To convert a DataFrame column or row to a list in Pandas, we can use the Series method tolist(). Here's how to do it:
df['A'].tolist()
df.B.tolist()
Image below shows some of the solutions described in this article:
Setup
We will use the following DataFrame to convert rows and columns to list:
```python
import pandas as pd
df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
data:
| A | B | |
|---|---|---|
| 0 | 1 | 4 |
| 1 | 2 | 5 |
| 2 | 3 | 6 |
Convert column to list
To convert a column to a list, we can access the column using either
- the bracket notation
([]) - or the dot notation
(.)
and then call the tolist() method on the resulting pandas Series object:
df['A'].tolist()
df.B.tolist()
result:
[1, 2, 3]
[4, 5, 6]
Convert row to list
To get a list from a row in a Pandas DataFrame, we can use the iloc indexer to access the row by its index. Then call the tolist() method on the resulting pandas Series object:
row_list = df.iloc[0].tolist()
result:
[1, 4]
Convert column with list values to row
We can convert columns which have list values to rows by using method .explode(). The example below shows how to convert column B which has list values. We will use new DataFrame:
df = pd.DataFrame({'A':['a','b'],
'B':[['1', '2'],['3', '4', '5']]})
with data:
| A | B | |
|---|---|---|
| 0 | a | [1, 2] |
| 1 | b | [3, 4, 5] |
To rows by:
df.explode('B')
| A | B | |
|---|---|---|
| 0 | a | 1 |
| 0 | a | 2 |
| 1 | b | 3 |
| 1 | b | 4 |
| 1 | b | 5 |
Column from lists (string) to lists
Finally let's check how to convert column which contains list values stored as strings to list:
import pandas as pd
data_dict = {'one': pd.Series([1, 2, 3], index=['a', 'b', 'c']),
'two': pd.Series(['[1, 2]', '[3, 4]', '[5, 6]'], index=['a', 'b', 'c'])}
df = pd.DataFrame(data_dict)
data looks like:
| one | two | |
|---|---|---|
| a | 1 | [1, 2] |
| b | 2 | [3, 4] |
| c | 3 | [5, 6] |
We can extract list values by using list comprehensions:
[x.strip('[]').split(',') for x in df['two']]
which result into new list of lists:
[['1', ' 2'], ['3', ' 4'], ['5', ' 6']]
If we like to keep the list values in the column we can use ast module:
import ast
df.two.apply(ast.literal_eval)
Which we result into:
a [1, 2]
b [3, 4]
c [5, 6]
Name: two, dtype: object