Exploratory Data Analysis (EDA) using Python and Jupyter Notebook

How to open a file to start the data analysis?

First you need upload a excel file which has a .csv format. You can upload by clicking the button and see the file on the left side of the page as you can see the pic with red boxes below.

Let’s start our analysis. First we need import pandas to working with data sets properly. Then we import numpy to enable the array functions. And we import matplotlib to analyze the data’s and results on different graphs.

After completing all the importing procceses, we read excel file by using pandas.

We use head() function to analyze the top 5 data. Additionally, you can set the number of datas by entering the number inside the head() function.

You can check the information of datas by using info() that what type of data’s are and how much memory usage have occured. You can also use .shape command to see number of rows and columns.

We use describe() to see the different values of data’s such as maximum, minimum, standart deviation etc.

We use isna() command that returns a DataFrame object where all the values are replaced with a Boolean value True for NA (not-a -number) values, and otherwise False.

Let’s start with plotting

We plot the graphs by using plot() and you can change the type of the graphs for instance by using kind=”bar”etc.

Now we use hist() which is the another method of plotting process that indicates the data’s with histogram.

You can determine the width of the each blocks to change the styles by using bins command inside of the hist() function.