Informations sur les ressources :

Temps de génération : 77 secondes

Utilisation CPU : [55.1, 59.4, 54.2, 59.3] %

Utilisation mémoire : 12870 Go

Processeur : 3201.0 MHz

Informations sur le DataFrame ( df.info() ):

RangeIndex: 50 entries, 0 to 49
Data columns (total 6 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 tconst 50 non-null object
1 ordering 50 non-null int64
2 nconst 50 non-null object
3 category 50 non-null object
4 job 50 non-null object
5 characters 50 non-null object
dtypes: int64(1), object(5)
memory usage: 2.5+ KB

Noms des colonnes ( df.columns ) :

tconst, ordering, nconst, category, job, characters

Types de données des colonnes ( df.dtypes ):

tconst	object
ordering	int64
nconst	object
category	object
job	object
characters	object

Statistiques descriptives pour les colonnes numériques ( df.describe() ):

count	50.000000
mean	2.480000
std	1.631826
min	1.000000
25%	1.000000
50%	2.000000
75%	3.000000
max	8.000000

Valeurs manquantes dans le Dataframe ( df.isnull().sum() ) :

tconst	0
ordering	0
nconst	0
category	0
job	0
characters	0

19 premières lignes :

tconst	ordering	nconst	category	job	characters
tt0000001	1	nm1588970	self	\N	["Self"]
tt0000001	2	nm0005690	director	\N	\N
tt0000001	3	nm0374658	cinematographer	director of photography	\N
tt0000002	1	nm0721526	director	\N	\N
tt0000002	2	nm1335271	composer	\N	\N
tt0000003	1	nm0721526	director	\N	\N
tt0000003	2	nm1770680	producer	producer	\N
tt0000003	3	nm1335271	composer	\N	\N
tt0000003	4	nm5442200	editor	\N	\N
tt0000004	1	nm0721526	director	\N	\N
tt0000004	2	nm1335271	composer	\N	\N
tt0000005	1	nm0443482	actor	\N	["Blacksmith"]
tt0000005	2	nm0653042	actor	\N	["Assistant"]
tt0000005	3	nm0005690	director	\N	\N
tt0000005	4	nm0249379	producer	producer	\N
tt0000006	1	nm0005690	director	\N	\N
tt0000007	1	nm0179163	actor	\N	\N
tt0000007	2	nm0183947	actor	\N	\N
tt0000007	3	nm0005690	director	\N	\N

20 lignes au hasard :

tconst	ordering	nconst	category	job	characters
tt0000008	3	nm0374658	cinematographer	\N	\N
tt0000012	1	nm2880396	self	\N	["Self"]
tt0000008	2	nm0005690	director	\N	\N
tt0000010	1	nm0525910	director	\N	\N
tt0000009	1	nm0063086	actress	\N	["Miss Geraldine Holbrook (Miss Jerry)"]
tt0000006	1	nm0005690	director	\N	\N
tt0000003	3	nm1335271	composer	\N	\N
tt0000016	2	nm9735581	self	\N	["Self (on the pier)"]
tt0000007	4	nm0374658	director	\N	\N
tt0000012	3	nm0525900	self	\N	["Self"]
tt0000013	3	nm0525910	director	\N	\N
tt0000012	2	nm9735580	self	\N	["Self"]
tt0000013	2	nm1715062	self	\N	["Self"]
tt0000007	3	nm0005690	director	\N	\N
tt0000017	1	nm3691272	actor	\N	["The boy"]
tt0000003	1	nm0721526	director	\N	\N
tt0000013	1	nm0525908	self	\N	["Self"]
tt0000011	2	nm0804434	director	\N	\N
tt0000002	2	nm1335271	composer	\N	\N
tt0000009	3	nm1309758	actor	\N	["Chauncey Depew - the Director of the New York Central Railroad"]

21 dernières lignes :

tconst	ordering	nconst	category	job	characters
tt0000011	1	nm3692297	actor	\N	["Acrobats"]
tt0000011	2	nm0804434	director	\N	\N
tt0000012	1	nm2880396	self	\N	["Self"]
tt0000012	2	nm9735580	self	\N	["Self"]
tt0000012	3	nm0525900	self	\N	["Self"]
tt0000012	4	nm9735581	self	\N	["Self"]
tt0000012	5	nm0525908	director	\N	\N
tt0000012	6	nm0525910	director	\N	\N
tt0000012	7	nm9735579	self	\N	["Self"]
tt0000012	8	nm9653419	self	\N	["Self"]
tt0000013	1	nm0525908	self	\N	["Self"]
tt0000013	2	nm1715062	self	\N	["Self"]
tt0000013	3	nm0525910	director	\N	\N
tt0000014	1	nm0166380	actor	\N	["The Gardener"]
tt0000014	2	nm0244989	actor	\N	["The Boy"]
tt0000014	3	nm0525910	director	\N	\N
tt0000015	1	nm0721526	director	\N	\N
tt0000016	1	nm0525900	self	\N	["Self (on the pier)"]
tt0000016	2	nm9735581	self	\N	["Self (on the pier)"]
tt0000016	3	nm0525910	director	\N	\N
tt0000017	1	nm3691272	actor	\N	["The boy"]