Tutorials References Exercises Videos NEW Menu
Paid Courses Website NEW

Pandas DataFrames


What is a DataFrame?

A Pandas DataFrame is a 2 dimensional data structure, like a 2 dimensional array, or a table with rows and columns.

Example

Create a simple Pandas DataFrame:

import pandas as pd

data = {
  "calories": [420, 380, 390],
  "duration": [50, 40, 45]
}

#load data into a DataFrame object:
df = pd.DataFrame(data)

print(df) 

Result


     calories  duration
  0       420        50
  1       380        40
  2       390        45

Try it Yourself »

Locate Row

As you can see from the result above, the DataFrame is like a table with rows and columns.

Pandas use the loc attribute to return one or more specified row(s)

Example

Return row 0:

#refer to the row index:
print(df.loc[0])

Result


  calories    420
  duration     50
  Name: 0, dtype: int64

Try it Yourself »

Note: This example returns a Pandas Series.

Example

Return row 0 and 1:

#use a list of indexes:
print(df.loc[[0, 1]])

Result


     calories  duration
  0       420        50
  1       380        40

Try it Yourself »

Note: When using [], the result is a Pandas DataFrame.


w3schools CERTIFIED . 2021

Get Certified!

Complete the Pandas modules, do the exercises, take the exam, and you will become w3schools certified!

$10 ENROLL

Named Indexes

With the index argument, you can name your own indexes.

Example

Add a list of names to give each row a name:

import pandas as pd

data = {
  "calories": [420, 380, 390],
  "duration": [50, 40, 45]
}

df = pd.DataFrame(data, index = ["day1", "day2", "day3"])

print(df) 

Result


        calories  duration
  day1       420        50
  day2       380        40
  day3       390        45

Try it Yourself »

Locate Named Indexes

Use the named index in the loc attribute to return the specified row(s).

Example

Return "day2":

#refer to the named index:
print(df.loc["day2"])

Result


  calories    380
  duration     40
  Name: 0, dtype: int64

Try it Yourself »

Load Files Into a DataFrame

If your data sets are stored in a file, Pandas can load them into a DataFrame.

Example

Load a comma separated file (CSV file) into a DataFrame:

import pandas as pd

df = pd.read_csv('data.csv')

print(df) 
Try it Yourself »

You will learn more about importing files in the next chapters.


Test Yourself With Exercises

Exercise:

Insert the correct Pandas method to create a DataFrame.

pd.(data)

Start the Exercise