Converting Data file to CSV file and read through Jupyter notebook

Data File to CSV file

1.Datasets Extraction

There are various free sources where we can get data of any domain and infer the business insights. Below I am listing the various useful resource where we can extract the datafiles for our projects.

  1. Kaggle:https://www.kaggle.com/tags/web-sites
  2. UCI Machine Learning: Repository :https://archive.ics.uci.edu/ml/index.php
  3. Data World:https://data.world/datasets/website
  4. Government data:https://data.gov.in/

2 .Data file to CSV file through excel

Some of the data file you download may not be in the condition where you cannot directly work with platform, it may be unstructured, In order to convert it into better readable form you need to convert it into structured data. Here I will show how we are going to convert the unstructured data file to structured csv file and use it in the Jupyter platform where it is helpful for the data scientist and data analyst to make his/her work simple.

Data file
Conversion to notepad
Paste the content of notepad to Excel.
Click on data in menu bar and click text to columns.
Use the delimiter option and change in to relevant columns and rows click next.
Changed to relevant rows and columns.

Read through Jupyter Notebook without changing anything in excel using python code.

open the jupyter notebook and type the following commands to import the csv file.

Import csv file to Jupyter

import numpy as np

import pandas as pd

After import the datasets read the csv file

df=pd.read_csv(“car.csv”)

Data frame has been created and now we are free to work and infer the insights of the datasets that is imported.

Reading the DATA file through Python code is as simple .

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Vignesh S

Vignesh S

Data scientist Aspirant passionate in learning new technologies and sharing my thoughts to others .