Table of Contents
Use Series.values.tolist()
Method
To convert pandas
dataframe column to list:
- Use
pd.DataFrame()
to readposition_salaries
as apandas
data frame. - Use
df["Position"]
to get the columnposition
fromdf
- Use
position.values
to get values of theposition
- Use
position_values.tolist()
to get list ofposition_values
asposition_list
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 |
import pandas as pd<br> # Create a pandas data frame position_salaries = { 'Position': ["Business Analyst", "Junior Consultant", "Senior Consultant", "Manager", "Country Manager", "Region Manager", "Partner", "Senior Partner", "C-level", "CEO"], 'Level': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'Salary': [45000, 50000, 60000, 80000, 110000, 150000, 200000, 300000, 500000, 1000000] } df = pd.DataFrame(position_salaries) position = df["Position"] position_values = position.values position_list = position_values.tolist() print(column_list) |
The code above will print the following output on the console:
1 2 3 |
['Business Analyst', 'Junior Consultant', 'Senior Consultant', 'Manager', 'Country Manager', 'Region Manager', 'Partner', 'Senior Partner', 'C-level', 'CEO'] |
Suppose we already have a Python library called pandas
installed for working with data frames. If we don’t have it, we can install it using pip install pandas
.
We imported the Python library pandas
as pd
.
pd.DataFrame() is a class of Python two-dimensional data structures used for data analysis and manipulation. We used it to read positon_salaries
and to store the data frame in df
.
In the pandas
data frame, we can get columns of the data frame using the data retrieval technique that we use when working with arrays. The df["Position"]
took the column name and stored the column in position
.
In the Series.values
function:
Series()
is an n-dimensional array that holds data of any type. You may have questions about where thisSeries
is in the code. Here theposition
is aSeries
created usingdf["Position"]
.Series.values
reads theSeries
and returns an object of typenumpy.ndarray
.
Once we got a series
called position
, we used position.values
to get position_values
.
tolist()
is a predefined method in Python that does not hold any parameter. When we apply it to any iterable object, it converts that object to a list. We used it on our numpy.ndarray
type position_values
to get position_list
.
Further reading:
Use list()
Method
To convert the pandas
data frame column to list:
- Use
pd.DataFrame()
to readposition_salaries
as apandas
data frame. - Use
df["Position"]
to get the columnposition
fromdf
- Use
position.values
to get values of theposition
- Use
list()
to convertposition_values
toposition_list
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 |
import pandas as pd<br> position_salaries = { 'Position': ["Business Analyst", "Junior Consultant", "Senior Consultant", "Manager", "Country Manager", "Region Manager", "Partner", "Senior Partner", "C-level", "CEO"], 'Level': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'Salary': [45000, 50000, 60000, 80000, 110000, 150000, 200000, 300000, 500000, 1000000] } df = pd.DataFrame(position_salaries) position = df["Position"] position_values = position.values position_list = list(position_values) print(position_list) |
The code above will print the following output on the console:
1 2 3 |
['Business Analyst', 'Junior Consultant', 'Senior Consultant', 'Manager', 'Country Manager', 'Region Manager', 'Partner', 'Senior Partner', 'C-level', 'CEO'] |
We covered pd.DataFrame()
, position
, position_values
, and Series
while explaining the code using the Series.values.tolist()
method.
In this code snippet, we used the list()
method that takes an iterable object as an argument and creates an immutable list of that object. We passed position_values
as an iterable Series
to convert it to position_list
.
Conclusion
You can use tolist()
or list()
methods to convert the pandas
dataframe column to list.
You should always prefer tolist()
over list()
as tolist()
is much faster than list()
method.
That’s all about how to convert pandas dataframe column to list.