Plotting F1 race data

Casus Plotting formule 1 data

Data is provided by Ivon Kok.

It contains points per location per F1 coureur. The progress in points will be plotted by a cumsum plot

import pandas as pd

Load data

df = pd.read_csv('data/points.csv')

Inspect data

df.head(2)

	Coureur	BHR	EMI	POR	SPA	MON	AZE	FRA	STI	OOS	...	NED	ITA	RUS	TUR	VST	MXS	SAP	QAT	SAU	ABU
0	Hamilton	25	19	25	25	7	0	18	19	12	...	19	0	25	0	0	0	0	0	0	0
1	Verstappen	18	25	18	19	25	0	26	25	26	...	25	0	18	0	0	0	0	0	0	0

2 rows × 23 columns

df.tail(2)

	Coureur	BHR	EMI	POR	SPA	MON	AZE	FRA	STI	OOS	...	NED	ITA	RUS	TUR	VST	MXS	SAP	QAT	SAU	ABU
19	Kubica	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
20	Mazepin	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0

2 rows × 23 columns

# check if all are numbers
df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 21 entries, 0 to 20
Data columns (total 23 columns):
 #   Column   Non-Null Count  Dtype  
---  ------   --------------  -----  
 0   Coureur  21 non-null     object 
 1   BHR      21 non-null     int64  
 2   EMI      21 non-null     int64  
 3   POR      21 non-null     int64  
 4   SPA      21 non-null     int64  
 5   MON      21 non-null     int64  
 6   AZE      21 non-null     int64  
 7   FRA      21 non-null     int64  
 8   STI      21 non-null     int64  
 9   OOS      21 non-null     int64  
 10  GBR      21 non-null     int64  
 11  HON      21 non-null     int64  
 12  BEL      21 non-null     float64
 13  NED      21 non-null     int64  
 14  ITA      21 non-null     int64  
 15  RUS      21 non-null     int64  
 16  TUR      21 non-null     int64  
 17  VST      21 non-null     int64  
 18  MXS      21 non-null     int64  
 19  SAP      21 non-null     int64  
 20  QAT      21 non-null     int64  
 21  SAU      21 non-null     int64  
 22  ABU      21 non-null     int64  
dtypes: float64(1), int64(21), object(1)
memory usage: 3.9+ KB

#some statistics
df.describe()

	BHR	EMI	POR	SPA	MON	AZE	FRA	STI	OOS	GBR	...	NED	ITA	RUS	TUR	VST	MXS	SAP	QAT	SAU	ABU
count	21.000000	21.000000	21.000000	21.000000	21.000000	21.000000	21.000000	21.000000	21.000000	21.000000	...	21.000000	21.000000	21.000000	21.0	21.0	21.0	21.0	21.0	21.0	21.0
mean	4.857143	4.857143	4.857143	4.857143	4.857143	4.809524	4.857143	4.857143	4.857143	4.809524	...	4.857143	4.857143	4.857143	0.0	0.0	0.0	0.0	0.0	0.0	0.0
std	7.329978	7.350413	7.329978	7.350413	7.268327	7.256852	7.397876	7.350413	7.397876	7.256852	...	7.350413	7.397876	7.268327	0.0	0.0	0.0	0.0	0.0	0.0	0.0
min	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	...	0.000000	0.000000	0.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0
25%	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	...	0.000000	0.000000	0.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0
50%	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	...	0.000000	0.000000	0.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0
75%	8.000000	8.000000	8.000000	8.000000	8.000000	8.000000	8.000000	8.000000	8.000000	8.000000	...	8.000000	8.000000	8.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0
max	25.000000	25.000000	25.000000	25.000000	25.000000	25.000000	26.000000	25.000000	26.000000	25.000000	...	25.000000	26.000000	25.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0

8 rows × 22 columns

#visualize
df.boxplot()

Prepare data

#select only races that happened
df2=df.iloc[:,:-7]

df2.boxplot()

df2.head(3)

	Coureur	BHR	EMI	POR	SPA	MON	AZE	FRA	STI	OOS	GBR	HON	BEL	NED	ITA	RUS
0	Hamilton	25	19	25	25	7	0	18	19	12	25	18	7.5	19	0	25
1	Verstappen	18	25	18	19	25	0	26	25	26	0	2	12.5	25	0	18
2	Bottas	16	0	16	15	0	0	12	15	18	15	0	0.0	15	15	10

#For plotting easiest is to set coureur as index
df2 = df2.set_index('Coureur')

df2.head(3)

	BHR	EMI	POR	SPA	MON	AZE	FRA	STI	OOS	GBR	HON	BEL	NED	ITA	RUS
Coureur
Hamilton	25	19	25	25	7	0	18	19	12	25	18	7.5	19	0	25
Verstappen	18	25	18	19	25	0	26	25	26	0	2	12.5	25	0	18
Bottas	16	0	16	15	0	0	12	15	18	15	0	0.0	15	15	10

# Create cummulative dataframe in columns direction
df_cum = df2.cumsum(axis = 1)
#select only top 10
df_cum = df_cum.nlargest(10, 'RUS')

Plot Data

#Plot the cummulative numbers
#Plot by index, not by column -> df_cum.T
df_cum.T.plot(title = 'top 10 F1 coureurs', ylabel = 'points')