How to make our first graph using Python

• Author
• Recent Posts

Stratos Matzouranis

The journey began in 2008 where I officially started working in the field of IT (IT). Starting the first semester of school I realized a special attraction towards databases and automation. I have been involved with databases such as Microsoft SQL Server / Oracle Database, data analysis and automations using the command line (CLI), Visual Basic for Applications and Python. Through years of experience I have developed these capabilities so that I can make my life easier. For me, the purpose of every IT guy and every office worker is to have the knowledge so that through tools he can work a little but produce a lot. Through this his website DataPlatform.gr I try to offer knowledge and propose solutions to everyday problems.

Certifications:

Latest posts by Stratos Matzouranis (see all)

• How we enable Unified Auditing in Oracle Database - 7 October 2024
• What is PostgreSQL and how do we do a full installation - September 2, 2024
• How do we configure GoldenGate replication to read from Oracle Data Guard Standby - 2 August 2024

In the article we will see how we can make graphs barplots with use Python easy and fast.

To begin with, we should load 3 libraries that we have ready with the functions we will need:

import pandas as pd #για τη δημιουργία dataframe
import matplotlib 
import matplotlib.pyplot as plt #για το γράφημα
import numpy as np #για εύκολα math calculations

df = pd.read_csv('https://cocl.us/datascience_survey_data', index_col=0)

In the variable df we loaded one dataframe built using pandas with data from a public csv.

With .head() preview the first records of the dataframe:

df.head()

We can do them too sort:

df = df.sort_values('Very interested',axis=0, ascending=False)

df.head()

Now let's create the chart

We will need a new variable that will have the parameters of the graph, we will call it 'for' which will take as an argument the dataframe(df) and with .plot(kind='bar') we define it as a bar chart.

After defining what else we want, such as name, font size (legend is the box with the descriptions in the upper right graph) and colors.

By choice plt.show() will display it:

per = df.plot(kind='bar', 
            figsize=(20, 8), 
            width=0.8, 
            color=['#5cb85c', '#5bc0de', '#d9534f'],
           )
per.set_title("Παράδειγμα bar plot", fontsize=16)
per.spines['left'].set_visible(False)
per.spines['top'].set_visible(False)
per.spines['right'].set_visible(False)
per.axes.get_yaxis().set_visible(False)
per.tick_params(labelsize=14)
per.legend(fontsize=14)

for p in per.patches:
    per.annotate(np.round(p.get_height(),decimals=2), 
                (p.get_x()+p.get_width()/2., p.get_height()), 
                ha='center', 
                va='center', 
                xytext=(0, 10), 
                textcoords='offset points',
                fontsize = 14
               )

plt.show()

The result

As an understanding at first it seems difficult but I think the result shows that it is worth the effort.

Taking the example as a guide you can experiment by playing with the parameters and you will see that it is easier than it first seems.