In [1]:

#loading the required libraries
import pandas as pd
from matplotlib import pyplot as plt
#import seaborn as sns

In [2]:

#loading the serie A dataset
sra=pd.read_csv('table_serie_2022-23.csv')

In [3]:

#having a glance at top 5 records of the dataset
sra.head()

Out [3]:

	Team	Position	PL	W	D	L	GD	PTS
0	Napoli	1	27	23	2	2	48	71
1	Lazio	2	27	15	7	5	23	52
2	Inter	3	27	16	2	9	16	50
3	Milan	4	27	14	6	7	8	48
4	Roma	5	27	14	5	8	9	47

In [4]:

#Looking at the number of rows(no. of teams) and columns in dataset
sra.shape

Out [4]:

(20, 8)

In [5]:

#Extracting the records where a team has positive GD.
sra[sra['GD']>=0]

Out [5]:

	Team	Position	PL	W	D	L	GD	PTS
0	Napoli	1	27	23	2	2	48	71
1	Lazio	2	27	15	7	5	23	52
2	Inter	3	27	16	2	9	16	50
3	Milan	4	27	14	6	7	8	48
4	Roma	5	27	14	5	8	9	47
5	Atalanta	6	27	13	6	8	13	45
6	Juventus	7	27	17	5	5	23	41
7	Udinese	8	27	9	11	7	6	38
8	Fiorentina	9	27	10	7	10	1	37

In [6]:

plt.bar(list(sra['PTS'][0:5].keys()),list(sra['PTS'][0:5]),color=["deepskyblue","cornflowerblue","blue","red","maroon"])
plt.xticks([0, 1, 2, 3, 4], ['NAP', 'LAZ', 'INT','MIL','ROM'])
plt.xlabel('Teams')
plt.ylabel('Prices')
plt.show()

In [7]:

#Teams going to the champions league
sra[0:4]

Out [7]:

	Team	Position	PL	W	D	L	GD	PTS
0	Napoli	1	27	23	2	2	48	71
1	Lazio	2	27	15	7	5	23	52
2	Inter	3	27	16	2	9	16	50
3	Milan	4	27	14	6	7	8	48

In [8]:

#Team going to the europa league
sra[4:5]

Out [8]:

	Team	Position	PL	W	D	L	GD	PTS
4	Roma	5	27	14	5	8	9	47

In [9]:

#Team going to the Conference league
sra[5:6]

Out [9]:

	Team	Position	PL	W	D	L	GD	PTS
5	Atalanta	6	27	13	6	8	13	45

In [10]:

#Team getting to relegated to Serie B league
sra[-3:]

Out [10]:

	Team	Position	PL	W	D	L	GD	PTS
17	Hellas Verona	18	27	4	7	16	-19	19
18	Sampdoria	19	27	3	6	18	-28	15
19	Cremonese	20	27	1	10	16	-27	13

In [11]:

#loading the serie A events dataset
esra=pd.read_csv('events_serie_2022-23.csv')

In [12]:

esra.head()

Out [12]:

	event_id	match_id	team	event_team	event_time	event_type	action_player_1	action_player_2
0	1	1	Juventus	away	23	Goal	Filip Kostić	Adrien Rabiot
1	2	1	Inter	home	30	Yellow card	Nicolo Barella	NaN
2	3	1	Juventus	away	31	Yellow card	Federico Gatti	NaN
3	4	1	Inter	home	63	Substitution	Danilo D'Ambrosio	Federico Dimarco
4	5	1	Inter	home	63	Substitution	Henrikh Mkhitaryan	Nicolo Barella

In [17]:

esra[esra['event_type'].str.contains('Goal')]

Out [17]:

	event_id	match_id	team	event_team	event_time	event_type	action_player_1	action_player_2
0	1	1	Juventus	away	23	Goal	Filip Kostić	Adrien Rabiot
23	24	2	Lazio	home	65	Goal	Mattia Zaccagni	NaN
37	38	3	Napoli	away	9	Goal	Victor Osimhen	Piotr Zieliński
40	41	3	Napoli	away	51	Goal	Victor Osimhen	Mathías Olivera
46	47	3	Napoli	away	68	Goal	Tanguy Ndombele	Khvicha Kvaratskhelia
...	...	...	...	...	...	...	...	...
4487	4488	269	Udinese	away	2	Goal	Rodrigo Becão	Gerard Deulofeu
4490	4491	269	Milan	home	15	Goal	Ante Rebic	Davide Calabria
4493	4494	269	Udinese	away	49	Goal	Adam Masina	Roberto Pereyra
4494	4495	269	Milan	home	46	Goal	Brahim Diaz	NaN
4498	4499	269	Milan	home	68	Goal	Ante Rebic	Brahim Diaz

600 rows × 8 columns

In [37]:

esra[(esra['team'] == 'Napoli')]

Out [37]:

	event_id	match_id	team	event_team	event_time	event_type	action_player_1	action_player_2
37	38	3	Napoli	away	9	Goal	Victor Osimhen	Piotr Zieliński
39	40	3	Napoli	away	35	Penalty	Khvicha Kvaratskhelia	Penalty
40	41	3	Napoli	away	51	Goal	Victor Osimhen	Mathías Olivera
44	45	3	Napoli	away	65	Substitution	Eljif Elmas	Hirving Lozano
45	46	3	Napoli	away	65	Substitution	Tanguy Ndombele	Piotr Zieliński
...	...	...	...	...	...	...	...	...
4360	4361	261	Napoli	away	79	Goal	Matteo Politano	Victor Osimhen
4361	4362	261	Napoli	away	83	Substitution	Mathías Olivera	Mario Rui
4362	4363	261	Napoli	away	83	Substitution	Adam Ounas	Victor Osimhen
4363	4364	261	Napoli	away	84	Disallowed goal	Disallowed goal	NaN
4364	4365	261	Napoli	away	93	Yellow card	Kim Min-jae	NaN

234 rows × 8 columns

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