To convert an index to a list in Pandas DataFrame, use the Index.tolist()
, Index.values.tolist()
and list()
functions. These functions are used to return a list of values. In this article, I will explain how to convert the pandas DataFrame index to a list by using list()
, index.tolist()
, and index.values
functions with examples.
1. Quick Examples of Convert Index to List
If you are in a hurry, below are some quick examples of how to convert the index to list in DataFrame.
# Below are some quick examples
# Example 1: Use tolist() function to convert index to list
df2 = df.index.tolist()
# Example 2: Convert the index as list using tolist()
df2 = df.index.values.tolist()
# Example 3: Convert the index into a list
df2 = list(df.index)
# Example 4: Use list() function to convert index as a list
df2 = list(df.index.values)
2. Syntax of Index.tolist()
Following is the syntax of Pandas Index.tolist()
function.
# Syntax of Index.tolist()
Index.tolist()
It returns a list of the values.
Now, Let’s create Pandas DataFrame using data from a Python dictionary, where the columns are Courses
, Fee
, Duration
and Discount
.
import pandas as pd
import numpy as np
technologies= ({
'Courses':["Spark","PySpark","Hadoop","Pandas"],
'Fee' :['22000','25000','24000','26000'],
'Duration':['30days','50days','40days','60days'],
'Discount':['1000','2300','2500','1400']
})
df = pd.DataFrame(technologies, index = ['r1', 'r2', 'r3', 'r4'])
print(df)
Yields below output.
# Output:
Courses Fee Duration Discount
r1 Spark 22000 30days 1000
r2 PySpark 25000 50days 2300
r3 Hadoop 24000 40days 2500
r4 Pandas 26000 60days 1400
3. Pandas Convert Index to List using tolist()
We can use the Pandas DataFrame.index.tolist()
function to convert a DataFrame index to a list object. pandas.Index is a basic object that stores axis labels for all pandas objects. The Index is a type of class pandas.core.indexes.base.Index
# Use tolist() function to convert index to list
df2 = df.index.tolist()
print(df2)
Yields below output.
# Output:
['r1', 'r2', 'r3', 'r4']
Alternatively, you can also use df.index.values.tolist()
.
# Using df.index.values
df.index.values.tolist()
4. Convert Index as a List Using list()
You can also use the Python list() function to convert the pandas index to a list object. This function takes an object as an argument you wanted to convert, I am using DataFrame.Index object as an argument.
# Use list() function to convert index as a list
df2 = list(df.index)
print(df2)
Yields the same output as above.
We could also pass DataFrame.index.values as a param. index.values
actually return a NumPy object, so here we are actually converting NumPy to List.
# Convert the index into a list
df2 = list(df.index.values)
print(df2)
Yields the same output as above.
6. Complete Example For Convert Index as a List
import pandas as pd
import numpy as np
technologies= ({
'Courses':["Spark","PySpark","Hadoop","Pandas"],
'Fee' :['22000','25000','24000','26000'],
'Duration':['30days','50days','40days','60days'],
'Discount':['1000','2300','2500','1400']
})
df = pd.DataFrame(technologies, index = ['r1', 'r2', 'r3', 'r4'])
print(df)
# # Use tolist() function to convert index to list
df2 = df.index.tolist()
print(df2)
# convert the index as list using tolist()
df2 = df.index.values.tolist()
print(df2)
# Convert the index into a list
df2 = list(df.index)
print(df2)
# Use list() function to convert index as a list
df2 = list(df.index.values)
print(df2)
7. Conclusion
In this article, I have explained how to convert an index to a list in Pandas DataFrame by using Index.tolist()
, list()
, and index.values.tolist()
function with examples.
Happy Learning !!
Related Articles
- Get First Row of Pandas DataFrame
- How to Use NOT IN Filter in Pandas
- Pandas Get Last Row from DataFrame
- Pretty Print Pandas DataFrame or Series
- Pandas Series.replace() – Replace Values
- Pandas Handle Missing Data in Dataframe
- Convert NumPy Array to Pandas DataFrame
- How to Get an Index from Pandas DataFrame
- Pandas Get First Column of DataFrame as Series
- Apply Multiple Filters to Pandas DataFrame or Series