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Importing Data in Python


There are always essential things we do before running any python programs which are extremely simple. And the program starts by getting the data into the Python environment. After importing the data we can visualize , wrangle and clean it.

In this blog, you'll learn some important methods to import data into Python. We will start with various files formats, including .txt , .xlsx and .csv files, which are simple formats for data storage.

CSV Files

The CSV format is one of the common data type. Which is comma-separated, indicating where one field ends and the next field starts. First. We need to capture the full path where your CSV file is stored. And then import our CSV file with the pandas library as we do in the next code.

import pandas as pd
path = "/content/drive/MyDrive/addresses.csv"
df_bonus = pd.read_csv(path)

Text Files

The text file is another common data type, which contains textual data. Importing text file is so similar to cvs where we will also use pandas but with different function. In our example we use a simple text file which contains several sentences.

text_path = "/content/drive/MyDrive/sample3.txt"
text = pd.read_table(text_path)

Excel Data

we can import excel file is simple way using pandas and to do that we have to use ExcelFile function.

excel_path= "/content/drive/MyDrive/ir211wk12sample.xls"
excel= pd.ExcelFile(excel_path)


The data is often available on a website and can be downloaded into a local device. So we can load the data directly by a website URL into Python.

And to do that, firstly we have to import the urllib library for performing this task. Then we save the loaded file in the local python environment using the urlretrieve function. Finally we can simply read the file using the pandas library as we did in the previous examples.

import urllib
from urllib.request import urlretrieve

url = ''

urlretrieve(url, 'airtravel.csv')

df_web = pd.read_csv('airtravel.csv')


SQL Database

In order to import data SQL, we have to import In order to import data into anSQLite llibrary. The next step is to establish the connection with the database as we do in our example.

import sqlite3
conn = sqlite3.connect('my_data.db')
c = conn.cursor()
Data = c.execute('''SELECT * FROM username''').fetchall()

Finally thank you so much for reading. As always, I welcome feedback. And this is my GitHub link.


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