SARVODAYA VIDYALAYA NO.

3
SECTOR-7. RK PURAM

INFORMATIC PRACTICES
CLASS:12th
PROJECT FILE
SESSION2023-24
TEACHER: STUDENT:
MS. PRIYA MAYANK ANUKUMARI
LECTURE (CS) CLASS: 12B
ID:
 CERTIFICATE
This to certify that Anu kumari, student of class
12th'B has successfully completed the research on
the project "Analysis of covid19 impact on India
using Data Visualizations" under the guidance of
"Miss Priya Mayank" during the year 2023-24.

Teacher's signature
 ACKNOWLEDGMENT
Iwould like to express my special thanks of gratitude
to my teacher Miss Priya Mayank as well as our
principal Mrs. Anamika Who gave me the excellent
opportunity to do this wonderful project on the topic
"Analysis of COVID-19 impact on India using data
visualization", Which also helped me in doing a lot of
research and Icame to know about so many things.
Secondly, I would like to thank my parents and friends
who helped me a lot in finishing this project within the
time limit.

Iam making this project not only for marks but also to
increase my knowledge.
ANALYSIS OF
COVID-19
IMPACT ON
INDIA
USING DATA
VISUALISATION
 INDEX
Sno. Topic Page
N
1. What is Covid-19? 1
2. Covid-19 in India
3. Worst affected states from Covid-1 3-5
inlndia
4. Least affected states from Covid-19 in 6-8
India
5. Deaths in each age group due to 9-11
Covid-19
6. Deaths in each age group in male 12-14
andfemale due to Covid-19
7. Covid-19 test conducted by different 15-17
countries in the world
8. Conclusion 18
9. Reference 19
 What is Covid-19?
Coronavirus disease 2019 (COVID-19) is a

contagious disease caused by Severe accurate

respiratory Syndrome coronavirus 2 (SARS-CoV-2).
The first case was identified in Wuhan, China, in
December 2019. It has since spread worldwide,
leading to an ongoing pandemic. Most people
infected with the COVID-19 virus will experience
mild to moderate respiratory illness and recover
without requiring special treatment. Older people
and those with underlying medical problems like.
Cardiovascular disease, diabetes, chronic
respiratory disease, and cancer are more likely to
develop seriousillness.
A new train of coronavirus is discovered in Britain.
It is said to mutate faster than the older variant.
 Covid-19 in India
The first case of COVID-19 in India, which
originated from China,was reported on 30 January
2020. India currently has the largest number of
confirmed cases in the world after the United States.

On 24 March, The Prime Minister ordered a

Nationawide lockdown for 21 days (about 3 weeks),
affecting the entire 1.3 billion population of India.
On April 14th, India extended the nationwide
lockdown till 3may, which was followed by two
week extensions.

From 1 June, the government started "unlocking"

the country (barring "containment zones") in three
unlock phases.
 Worst affected statesfrom
Covid-19 in India
Five worst affected states in India are Maharashtra,
Karnataka, Andhra Pradesh, Tamil Nadu, and Kerala.
Givenbelow is the bar graph as of 26th December 2020.

A B C

1 C r

2 1913382 1806298 49129

3 914488 888917 12044
4 880430 869478 7091
5 812142 790965 12048
6 732084 664951 2930
7

10

11

12
 PROGRAM

1 import matplotlib.pyplot as plt

2 import numpy as np
3 import pandas as pd
4 a=pd.read_csv(/storage/emulated/o/
Download/Covidip.csv')
5 X=np.linspace(1,61,5)
6 plt.xticks(x+6/2, Maharashtra,
'Karnataka,'APTN; Kerala')
7 plt.bar(x,alc],width=3,color='blue',
label=Cases')
8 plt.bar(x+3,a[r'],width=3,color='green,
label='Recover')
9 plt.bar(x+6,a[d'],width=3,color='red,
label='Death)
10 plt.title('Most affected states due to
covid19")
11 plt.legend)
12 plt.xlabel(States)
13 plt.ylabel(Number)
14 plt.showol
 OUTPUT
Most affected states due to covid19
2000000
Cases
Recover
Death

1750000

150000o

125000o

10000o0

750000

500000

250000

Maharashtra Karnataka AP TN Kerala

States
 Least affected states from
Covid-19 in India
Five worst affected states in India are Mizoram, Sikkim,
Nagaland, Meghalaya, and Arunachal Pradesh. Given
belowis the bar graph as of 26th December 2020.

CSV FILE

A B D
1 C d
2 4178 4036
3 5684 5142 125
4 11845 11544 77
13396 12940 135
6 16678 16454 56
7
 PROGRAM
1 import matplotlib.pyplot as plt
2 import numpy as np
3 import pandas as pd
a=pd.read_csv(/storage/emulated/0/
Download/covidip2.csv)
5 X=np.linspace(1,61,5)
6 plt.xticks(x+6/2, [Mizoram, 'Sikkim,
"Nagaland; Meghalaya, Arunachal
Pradesh])
7 plt.bar(x,a[c],width=3,color='blue,
label='Cases')
8 plt.bar(x+3,a[r]width=3,color='green',
label='Recover)
9 plt.bar(x+6,a[d']width=3,color=red,
label='Death')
10 plt.title('Least affected states due to
covid19)
11 plt.legend)
12 plt.xlabel(States)
13 plt.ylabel('Number)
14 plt.showol
 OUTPUT
Least affected states due to covid19
Cases
Recover
Death
16000

14000

12000

10000

8000

6000

4000 -

2000

Mizoram Sikkim Nagaland Meghalaya Arunachal Pradesh

States
 Deaths in each age group due
to Covid-19
Deaths caused in each age groups is shown
belowthrough a line graph as at 2ndSeptember,
2020.

Csv file

A B D

1 X
2 0-10 0.5
3 11-20 0.7
4 21-30 2.6
5 31-40 6.1
6 41-50 13.4
7 51-60 25.13
8 61-70 28.6
9 71-80 17
10 81-90 5.3
11 >90 0.5
12

13
 PROGRAM

1 import matplotlib.pyplot as plt

2 import pandas as pd
3 a=pd.read_csv(/storage/emulated/0/
Download/covidip3.csv')
4 plt.plot(alx]aly],marker=*,
markeredgecolor='r)
5 plt.title(% of death in each age group')
6 plt.xlabel(Ages')
7 plt.ylabel(percent')
8 plt.showol
 OUTPUT
30
% of death in each age group

25

20

percent

10

0-10 11-20 21-30 31-40 41-50 51-60 61-70 71-80 81-90 >90
Ages
Deathsin each age group in male
andfemnale dueto Covid-19
Deaths caused in each age groups in male and
female areshown below through a bar graph as of
2nd September 2020
CSV FILE

A
A B C

1 f m

2 109 180
3 195 202
4 529 926
5 952 2484
6 2308 5230
7 4548 9683
8 4947 11142
9 2766 6788
10 857 2141
11 104 197
12
 PROGRAM

import matplotlib.pyplot as plt

2 import pandas as pd
3 a=pd.read_csv(/storage/emulated/0/
Download/covidip3.csv)
4 plt.plot(alxlaly'lmarker=*,
markeredgecolor=r)
5 plt.title(% of death in each age group')
6 plt:xlabel(Ages)
7 pltylabel('percent')
8 plt.showØ
 OUTPUT
No. of Deaths up to 2nd Sep 2020
Female
Male

10000

8000

laqunN 6000

4000

2000

0-10 11-20 21-30 31 40 41-50 51-60 61-70 71-80 81-90 >90

Age
 Covid-19 test conducted by
different Countries in the World
Number of Covid-19 tests conducted by different
countries all over the world upto 16th December
2020. India has done 3rd largest testing in the
world.
CSV FILE

A B

1 n

2 224938642 USA
3 160000000 China
4 156646280 India
5 83867186 Russia
6 48488168 UK
7
30494O36 Germany
8 29323706 France
9 25700000 Brazil
10 24918644 Spain
11 24482190 Italy
12
 PROGRAM

1 import matplotlib.pyplot as plt

2 import pandas as pd
3a=pd.read_csv(/storage/emulated/0/
Download/covidip5.csv)
4 plt.barh (a>n],a[clcolor=)
5 plt.title(Number of coronavirus tests
performed in the most \n impacted
countries worldwide as of December 16,
2020)
6 plt:xlabel(No. of test')
7 plt.ylabel(Country)
8 plt.showØ
 OUTPUT
Number countries
of coronavirus tests performed in the most
worldwide as of December 16,2020
im

Italy

Spain

Brazil

France

Germany
Anunon

UK

Russia

India

China -

USA -

0.0 O.5 1.0 1.5 2.0

No, of test le8
 Conclusion
By visualizing data in the form of bar and line
graphs we can easily Analyse that the states
Worsley affected due to Covid-19 are states with
dense population and least affected are not so
densely populated.
The worst affected age group is 61 to 70 as there are
More deaths caused in this group due toCovid-19. We
can also clearly see that in every age group there is
more deaths caused in males than
in females.
We are also able to see that India stands at third
position in global testing of coronavirus with more
than 15.6 crores sample already tested.
 References
wwW.YOUTUBE.COM
https:llwww.youtube.com/watch?v=r-Dihn9-uTU
https://www.youtube.com/watch?v=PSji21jUNOO
WEBSITES
"https:lwww.who.int
" Https:llen.m.wikipedia.org
" https:llwww.statista.com
https:l/m.hindustantimes.com

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