How to Load Datasets from CSV in Python

Need to import a CSV file into Python?

If so, you’ll see the complete steps to import a CSV file into Python using Pandas.

To start, here is a simple template that you may use to import a CSV file into Python:

import pandas as pd

df = pd.read_csv (r'Path where the CSV file is stored\File name.csv')
print (df)

Next, you’ll see an example with the steps needed to import your file.

Importing the Data into Python

So let’s begin with a simple example, where you have the following client list and some additional sales information stored in a CSV file (where the file name is ‘Clients‘):

Person NameCountryProductPurchase Price
JonJapanComputer$800
BillUSTablet$450
MariaCanadaPrinter$150
RitaBrazilLaptop$1,200
JackUKMonitor$300
RonSpainLaptop$1,200
JeffChinaLaptop$1,200
CarrieItalyComputer$800
MarryPeruComputer$800
BenRussiaPrinter$150

Steps to Import a CSV File into Python using Pandas

Step 1: Capture the File Path

Firstly, capture the full path where your CSV file is stored.

For example, let’s suppose that a CSV file is stored under the following path:

C:\Users\Ron\Desktop\Clients.csv

You’ll need to modify the Python code below to reflect the path where the CSV file is stored on your computer. Don’t forget to include the:

  • File name (as highlighted in green). You may choose a different file name, but make sure that the file name specified in the code matches with the actual file name
  • File extension (as highlighted in blue). The file extension should always be ‘.csv’ when importing CSV files

Step 2: Apply the Python code

Type/copy the following code into Python, while making the necessary changes to your path.

Here is the code for our example (you can find additional comments within the code itself):

import pandas as pd

df = pd.read_csv (r'C:\Users\Ron\Desktop\Clients.csv')   #read the csv file (put 'r' before the path string to address any special characters in the path, such as '\'). Don't forget to put the file name at the end of the path + ".csv"
print (df)

Step 3: Run the Code

Finally, run the Python code and you’ll get:

  Person Name Country   Product Purchase Price
0         Jon   Japan  Computer          $800 
1        Bill      US    Tablet          $450 
2       Maria  Canada   Printer          $150 
3        Rita  Brazil    Laptop        $1,200 
4        Jack      UK   Monitor          $300 
5         Ron   Spain    Laptop        $1,200 
6        Jeff   China    Laptop        $1,200 
7      Carrie   Italy  Computer          $800 
8       Marry    Peru  Computer          $800 
9         Ben  Russia   Printer          $150

Optional Step: Select Subset of Columns

Now what if you want to select a subset of columns from the CSV file?

For example, what if you want to select only the Person Name and Country columns. If that’s the case, you can specify those columns names as captured below:

import pandas as pd

data = pd.read_csv (r'C:\Users\Ron\Desktop\Clients.csv')   
df = pd.DataFrame(data, columns= ['Person Name','Country'])
print (df)

You’ll need to make sure that the column names specified in the code exactly match with the column names within the CSV file. Otherwise, you’ll get NaN values.

Once you’re ready, run the code (after adjusting the file path), and you would get only the Person Name and Country columns:

  Person Name Country
0         Jon   Japan
1        Bill      US
2       Maria  Canada
3        Rita  Brazil
4        Jack      UK
5         Ron   Spain
6        Jeff   China
7      Carrie   Italy
8       Marry    Peru
9         Ben  Russia
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