DEV Community

c a
c a

Posted on • Originally published at chrisdevcode.hashnode.dev on

Quick Data Exploration - Python

Hi There! Welcome to Data 101.

NOTE:

I'll be using Google's Colab and Python in the article.

To learn how to read files, refer to the previous article in this series :

https://chrisdevcode.hashnode.dev/reading-data-from-files-using-python

Data Exploration

In Data Exploration, we look into finding the number of instances of records, number of columns and rows, the columns and data types in each column...

I will be using pandas library throughout.

I will be using airlines and airports CSV files.

To import the data:

import pandas as pd
airlines = pd.read_csv('airlines.csv')
airports = pd.read_csv('airports.csv')
Enter fullscreen mode Exit fullscreen mode

Viewing First and Last few rows

To view the first 5 rows on the data set, we use .head() from pandas.

airports.head()
Enter fullscreen mode Exit fullscreen mode

head.png

You can use .head(x) to get x number of rows from the top

To view the last 5 rows on the data set, we use .tail() from pandas.

airports.tail()
Enter fullscreen mode Exit fullscreen mode

tail.png

Viewing Rows and Columns

To know the number of columns and rows in your data frame, use .shape. It returns the dimensions of your data set:

airports.shape
Enter fullscreen mode Exit fullscreen mode

shape.png

To view the columns in the data frame, use .columns()

airports.columns
Enter fullscreen mode Exit fullscreen mode

columns.png

Viewing Data Types

To view datatypes of each data in each column, use .dtypes:

airports.dtypes
Enter fullscreen mode Exit fullscreen mode

dtype.png

Other tricks you could use are:

x.rows
x.info()
x.describe()
x.unique()
x.describe()
Enter fullscreen mode Exit fullscreen mode

Top comments (0)