Overview

Brought to you by YData

Dataset statistics

Number of variables 12
Number of observations 6234
Missing cells 3036
Missing cells (%) 4.1%
Duplicate rows 0
Duplicate rows (%) 0.0%
Total size in memory 5.5 MiB
Average record size in memory 918.0 B

Variable types

Numeric 2
Categorical 2
Text 7
DateTime 1

Alerts

release_year is highly overall correlated with show_id High correlation
show_id is highly overall correlated with release_year High correlation
director has 1969 (31.6%) missing values Missing
cast has 570 (9.1%) missing values Missing
country has 476 (7.6%) missing values Missing
show_id has unique values Unique

Reproduction

Analysis started 2025-08-20 15:03:34.854121
Analysis finished 2025-08-20 15:03:35.477890
Duration 0.62 seconds
Software version ydata-profiling vv4.16.1
Download configuration config.json

Variables

show_id
Real number (ℝ)

High correlation  Unique 

Distinct 6234
Distinct (%) 100.0%
Missing 0
Missing (%) 0.0%
Infinite 0
Infinite (%) 0.0%
Mean 76703679
Minimum 247747
Maximum 81235729
Zeros 0
Zeros (%) 0.0%
Negative 0
Negative (%) 0.0%
Memory size 48.8 KiB
2025-08-20T12:03:35.498800 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum 247747
5-th percentile 70000159
Q1 80035802
median 80163367
Q3 80244889
95-th percentile 81121182
Maximum 81235729
Range 80987982
Interquartile range (IQR) 209087

Descriptive statistics

Standard deviation 10942965
Coefficient of variation (CV) 0.14266545
Kurtosis 30.33529
Mean 76703679
Median Absolute Deviation (MAD) 125119.5
Skewness -5.1508927
Sum 4.7817074 × 1011
Variance 1.1974848 × 1014
Monotonicity Not monotonic
2025-08-20T12:03:35.530508 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Value Count Frequency (%)
81145628 1
 
< 0.1%
81019391 1
 
< 0.1%
81135440 1
 
< 0.1%
81188871 1
 
< 0.1%
80004478 1
 
< 0.1%
80104103 1
 
< 0.1%
80187435 1
 
< 0.1%
80204730 1
 
< 0.1%
80211229 1
 
< 0.1%
80244190 1
 
< 0.1%
Other values (6224) 6224
99.8%
Value Count Frequency (%)
247747 1
< 0.1%
269880 1
< 0.1%
281550 1
< 0.1%
284890 1
< 0.1%
292118 1
< 0.1%
296682 1
< 0.1%
347365 1
< 0.1%
352989 1
< 0.1%
372195 1
< 0.1%
374651 1
< 0.1%
Value Count Frequency (%)
81235729 1
< 0.1%
81235603 1
< 0.1%
81228864 1
< 0.1%
81227195 1
< 0.1%
81224868 1
< 0.1%
81224839 1
< 0.1%
81224811 1
< 0.1%
81224128 1
< 0.1%
81221914 1
< 0.1%
81221913 1
< 0.1%

type
Categorical

Distinct 2
Distinct (%) < 0.1%
Missing 0
Missing (%) 0.0%
Memory size 332.7 KiB
Movie
4265 
TV Show
1969 

Length

Max length 7
Median length 5
Mean length 5.6316971
Min length 5

Characters and Unicode

Total characters 35108
Distinct characters 11
Distinct categories 1 ?
Distinct scripts 1 ?
Distinct blocks 1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique 0 ?
Unique (%) 0.0%

Sample

1st row Movie
2nd row Movie
3rd row TV Show
4th row TV Show
5th row Movie

Common Values

Value Count Frequency (%)
Movie 4265
68.4%
TV Show 1969
31.6%

Length

2025-08-20T12:03:35.559332 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-08-20T12:03:35.574144 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/
Value Count Frequency (%)
movie 4265
52.0%
tv 1969
24.0%
show 1969
24.0%

Most occurring characters

Value Count Frequency (%)
o 6234
17.8%
M 4265
12.1%
v 4265
12.1%
i 4265
12.1%
e 4265
12.1%
T 1969
 
5.6%
V 1969
 
5.6%
1969
 
5.6%
S 1969
 
5.6%
h 1969
 
5.6%

Most occurring categories

Value Count Frequency (%)
(unknown) 35108
100.0%

Most frequent character per category

(unknown)
Value Count Frequency (%)
o 6234
17.8%
M 4265
12.1%
v 4265
12.1%
i 4265
12.1%
e 4265
12.1%
T 1969
 
5.6%
V 1969
 
5.6%
1969
 
5.6%
S 1969
 
5.6%
h 1969
 
5.6%

Most occurring scripts

Value Count Frequency (%)
(unknown) 35108
100.0%

Most frequent character per script

(unknown)
Value Count Frequency (%)
o 6234
17.8%
M 4265
12.1%
v 4265
12.1%
i 4265
12.1%
e 4265
12.1%
T 1969
 
5.6%
V 1969
 
5.6%
1969
 
5.6%
S 1969
 
5.6%
h 1969
 
5.6%

Most occurring blocks

Value Count Frequency (%)
(unknown) 35108
100.0%

Most frequent character per block

(unknown)
Value Count Frequency (%)
o 6234
17.8%
M 4265
12.1%
v 4265
12.1%
i 4265
12.1%
e 4265
12.1%
T 1969
 
5.6%
V 1969
 
5.6%
1969
 
5.6%
S 1969
 
5.6%
h 1969
 
5.6%

title
Text

Distinct 6172
Distinct (%) 99.0%
Missing 0
Missing (%) 0.0%
Memory size 413.0 KiB
2025-08-20T12:03:35.662276 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/

Length

Max length 104
Median length 65
Mean length 17.504812
Min length 1

Characters and Unicode

Total characters 109125
Distinct characters 187
Distinct categories 1 ?
Distinct scripts 1 ?
Distinct blocks 1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique 6115 ?
Unique (%) 98.1%

Sample

1st row Norm of the North: King Sized Adventure
2nd row Jandino: Whatever it Takes
3rd row Transformers Prime
4th row Transformers: Robots in Disguise
5th row #realityhigh
Value Count Frequency (%)
the 1502
 
7.9%
of 496
 
2.6%
a 225
 
1.2%
in 183
 
1.0%
and 172
 
0.9%
151
 
0.8%
to 122
 
0.6%
love 114
 
0.6%
my 107
 
0.6%
2 88
 
0.5%
Other values (7221) 15906
83.4%
2025-08-20T12:03:35.791046 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

Value Count Frequency (%)
12832
 
11.8%
e 10149
 
9.3%
a 7896
 
7.2%
o 6148
 
5.6%
i 6078
 
5.6%
r 5844
 
5.4%
n 5751
 
5.3%
t 4974
 
4.6%
s 4363
 
4.0%
h 3755
 
3.4%
Other values (177) 41335
37.9%

Most occurring categories

Value Count Frequency (%)
(unknown) 109125
100.0%

Most frequent character per category

(unknown)
Value Count Frequency (%)
12832
 
11.8%
e 10149
 
9.3%
a 7896
 
7.2%
o 6148
 
5.6%
i 6078
 
5.6%
r 5844
 
5.4%
n 5751
 
5.3%
t 4974
 
4.6%
s 4363
 
4.0%
h 3755
 
3.4%
Other values (177) 41335
37.9%

Most occurring scripts

Value Count Frequency (%)
(unknown) 109125
100.0%

Most frequent character per script

(unknown)
Value Count Frequency (%)
12832
 
11.8%
e 10149
 
9.3%
a 7896
 
7.2%
o 6148
 
5.6%
i 6078
 
5.6%
r 5844
 
5.4%
n 5751
 
5.3%
t 4974
 
4.6%
s 4363
 
4.0%
h 3755
 
3.4%
Other values (177) 41335
37.9%

Most occurring blocks

Value Count Frequency (%)
(unknown) 109125
100.0%

Most frequent character per block

(unknown)
Value Count Frequency (%)
12832
 
11.8%
e 10149
 
9.3%
a 7896
 
7.2%
o 6148
 
5.6%
i 6078
 
5.6%
r 5844
 
5.4%
n 5751
 
5.3%
t 4974
 
4.6%
s 4363
 
4.0%
h 3755
 
3.4%
Other values (177) 41335
37.9%

director
Text

Missing 

Distinct 3301
Distinct (%) 77.4%
Missing 1969
Missing (%) 31.6%
Memory size 339.5 KiB
2025-08-20T12:03:35.884238 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/

Length

Max length 208
Median length 167
Mean length 15.448535
Min length 3

Characters and Unicode

Total characters 65888
Distinct characters 96
Distinct categories 1 ?
Distinct scripts 1 ?
Distinct blocks 1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique 2752 ?
Unique (%) 64.5%

Sample

1st row Richard Finn, Tim Maltby
2nd row Fernando Lebrija
3rd row Gabe Ibáñez
4th row Rodrigo Toro, Francisco Schultz
5th row Henrik Ruben Genz
Value Count Frequency (%)
david 90
 
0.9%
michael 82
 
0.8%
john 76
 
0.7%
paul 47
 
0.5%
robert 40
 
0.4%
jay 38
 
0.4%
chris 36
 
0.4%
mike 33
 
0.3%
smith 33
 
0.3%
daniel 32
 
0.3%
Other values (4937) 9726
95.0%
2025-08-20T12:03:36.015030 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

Value Count Frequency (%)
a 6991
 
10.6%
5968
 
9.1%
e 4897
 
7.4%
n 4366
 
6.6%
i 4040
 
6.1%
r 3963
 
6.0%
o 3380
 
5.1%
l 2661
 
4.0%
h 2305
 
3.5%
s 2096
 
3.2%
Other values (86) 25221
38.3%

Most occurring categories

Value Count Frequency (%)
(unknown) 65888
100.0%

Most frequent character per category

(unknown)
Value Count Frequency (%)
a 6991
 
10.6%
5968
 
9.1%
e 4897
 
7.4%
n 4366
 
6.6%
i 4040
 
6.1%
r 3963
 
6.0%
o 3380
 
5.1%
l 2661
 
4.0%
h 2305
 
3.5%
s 2096
 
3.2%
Other values (86) 25221
38.3%

Most occurring scripts

Value Count Frequency (%)
(unknown) 65888
100.0%

Most frequent character per script

(unknown)
Value Count Frequency (%)
a 6991
 
10.6%
5968
 
9.1%
e 4897
 
7.4%
n 4366
 
6.6%
i 4040
 
6.1%
r 3963
 
6.0%
o 3380
 
5.1%
l 2661
 
4.0%
h 2305
 
3.5%
s 2096
 
3.2%
Other values (86) 25221
38.3%

Most occurring blocks

Value Count Frequency (%)
(unknown) 65888
100.0%

Most frequent character per block

(unknown)
Value Count Frequency (%)
a 6991
 
10.6%
5968
 
9.1%
e 4897
 
7.4%
n 4366
 
6.6%
i 4040
 
6.1%
r 3963
 
6.0%
o 3380
 
5.1%
l 2661
 
4.0%
h 2305
 
3.5%
s 2096
 
3.2%
Other values (86) 25221
38.3%

cast
Text

Missing 

Distinct 5469
Distinct (%) 96.6%
Missing 570
Missing (%) 9.1%
Memory size 1.1 MiB
2025-08-20T12:03:36.116782 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/

Length

Max length 771
Median length 311
Mean length 116.25282
Min length 4

Characters and Unicode

Total characters 658456
Distinct characters 139
Distinct categories 1 ?
Distinct scripts 1 ?
Distinct blocks 1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique 5358 ?
Unique (%) 94.6%

Sample

1st row Alan Marriott, Andrew Toth, Brian Dobson, Cole Howard, Jennifer Cameron, Jonathan Holmes, Lee Tockar, Lisa Durupt, Maya Kay, Michael Dobson
2nd row Jandino Asporaat
3rd row Peter Cullen, Sumalee Montano, Frank Welker, Jeffrey Combs, Kevin Michael Richardson, Tania Gunadi, Josh Keaton, Steve Blum, Andy Pessoa, Ernie Hudson, Daran Norris, Will Friedle
4th row Will Friedle, Darren Criss, Constance Zimmer, Khary Payton, Mitchell Whitfield, Stuart Allan, Ted McGinley, Peter Cullen
5th row Nesta Cooper, Kate Walsh, John Michael Higgins, Keith Powers, Alicia Sanz, Jake Borelli, Kid Ink, Yousef Erakat, Rebekah Graf, Anne Winters, Peter Gilroy, Patrick Davis
Value Count Frequency (%)
michael 459
 
0.5%
john 405
 
0.4%
david 394
 
0.4%
lee 333
 
0.4%
james 286
 
0.3%
paul 246
 
0.3%
kim 229
 
0.3%
khan 216
 
0.2%
de 190
 
0.2%
kapoor 189
 
0.2%
Other values (26089) 88189
96.8%
2025-08-20T12:03:36.299609 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

Value Count Frequency (%)
85475
 
13.0%
a 65499
 
9.9%
e 45346
 
6.9%
n 40270
 
6.1%
, 38647
 
5.9%
i 38608
 
5.9%
r 33798
 
5.1%
o 30210
 
4.6%
l 24312
 
3.7%
h 20039
 
3.0%
Other values (129) 236252
35.9%

Most occurring categories

Value Count Frequency (%)
(unknown) 658456
100.0%

Most frequent character per category

(unknown)
Value Count Frequency (%)
85475
 
13.0%
a 65499
 
9.9%
e 45346
 
6.9%
n 40270
 
6.1%
, 38647
 
5.9%
i 38608
 
5.9%
r 33798
 
5.1%
o 30210
 
4.6%
l 24312
 
3.7%
h 20039
 
3.0%
Other values (129) 236252
35.9%

Most occurring scripts

Value Count Frequency (%)
(unknown) 658456
100.0%

Most frequent character per script

(unknown)
Value Count Frequency (%)
85475
 
13.0%
a 65499
 
9.9%
e 45346
 
6.9%
n 40270
 
6.1%
, 38647
 
5.9%
i 38608
 
5.9%
r 33798
 
5.1%
o 30210
 
4.6%
l 24312
 
3.7%
h 20039
 
3.0%
Other values (129) 236252
35.9%

Most occurring blocks

Value Count Frequency (%)
(unknown) 658456
100.0%

Most frequent character per block

(unknown)
Value Count Frequency (%)
85475
 
13.0%
a 65499
 
9.9%
e 45346
 
6.9%
n 40270
 
6.1%
, 38647
 
5.9%
i 38608
 
5.9%
r 33798
 
5.1%
o 30210
 
4.6%
l 24312
 
3.7%
h 20039
 
3.0%
Other values (129) 236252
35.9%

country
Text

Missing 

Distinct 554
Distinct (%) 9.6%
Missing 476
Missing (%) 7.6%
Memory size 360.4 KiB
2025-08-20T12:03:36.361298 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/

Length

Max length 123
Median length 104
Mean length 12.41629
Min length 4

Characters and Unicode

Total characters 71493
Distinct characters 51
Distinct categories 1 ?
Distinct scripts 1 ?
Distinct blocks 1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique 408 ?
Unique (%) 7.1%

Sample

1st row United States, India, South Korea, China
2nd row United Kingdom
3rd row United States
4th row United States
5th row United States
Value Count Frequency (%)
united 3233
30.0%
states 2610
24.2%
india 838
 
7.8%
kingdom 602
 
5.6%
canada 318
 
3.0%
france 271
 
2.5%
japan 231
 
2.1%
south 192
 
1.8%
spain 178
 
1.7%
korea 162
 
1.5%
Other values (111) 2141
19.9%
2025-08-20T12:03:36.458896 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

Value Count Frequency (%)
t 9107
12.7%
e 7432
10.4%
a 7287
10.2%
n 6932
9.7%
i 6153
8.6%
d 5301
 
7.4%
5018
 
7.0%
U 3249
 
4.5%
S 3079
 
4.3%
s 3032
 
4.2%
Other values (41) 14903
20.8%

Most occurring categories

Value Count Frequency (%)
(unknown) 71493
100.0%

Most frequent character per category

(unknown)
Value Count Frequency (%)
t 9107
12.7%
e 7432
10.4%
a 7287
10.2%
n 6932
9.7%
i 6153
8.6%
d 5301
 
7.4%
5018
 
7.0%
U 3249
 
4.5%
S 3079
 
4.3%
s 3032
 
4.2%
Other values (41) 14903
20.8%

Most occurring scripts

Value Count Frequency (%)
(unknown) 71493
100.0%

Most frequent character per script

(unknown)
Value Count Frequency (%)
t 9107
12.7%
e 7432
10.4%
a 7287
10.2%
n 6932
9.7%
i 6153
8.6%
d 5301
 
7.4%
5018
 
7.0%
U 3249
 
4.5%
S 3079
 
4.3%
s 3032
 
4.2%
Other values (41) 14903
20.8%

Most occurring blocks

Value Count Frequency (%)
(unknown) 71493
100.0%

Most frequent character per block

(unknown)
Value Count Frequency (%)
t 9107
12.7%
e 7432
10.4%
a 7287
10.2%
n 6932
9.7%
i 6153
8.6%
d 5301
 
7.4%
5018
 
7.0%
U 3249
 
4.5%
S 3079
 
4.3%
s 3032
 
4.2%
Other values (41) 14903
20.8%

date_added
Date

Distinct 1189
Distinct (%) 19.1%
Missing 11
Missing (%) 0.2%
Memory size 48.8 KiB
Minimum 2008-01-01 00:00:00
Maximum 2020-01-18 00:00:00
Invalid dates 0
Invalid dates (%) 0.0%
2025-08-20T12:03:36.485544 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/
2025-08-20T12:03:36.519401 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

release_year
Real number (ℝ)

High correlation 

Distinct 72
Distinct (%) 1.2%
Missing 0
Missing (%) 0.0%
Infinite 0
Infinite (%) 0.0%
Mean 2013.3593
Minimum 1925
Maximum 2020
Zeros 0
Zeros (%) 0.0%
Negative 0
Negative (%) 0.0%
Memory size 48.8 KiB
2025-08-20T12:03:36.551797 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum 1925
5-th percentile 1997
Q1 2013
median 2016
Q3 2018
95-th percentile 2019
Maximum 2020
Range 95
Interquartile range (IQR) 5

Descriptive statistics

Standard deviation 8.8116204
Coefficient of variation (CV) 0.0043765761
Kurtosis 18.317374
Mean 2013.3593
Median Absolute Deviation (MAD) 2
Skewness -3.7047455
Sum 12551282
Variance 77.644653
Monotonicity Not monotonic
2025-08-20T12:03:36.579051 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Value Count Frequency (%)
2018 1063
17.1%
2017 959
15.4%
2019 843
13.5%
2016 830
13.3%
2015 517
8.3%
2014 288
 
4.6%
2013 237
 
3.8%
2012 183
 
2.9%
2010 149
 
2.4%
2011 136
 
2.2%
Other values (62) 1029
16.5%
Value Count Frequency (%)
1925 1
 
< 0.1%
1942 2
< 0.1%
1943 3
< 0.1%
1944 3
< 0.1%
1945 3
< 0.1%
1946 3
< 0.1%
1947 1
 
< 0.1%
1954 1
 
< 0.1%
1955 1
 
< 0.1%
1956 1
 
< 0.1%
Value Count Frequency (%)
2020 25
 
0.4%
2019 843
13.5%
2018 1063
17.1%
2017 959
15.4%
2016 830
13.3%
2015 517
8.3%
2014 288
 
4.6%
2013 237
 
3.8%
2012 183
 
2.9%
2011 136
 
2.2%

rating
Categorical

Distinct 14
Distinct (%) 0.2%
Missing 10
Missing (%) 0.2%
Memory size 325.6 KiB
TV-MA
2027 
TV-14
1698 
TV-PG
701 
R
508 
PG-13
286 
Other values (9)
1004 

Length

Max length 8
Median length 5
Mean length 4.4514781
Min length 1

Characters and Unicode

Total characters 27706
Distinct characters 17
Distinct categories 1 ?
Distinct scripts 1 ?
Distinct blocks 1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique 0 ?
Unique (%) 0.0%

Sample

1st row TV-PG
2nd row TV-MA
3rd row TV-Y7-FV
4th row TV-Y7
5th row TV-14

Common Values

Value Count Frequency (%)
TV-MA 2027
32.5%
TV-14 1698
27.2%
TV-PG 701
 
11.2%
R 508
 
8.1%
PG-13 286
 
4.6%
NR 218
 
3.5%
PG 184
 
3.0%
TV-Y7 169
 
2.7%
TV-G 149
 
2.4%
TV-Y 143
 
2.3%
Other values (4) 141
 
2.3%

Length

2025-08-20T12:03:36.604561 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
Value Count Frequency (%)
tv-ma 2027
32.6%
tv-14 1698
27.3%
tv-pg 701
 
11.3%
r 508
 
8.2%
pg-13 286
 
4.6%
nr 218
 
3.5%
pg 184
 
3.0%
tv-y7 169
 
2.7%
tv-g 149
 
2.4%
tv-y 143
 
2.3%
Other values (4) 141
 
2.3%

Most occurring characters

Value Count Frequency (%)
- 5365
19.4%
V 5077
18.3%
T 4982
18.0%
M 2027
 
7.3%
A 2027
 
7.3%
1 1986
 
7.2%
4 1698
 
6.1%
G 1357
 
4.9%
P 1171
 
4.2%
R 733
 
2.6%
Other values (7) 1283
 
4.6%

Most occurring categories

Value Count Frequency (%)
(unknown) 27706
100.0%

Most frequent character per category

(unknown)
Value Count Frequency (%)
- 5365
19.4%
V 5077
18.3%
T 4982
18.0%
M 2027
 
7.3%
A 2027
 
7.3%
1 1986
 
7.2%
4 1698
 
6.1%
G 1357
 
4.9%
P 1171
 
4.2%
R 733
 
2.6%
Other values (7) 1283
 
4.6%

Most occurring scripts

Value Count Frequency (%)
(unknown) 27706
100.0%

Most frequent character per script

(unknown)
Value Count Frequency (%)
- 5365
19.4%
V 5077
18.3%
T 4982
18.0%
M 2027
 
7.3%
A 2027
 
7.3%
1 1986
 
7.2%
4 1698
 
6.1%
G 1357
 
4.9%
P 1171
 
4.2%
R 733
 
2.6%
Other values (7) 1283
 
4.6%

Most occurring blocks

Value Count Frequency (%)
(unknown) 27706
100.0%

Most frequent character per block

(unknown)
Value Count Frequency (%)
- 5365
19.4%
V 5077
18.3%
T 4982
18.0%
M 2027
 
7.3%
A 2027
 
7.3%
1 1986
 
7.2%
4 1698
 
6.1%
G 1357
 
4.9%
P 1171
 
4.2%
R 733
 
2.6%
Other values (7) 1283
 
4.6%

duration
Text

Distinct 201
Distinct (%) 3.2%
Missing 0
Missing (%) 0.0%
Memory size 341.4 KiB
2025-08-20T12:03:36.684203 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/

Length

Max length 10
Median length 9
Mean length 7.0527751
Min length 5

Characters and Unicode

Total characters 43967
Distinct characters 19
Distinct categories 1 ?
Distinct scripts 1 ?
Distinct blocks 1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique 35 ?
Unique (%) 0.6%

Sample

1st row 90 min
2nd row 94 min
3rd row 1 Season
4th row 1 Season
5th row 99 min
Value Count Frequency (%)
min 4265
34.2%
1 1321
 
10.6%
season 1321
 
10.6%
seasons 648
 
5.2%
2 304
 
2.4%
3 159
 
1.3%
90 111
 
0.9%
91 104
 
0.8%
92 101
 
0.8%
94 94
 
0.8%
Other values (188) 4040
32.4%
2025-08-20T12:03:36.789133 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

Value Count Frequency (%)
n 6234
14.2%
6234
14.2%
m 4265
9.7%
i 4265
9.7%
1 4165
9.5%
s 2617
 
6.0%
S 1969
 
4.5%
e 1969
 
4.5%
a 1969
 
4.5%
o 1969
 
4.5%
Other values (9) 8311
18.9%

Most occurring categories

Value Count Frequency (%)
(unknown) 43967
100.0%

Most frequent character per category

(unknown)
Value Count Frequency (%)
n 6234
14.2%
6234
14.2%
m 4265
9.7%
i 4265
9.7%
1 4165
9.5%
s 2617
 
6.0%
S 1969
 
4.5%
e 1969
 
4.5%
a 1969
 
4.5%
o 1969
 
4.5%
Other values (9) 8311
18.9%

Most occurring scripts

Value Count Frequency (%)
(unknown) 43967
100.0%

Most frequent character per script

(unknown)
Value Count Frequency (%)
n 6234
14.2%
6234
14.2%
m 4265
9.7%
i 4265
9.7%
1 4165
9.5%
s 2617
 
6.0%
S 1969
 
4.5%
e 1969
 
4.5%
a 1969
 
4.5%
o 1969
 
4.5%
Other values (9) 8311
18.9%

Most occurring blocks

Value Count Frequency (%)
(unknown) 43967
100.0%

Most frequent character per block

(unknown)
Value Count Frequency (%)
n 6234
14.2%
6234
14.2%
m 4265
9.7%
i 4265
9.7%
1 4165
9.5%
s 2617
 
6.0%
S 1969
 
4.5%
e 1969
 
4.5%
a 1969
 
4.5%
o 1969
 
4.5%
Other values (9) 8311
18.9%

listed_in
Text

Distinct 461
Distinct (%) 7.4%
Missing 0
Missing (%) 0.0%
Memory size 502.2 KiB
2025-08-20T12:03:36.847326 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/

Length

Max length 79
Median length 59
Mean length 33.465512
Min length 6

Characters and Unicode

Total characters 208624
Distinct characters 43
Distinct categories 1 ?
Distinct scripts 1 ?
Distinct blocks 1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique 136 ?
Unique (%) 2.2%

Sample

1st row Children & Family Movies, Comedies
2nd row Stand-Up Comedy
3rd row Kids' TV
4th row Kids' TV
5th row Comedies
Value Count Frequency (%)
tv 4123
14.8%
movies 3907
14.0%
international 2928
10.5%
dramas 2222
 
8.0%
shows 2197
 
7.9%
1785
 
6.4%
comedies 1549
 
5.6%
adventure 723
 
2.6%
action 723
 
2.6%
documentaries 668
 
2.4%
Other values (33) 7061
25.3%
2025-08-20T12:03:36.939879 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

Value Count Frequency (%)
21652
 
10.4%
e 17744
 
8.5%
i 15000
 
7.2%
n 14809
 
7.1%
o 14149
 
6.8%
a 14080
 
6.7%
s 13855
 
6.6%
t 10681
 
5.1%
r 10225
 
4.9%
, 7436
 
3.6%
Other values (33) 68993
33.1%

Most occurring categories

Value Count Frequency (%)
(unknown) 208624
100.0%

Most frequent character per category

(unknown)
Value Count Frequency (%)
21652
 
10.4%
e 17744
 
8.5%
i 15000
 
7.2%
n 14809
 
7.1%
o 14149
 
6.8%
a 14080
 
6.7%
s 13855
 
6.6%
t 10681
 
5.1%
r 10225
 
4.9%
, 7436
 
3.6%
Other values (33) 68993
33.1%

Most occurring scripts

Value Count Frequency (%)
(unknown) 208624
100.0%

Most frequent character per script

(unknown)
Value Count Frequency (%)
21652
 
10.4%
e 17744
 
8.5%
i 15000
 
7.2%
n 14809
 
7.1%
o 14149
 
6.8%
a 14080
 
6.7%
s 13855
 
6.6%
t 10681
 
5.1%
r 10225
 
4.9%
, 7436
 
3.6%
Other values (33) 68993
33.1%

Most occurring blocks

Value Count Frequency (%)
(unknown) 208624
100.0%

Most frequent character per block

(unknown)
Value Count Frequency (%)
21652
 
10.4%
e 17744
 
8.5%
i 15000
 
7.2%
n 14809
 
7.1%
o 14149
 
6.8%
a 14080
 
6.7%
s 13855
 
6.6%
t 10681
 
5.1%
r 10225
 
4.9%
, 7436
 
3.6%
Other values (33) 68993
33.1%

description
Text

Distinct 6226
Distinct (%) 99.9%
Missing 0
Missing (%) 0.0%
Memory size 1.4 MiB
2025-08-20T12:03:37.037586 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/

Length

Max length 248
Median length 240
Mean length 142.88515
Min length 82

Characters and Unicode

Total characters 890746
Distinct characters 115
Distinct categories 1 ?
Distinct scripts 1 ?
Distinct blocks 1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique 6219 ?
Unique (%) 99.8%

Sample

1st row Before planning an awesome wedding for his grandfather, a polar bear king must take back a stolen artifact from an evil archaeologist first.
2nd row Jandino Asporaat riffs on the challenges of raising kids and serenades the audience with a rousing rendition of "Sex on Fire" in his comedy show.
3rd row With the help of three human allies, the Autobots once again protect Earth from the onslaught of the Decepticons and their leader, Megatron.
4th row When a prison ship crash unleashes hundreds of Decepticons on Earth, Bumblebee leads a new Autobot force to protect humankind.
5th row When nerdy high schooler Dani finally attracts the interest of her longtime crush, she lands in the cross hairs of his ex, a social media celebrity.
Value Count Frequency (%)
a 7968
 
5.4%
the 5864
 
4.0%
to 4509
 
3.0%
and 4467
 
3.0%
of 3864
 
2.6%
in 3128
 
2.1%
his 2341
 
1.6%
with 1553
 
1.0%
her 1460
 
1.0%
an 1365
 
0.9%
Other values (18097) 111762
75.4%
2025-08-20T12:03:37.169999 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

Value Count Frequency (%)
142050
15.9%
e 83599
 
9.4%
a 59751
 
6.7%
t 57351
 
6.4%
i 55533
 
6.2%
n 52758
 
5.9%
o 51397
 
5.8%
s 51046
 
5.7%
r 49659
 
5.6%
h 34313
 
3.9%
Other values (105) 253289
28.4%

Most occurring categories

Value Count Frequency (%)
(unknown) 890746
100.0%

Most frequent character per category

(unknown)
Value Count Frequency (%)
142050
15.9%
e 83599
 
9.4%
a 59751
 
6.7%
t 57351
 
6.4%
i 55533
 
6.2%
n 52758
 
5.9%
o 51397
 
5.8%
s 51046
 
5.7%
r 49659
 
5.6%
h 34313
 
3.9%
Other values (105) 253289
28.4%

Most occurring scripts

Value Count Frequency (%)
(unknown) 890746
100.0%

Most frequent character per script

(unknown)
Value Count Frequency (%)
142050
15.9%
e 83599
 
9.4%
a 59751
 
6.7%
t 57351
 
6.4%
i 55533
 
6.2%
n 52758
 
5.9%
o 51397
 
5.8%
s 51046
 
5.7%
r 49659
 
5.6%
h 34313
 
3.9%
Other values (105) 253289
28.4%

Most occurring blocks

Value Count Frequency (%)
(unknown) 890746
100.0%

Most frequent character per block

(unknown)
Value Count Frequency (%)
142050
15.9%
e 83599
 
9.4%
a 59751
 
6.7%
t 57351
 
6.4%
i 55533
 
6.2%
n 52758
 
5.9%
o 51397
 
5.8%
s 51046
 
5.7%
r 49659
 
5.6%
h 34313
 
3.9%
Other values (105) 253289
28.4%

Interactions

2025-08-20T12:03:35.336643 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/
2025-08-20T12:03:35.286963 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/
2025-08-20T12:03:35.361360 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/
2025-08-20T12:03:35.313661 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-08-20T12:03:37.189103 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/
rating release_year show_id type
rating 1.000 0.139 0.208 0.362
release_year 0.139 1.000 0.664 0.156
show_id 0.208 0.664 1.000 0.172
type 0.362 0.156 0.172 1.000

Missing values

2025-08-20T12:03:35.394814 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-08-20T12:03:35.424088 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-08-20T12:03:35.457767 image/svg+xml Matplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

show_id type title director cast country date_added release_year rating duration listed_in description
0 81145628 Movie Norm of the North: King Sized Adventure Richard Finn, Tim Maltby Alan Marriott, Andrew Toth, Brian Dobson, Cole Howard, Jennifer Cameron, Jonathan Holmes, Lee Tockar, Lisa Durupt, Maya Kay, Michael Dobson United States, India, South Korea, China September 9, 2019 2019 TV-PG 90 min Children & Family Movies, Comedies Before planning an awesome wedding for his grandfather, a polar bear king must take back a stolen artifact from an evil archaeologist first.
1 80117401 Movie Jandino: Whatever it Takes NaN Jandino Asporaat United Kingdom September 9, 2016 2016 TV-MA 94 min Stand-Up Comedy Jandino Asporaat riffs on the challenges of raising kids and serenades the audience with a rousing rendition of "Sex on Fire" in his comedy show.
2 70234439 TV Show Transformers Prime NaN Peter Cullen, Sumalee Montano, Frank Welker, Jeffrey Combs, Kevin Michael Richardson, Tania Gunadi, Josh Keaton, Steve Blum, Andy Pessoa, Ernie Hudson, Daran Norris, Will Friedle United States September 8, 2018 2013 TV-Y7-FV 1 Season Kids' TV With the help of three human allies, the Autobots once again protect Earth from the onslaught of the Decepticons and their leader, Megatron.
3 80058654 TV Show Transformers: Robots in Disguise NaN Will Friedle, Darren Criss, Constance Zimmer, Khary Payton, Mitchell Whitfield, Stuart Allan, Ted McGinley, Peter Cullen United States September 8, 2018 2016 TV-Y7 1 Season Kids' TV When a prison ship crash unleashes hundreds of Decepticons on Earth, Bumblebee leads a new Autobot force to protect humankind.
4 80125979 Movie #realityhigh Fernando Lebrija Nesta Cooper, Kate Walsh, John Michael Higgins, Keith Powers, Alicia Sanz, Jake Borelli, Kid Ink, Yousef Erakat, Rebekah Graf, Anne Winters, Peter Gilroy, Patrick Davis United States September 8, 2017 2017 TV-14 99 min Comedies When nerdy high schooler Dani finally attracts the interest of her longtime crush, she lands in the cross hairs of his ex, a social media celebrity.
5 80163890 TV Show Apaches NaN Alberto Ammann, Eloy Azorín, Verónica Echegui, Lucía Jiménez, Claudia Traisac Spain September 8, 2017 2016 TV-MA 1 Season Crime TV Shows, International TV Shows, Spanish-Language TV Shows A young journalist is forced into a life of crime to save his father and family in this series based on the novel by Miguel Sáez Carral.
6 70304989 Movie Automata Gabe Ibáñez Antonio Banderas, Dylan McDermott, Melanie Griffith, Birgitte Hjort Sørensen, Robert Forster, Christa Campbell, Tim McInnerny, Andy Nyman, David Ryall Bulgaria, United States, Spain, Canada September 8, 2017 2014 R 110 min International Movies, Sci-Fi & Fantasy, Thrillers In a dystopian future, an insurance adjuster for a tech company investigates a robot killed for violating protocol and discovers a global conspiracy.
7 80164077 Movie Fabrizio Copano: Solo pienso en mi Rodrigo Toro, Francisco Schultz Fabrizio Copano Chile September 8, 2017 2017 TV-MA 60 min Stand-Up Comedy Fabrizio Copano takes audience participation to the next level in this stand-up set while reflecting on sperm banks, family WhatsApp groups and more.
8 80117902 TV Show Fire Chasers NaN NaN United States September 8, 2017 2017 TV-MA 1 Season Docuseries, Science & Nature TV As California's 2016 fire season rages, brave backcountry firefighters race to put out the flames, protect homes and save lives in this docuseries.
9 70304990 Movie Good People Henrik Ruben Genz James Franco, Kate Hudson, Tom Wilkinson, Omar Sy, Sam Spruell, Anna Friel, Thomas Arnold, Oliver Dimsdale, Diana Hardcastle, Michael Jibson, Diarmaid Murtagh United States, United Kingdom, Denmark, Sweden September 8, 2017 2014 R 90 min Action & Adventure, Thrillers A struggling couple can't believe their luck when they find a stash of money in the apartment of a neighbor who was recently murdered.
show_id type title director cast country date_added release_year rating duration listed_in description
6224 70304979 TV Show Anthony Bourdain: Parts Unknown NaN Anthony Bourdain United States NaN 2018 TV-PG 5 Seasons Docuseries This CNN original series has chef Anthony Bourdain traveling to extraordinary locations around the globe to sample a variety of local cuisines.
6225 70153412 TV Show Frasier NaN Kelsey Grammer, Jane Leeves, David Hyde Pierce, Peri Gilpin, John Mahoney, Dan Butler United States NaN 2003 TV-PG 11 Seasons Classic & Cult TV, TV Comedies Frasier Crane is a snooty but lovable Seattle psychiatrist who dispenses advice on his call-in radio show while ignoring it in his own relationships.
6226 70243132 TV Show La Familia P. Luche NaN Eugenio Derbez, Consuelo Duval, Luis Manuel Ávila, Regina Blandón, Miguel Perez, Barbara Torres, Dalilah Polanco, Pierre Angelo United States NaN 2012 TV-14 3 Seasons International TV Shows, Spanish-Language TV Shows, TV Comedies This irreverent sitcom featues Ludovico, Federica and their three children Bibi, Junior and Ludoviquito, living in Ciudad P. Luche.
6227 80005756 TV Show The Adventures of Figaro Pho NaN Luke Jurevicius, Craig Behenna, Charlotte Hamlyn, Stavroula Mountzouris, Aletheia Burney Australia NaN 2015 TV-Y7 2 Seasons Kids' TV, TV Comedies Imagine your worst fears, then multiply them: Figaro is a boy with any number of phobias and a highly quirky and imaginative way of dealing with them.
6228 80159925 TV Show Kikoriki NaN Igor Dmitriev NaN NaN 2010 TV-Y 2 Seasons Kids' TV A wacky rabbit and his gang of animal pals have fun solving problems, sharing stories and exploring their sometimes magical, always special world.
6229 80000063 TV Show Red vs. Blue NaN Burnie Burns, Jason Saldaña, Gustavo Sorola, Geoff Lazer Ramsey, Joel Heyman, Matt Hullum, Dan Godwin, Kathleen Zuelch, Yomary Cruz, Nathan Zellner United States NaN 2015 NR 13 Seasons TV Action & Adventure, TV Comedies, TV Sci-Fi & Fantasy This parody of first-person shooter games, military life and science-fiction films centers on a civil war fought in the middle of a desolate canyon.
6230 70286564 TV Show Maron NaN Marc Maron, Judd Hirsch, Josh Brener, Nora Zehetner, Andy Kindler United States NaN 2016 TV-MA 4 Seasons TV Comedies Marc Maron stars as Marc Maron, who interviews fellow comedians for his popular podcast, only to reveal more about his own neuroses and relationships.
6231 80116008 Movie Little Baby Bum: Nursery Rhyme Friends NaN NaN NaN NaN 2016 NaN 60 min Movies Nursery rhymes and original music for children accompanied by bright, playful animation engage and educate about numbers, shapes, colors and more.
6232 70281022 TV Show A Young Doctor's Notebook and Other Stories NaN Daniel Radcliffe, Jon Hamm, Adam Godley, Christopher Godwin, Rosie Cavaliero, Vicki Pepperdine, Margaret Clunie, Tim Steed, Shaun Pye United Kingdom NaN 2013 TV-MA 2 Seasons British TV Shows, TV Comedies, TV Dramas Set during the Russian Revolution, this comic miniseries is based on a doctor's memories of his early career working in an out-of-the-way village.
6233 70153404 TV Show Friends NaN Jennifer Aniston, Courteney Cox, Lisa Kudrow, Matt LeBlanc, Matthew Perry, David Schwimmer United States NaN 2003 TV-14 10 Seasons Classic & Cult TV, TV Comedies This hit sitcom follows the merry misadventures of six 20-something pals as they navigate the pitfalls of work, life and love in 1990s Manhattan.