Need help in plotting data in the dataframe

Question

I have the following dataframe;

    Region Name Year    Internet usage %
0   Northern Africa 2000    0.6
1   Northern Africa 2005    9.6
2   Northern Africa 2010    24.6
3   Northern Africa 2014    35.3
4   Northern Africa 2015    38.9
5   Northern Africa 2016    41.7
6   Northern Africa 2017    45.5
7   Sub-Saharan Africa  2000    0.5
8   Sub-Saharan Africa  2005    2.1
9   Sub-Saharan Africa  2010    6.5
10  Sub-Saharan Africa  2014    14.3
11  Sub-Saharan Africa  2015    17.7
12  Sub-Saharan Africa  2016    19.5
13  Sub-Saharan Africa  2017    21.8
14  Eastern Africa  2000    0.2
15  Eastern Africa  2005    1.3
16  Eastern Africa  2010    4.5
17  Eastern Africa  2014    9.8
18  Eastern Africa  2015    13.3
19  Eastern Africa  2016    15.0
20  Eastern Africa  2017    17.6
21  Middle Africa   2000    0.1
22  Middle Africa   2005    0.7
23  Middle Africa   2010    2.1
24  Middle Africa   2014    7.0
25  Middle Africa   2015    8.7
26  Middle Africa   2016    10.5
27  Middle Africa   2017    12.2
28  Southern Africa 2000    4.9
29  Southern Africa 2005    7.0
30  Southern Africa 2010    22.0
31  Southern Africa 2014    45.9
32  Southern Africa 2015    48.9
33  Southern Africa 2016    51.2
34  Southern Africa 2017    53.4
35  Western Africa  2000    0.1
36  Western Africa  2005    2.5
37  Western Africa  2010    7.7
38  Western Africa  2014    16.7
39  Western Africa  2015    21.1
40  Western Africa  2016    22.9
41  Western Africa  2017    25.2
​

I want to plot this data, where X axis has the 'Year', Y axis 'Internet usage %' and the different regions are displayed in different colors and this will be a line plot.

When I tried plotting it I got the plot wrong. Can someone help me with this.

Thanks in advance

Answer 1

Using seaborn :

sns.lineplot(data=df, x='Year',y='Internet usage %', hue='Region Name')

Answer 2

This is the code I have developed so far;

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.read_csv('Internet Usage over the years.csv', engine='python')

# Remove the first row as it is not required
df = df.iloc[1:]

# Rename the columns
df.columns = ['Region Code', 'Region Name', 'Year', 'Misc 1', 'Internet usage %', 'Misc 2', 'Misc 3']

df = df[(df['Region Name'] == 'Northern Africa') | (df['Region Name'] == 'Sub-Saharan Africa') | (df['Region Name'] == 'Eastern Africa') | (df['Region Name'] == 'Middle Africa') | (df['Region Name'] == 'Southern Africa') | (df['Region Name'] == 'Western Africa')]
df = df.reset_index()

# Remove unwanted columns from the dataframe
cols = [0, 1, 4, 6, 7]
df.drop(df.columns[cols], inplace=True, axis=1)

convert_dict = {'Year': int, 
                'Internet usage %': float
               } 

df = df.astype(convert_dict)

df.plot(x ='Year', y='Internet usage %', kind = 'line') 

plt.xlabel('Year')
plt.ylabel('% of individuals using the internet')

plt.legend(loc='upper left', fontsize=9, frameon=True, framealpha=1)

plt.title('Internet usage % in different regions of Afria over the years')
plt.show()

I have attached the resulting plot enter image description here

Answer 3

So here are three solutions that might work for you.

1. Using pandas pivot

df_plot = df.pivot(index='Year', columns='Region', values='Internet usage %')
df_plot.plot()

2. Using pandas groupby

fig, ax = plt.subplots()

for region, grp in df.groupby(['Region']):
    ax = grp.plot(ax=ax, kind='line', x='Year', y='Internet usage %', c=region, label=region)

plt.show()

3. Using seaborn

Please see @Diziet Asahi's answer.

Personally, I prefer the first solution, but this is of course up to you.