Turn Pandas Multi-Index into column

Pandas DataFrame is a two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). A multi-index dataframe has multi-level, or hierarchical indexing. We can easily convert the multi-level index into the column by the reset_index() method.

DataFrame.reset_index() is used to reset the index to default and make the index a column of the DataFrame.

Turn Multi-Index into Column in Pandas

Below are the steps by which we can convert columns from multi-index in Pandas in Python:

Step 1: Creating a Multi-Index DataFrame

Let’s see an example by making a multi-index dataframe first. In this step, a multi-index DataFrame df is created with tuples (‘A’, ‘a’), (‘A’, ‘b’), (‘B’, ‘a’), and (‘B’, ‘b’) as indices, and corresponding values 2, 4, 6, and 8.

Python3

# Creating index for multi-index dataframe
tuples = [('A', 'a'), ('A', 'b'), ('B', 'a'), ('B', 'b')]
index = pd.MultiIndex.from_tuples(tuples, names=['index_1', 'index_2'])

# Value corresponding to the index
data = [2, 4, 6, 8]

# Creating dataframe using 'data' and 'index'
df = pd.DataFrame(data=data, index=index, columns=['value'])
print(df)

Output:

DataFrame created with multi-index

Step 2: Converting Index into the Column

Here we can see the hierarchical indexing, we are converting each index into a separate column using the reset_index() method.

Python3

new_df = df.reset_index()
print(new_df)

Output:

DataFrame after using reset_index() method

Here we can see that the all the levels of index are converted to columns. We can also select which level of multi-index to reset using parameter level.

level parameter can be an index name or can be a tuple or list of indices to remove from the dataframe and make them as dataframe columns.

Python3

new_df_2 = df.reset_index(level=("index_2",))
new_df_2.head()

Output:

DataFrame after using reset_index with level parameter set.

Note: Here, we can see that only “index_2” is reset from index and has become a column, but not “index_1“.