World's Best AI Learning Platform with profoundly Demanding Certification Programs
Designed by IITian's, only for AI Learners.
Download our e-book of Introduction To Python
Related Blog
Top Discussion
How to leave/exit/deactivate a Python virtualenvironment Exception Type: JSONDecodeError at /update/ Exception Value: Expecting value: line 1 column 1 (char 0) how to store the name of independent variable in a list which show non linear behavior HOW TO REMOVE OBJECT COLUMNS IN DATAFRAME. For loop giving incorrect answer What is the difference between a module and a package in Python? What is RMSE and MSE in linear regression models? How to know given a binary tree is a binary search tree or not? Join Discussion
Top Courses
Master's In Artificial Intelligence Job Guarantee Program
4.5 (1,292 Ratings)
547 Learners
Webinars
Bootcamp Session : Python for Artificial Intelligence.
Oct 2nd (4:00 PM) 173 Registered
Handling Different Data File In Python
Shashank Shanu
10 months ago
Table of Content
- Handling CSV Files
- Handling Text Files
- Handling excel file
- Conclusion
This article is a basic introduction to get some idea about how to import different
data into python. So, let’s start.
Python
provides us with many different functions to handle various types of data files.
In this article, I will try to take you through some of the functions mostly
used to handle different data files such as flat files, CSV and text, etc.
Handling CSV Files
One
of the most commonly used data file types is a CSV data file. CSV stands for
comma-separated-values. This type of file store data into a table from where
rows as observations and columns as attributes.
Let’s
take an example
import pandas as pd
data = pd.read_csv("People Charm case.csv")
print(data.shape)
data.head(5)
In
the above example, we used python library pandas which have a function “read_csv()”
to read a CSV file. Then we print the shape of the dataset and displayed only
the top 5 rows of the dataset using the head() function.
Output:
Handling Text Files
One
another most common flat file type is text files. Here we will take a file
that contains details of weblog in the text data file.
data2 = pd.read_table("file4.txt")
print(data2)In
the above example, we are reading a text file using pandas “read_table()”
function and printing it out.
Output:
Handling excel file
We
all know how popular and important excel file is and most of us used it in our
day to day life. So, it does not need any detailed introduction.
Let’s
take an example and see how we can read an excel file into python
data2 = pd.read_excel(“article topics.xlsx”)
data2.head()Output:
Here
we have an excel sheet and load it into python using “read_excel”
function available in panda’s library.
Conclusion
In
this, we learned about how to import different types of the data file into python.
Note I was using Jupiter notebook here so the output looks like this. The
knowledge of predictive modelling is important but equally important is knowing
how to import data files such as CSV, text, Excel files from a local machine
into the Python environment.
I hope you enjoyed reading this article and finally, you came
to know about Handling Different Data File In Python.
For more such blogs/courses on data science, machine
learning, artificial intelligence and emerging new technologies do visit us at InsideAIML.
Thanks for reading…
Happy Learning…