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To combine a dataframe and list of words under columns into a merged format, you can follow these steps:

1. Create the dataframe by importing data from a file or building it from scratch using pandas.

2. Create a list of words that you want to add to the dataframe under each column.

3. Use the pandas concat method to concatenate the dataframe and the list of words along the desired axis.

For example, if you have a dataframe df with columns A, B, and C, and a list of words words that you want to add under each column, you can use the following code:

import pandas as pd

# create the dataframe
df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]})

# create the list of words
words = ['dog', 'cat', 'bird']

# use concat to combine the dataframe and list of words
merged_df = pd.concat([df, pd.DataFrame(words, columns=['A']), pd.DataFrame(words, columns=['B']), pd.DataFrame(words, columns=['C'])], axis=0)

# reset the index
merged_df.reset_index(drop=True, inplace=True)

# print the merged dataframe
print(merged_df)

This will give you a merged dataframe where the words are listed under each column:

    A    B     C
0   1    4     7
1   2    5     8
2   3    6     9
3  dog  dog   dog
4  cat  cat   cat
5  bird bird bird