less the one which should be dropped:

cols = pd.MultiIndex.from_tuples([(0, 1), (0, 1)])
df = pd.DataFrame([[1,2], [3,4]], index=cols)

df.columns.droplevel(level=3)

IndexError: Too many levels: Index has only 1 level, not 4

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