Overview

Dataset statistics

Number of variables6
Number of observations865
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory190.1 KiB
Average record size in memory225.1 B

Variable types

Categorical3
Numeric3

Warnings

Code has a high cardinality: 865 distinct values High cardinality
Name has a high cardinality: 865 distinct values High cardinality
Hex has a high cardinality: 765 distinct values High cardinality
B is highly correlated with GHigh correlation
G is highly correlated with BHigh correlation
Code is uniformly distributed Uniform
Name is uniformly distributed Uniform
Hex is uniformly distributed Uniform
Code has unique values Unique
Name has unique values Unique
R has 81 (9.4%) zeros Zeros
G has 58 (6.7%) zeros Zeros
B has 80 (9.2%) zeros Zeros

Reproduction

Analysis started2021-05-11 22:13:42.969061
Analysis finished2021-05-11 22:13:45.773083
Duration2.8 seconds
Software versionpandas-profiling v3.0.0
Download configurationconfig.json

Variables

Code
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct865
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size57.9 KiB
chartreuse_traditional
 
1
ube
 
1
blanched_almond
 
1
plum_web
 
1
light_blue
 
1
Other values (860)
860 

Length

Max length39
Median length11
Mean length11.37572254
Min length3

Characters and Unicode

Total characters9840
Distinct characters31
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique865 ?
Unique (%)100.0%

Sample

1st rowair_force_blue_raf
2nd rowair_force_blue_usaf
3rd rowair_superiority_blue
4th rowalabama_crimson
5th rowalice_blue

Common Values

ValueCountFrequency (%)
chartreuse_traditional1
 
0.1%
ube1
 
0.1%
blanched_almond1
 
0.1%
plum_web1
 
0.1%
light_blue1
 
0.1%
russet1
 
0.1%
dark_cyan1
 
0.1%
sea_blue1
 
0.1%
azure1
 
0.1%
celadon1
 
0.1%
Other values (855)855
98.8%

Length

2021-05-11T22:13:46.046258image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
chartreuse_traditional1
 
0.1%
ube1
 
0.1%
blanched_almond1
 
0.1%
plum_web1
 
0.1%
light_blue1
 
0.1%
russet1
 
0.1%
dark_cyan1
 
0.1%
sea_blue1
 
0.1%
azure1
 
0.1%
celadon1
 
0.1%
Other values (855)855
98.8%

Most occurring characters

ValueCountFrequency (%)
e1201
 
12.2%
_799
 
8.1%
r796
 
8.1%
a788
 
8.0%
l695
 
7.1%
n626
 
6.4%
i558
 
5.7%
o519
 
5.3%
t396
 
4.0%
u373
 
3.8%
Other values (21)3089
31.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter9025
91.7%
Connector Punctuation799
 
8.1%
Decimal Number16
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1201
13.3%
r796
 
8.8%
a788
 
8.7%
l695
 
7.7%
n626
 
6.9%
i558
 
6.2%
o519
 
5.8%
t396
 
4.4%
u373
 
4.1%
s343
 
3.8%
Other values (16)2730
30.2%
Decimal Number
ValueCountFrequency (%)
113
81.2%
91
 
6.2%
71
 
6.2%
31
 
6.2%
Connector Punctuation
ValueCountFrequency (%)
_799
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9025
91.7%
Common815
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1201
13.3%
r796
 
8.8%
a788
 
8.7%
l695
 
7.7%
n626
 
6.9%
i558
 
6.2%
o519
 
5.8%
t396
 
4.4%
u373
 
4.1%
s343
 
3.8%
Other values (16)2730
30.2%
Common
ValueCountFrequency (%)
_799
98.0%
113
 
1.6%
91
 
0.1%
71
 
0.1%
31
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII9840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e1201
 
12.2%
_799
 
8.1%
r796
 
8.1%
a788
 
8.0%
l695
 
7.1%
n626
 
6.4%
i558
 
5.7%
o519
 
5.3%
t396
 
4.0%
u373
 
3.8%
Other values (21)3089
31.4%

Name
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct865
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size58.2 KiB
Meat Brown
 
1
Medium Violet-Red
 
1
Dark Yellow
 
1
Tiffany Blue
 
1
Dark Coral
 
1
Other values (860)
860 

Length

Max length41
Median length11
Mean length11.59190751
Min length3

Characters and Unicode

Total characters10027
Distinct characters69
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique865 ?
Unique (%)100.0%

Sample

1st rowAir Force Blue (Raf)
2nd rowAir Force Blue (Usaf)
3rd rowAir Superiority Blue
4th rowAlabama Crimson
5th rowAlice Blue

Common Values

ValueCountFrequency (%)
Meat Brown1
 
0.1%
Medium Violet-Red1
 
0.1%
Dark Yellow1
 
0.1%
Tiffany Blue1
 
0.1%
Dark Coral1
 
0.1%
Pastel Green1
 
0.1%
Byzantine1
 
0.1%
June Bud1
 
0.1%
Dark Sienna1
 
0.1%
Pale Lavender1
 
0.1%
Other values (855)855
98.8%

Length

2021-05-11T22:13:46.399864image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
blue98
 
6.0%
green78
 
4.8%
pink47
 
2.9%
dark45
 
2.8%
red42
 
2.6%
yellow31
 
1.9%
rose28
 
1.7%
light25
 
1.5%
lavender23
 
1.4%
orange23
 
1.4%
Other values (606)1190
73.0%

Most occurring characters

ValueCountFrequency (%)
e1168
 
11.6%
765
 
7.6%
a737
 
7.4%
r661
 
6.6%
l611
 
6.1%
n609
 
6.1%
i536
 
5.3%
o463
 
4.6%
u345
 
3.4%
t328
 
3.3%
Other values (59)3804
37.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7369
73.5%
Uppercase Letter1661
 
16.6%
Space Separator765
 
7.6%
Open Punctuation89
 
0.9%
Close Punctuation89
 
0.9%
Dash Punctuation20
 
0.2%
Other Punctuation17
 
0.2%
Decimal Number16
 
0.2%
Final Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1168
15.9%
a737
10.0%
r661
 
9.0%
l611
 
8.3%
n609
 
8.3%
i536
 
7.3%
o463
 
6.3%
u345
 
4.7%
t328
 
4.5%
d251
 
3.4%
Other values (19)1660
22.5%
Uppercase Letter
ValueCountFrequency (%)
B206
12.4%
P174
10.5%
C158
 
9.5%
G140
 
8.4%
R135
 
8.1%
M95
 
5.7%
S93
 
5.6%
D90
 
5.4%
L84
 
5.1%
T68
 
4.1%
Other values (16)418
25.2%
Other Punctuation
ValueCountFrequency (%)
/7
41.2%
'6
35.3%
#2
 
11.8%
&1
 
5.9%
.1
 
5.9%
Decimal Number
ValueCountFrequency (%)
113
81.2%
91
 
6.2%
71
 
6.2%
31
 
6.2%
Space Separator
ValueCountFrequency (%)
765
100.0%
Open Punctuation
ValueCountFrequency (%)
(89
100.0%
Close Punctuation
ValueCountFrequency (%)
)89
100.0%
Dash Punctuation
ValueCountFrequency (%)
-20
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9030
90.1%
Common997
 
9.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1168
 
12.9%
a737
 
8.2%
r661
 
7.3%
l611
 
6.8%
n609
 
6.7%
i536
 
5.9%
o463
 
5.1%
u345
 
3.8%
t328
 
3.6%
d251
 
2.8%
Other values (45)3321
36.8%
Common
ValueCountFrequency (%)
765
76.7%
(89
 
8.9%
)89
 
8.9%
-20
 
2.0%
113
 
1.3%
/7
 
0.7%
'6
 
0.6%
#2
 
0.2%
1
 
0.1%
&1
 
0.1%
Other values (4)4
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII10021
99.9%
Latin 1 Sup5
 
< 0.1%
Punctuation1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e1168
 
11.7%
765
 
7.6%
a737
 
7.4%
r661
 
6.6%
l611
 
6.1%
n609
 
6.1%
i536
 
5.3%
o463
 
4.6%
u345
 
3.4%
t328
 
3.3%
Other values (55)3798
37.9%
Punctuation
ValueCountFrequency (%)
1
100.0%
Latin 1 Sup
ValueCountFrequency (%)
é3
60.0%
à1
 
20.0%
ú1
 
20.0%

Hex
Categorical

HIGH CARDINALITY
UNIFORM

Distinct765
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size54.0 KiB
#c19a6b
 
5
#967117
 
4
#fada5e
 
4
#900
 
3
#008000
 
3
Other values (760)
846 

Length

Max length7
Median length7
Mean length6.798843931
Min length4

Characters and Unicode

Total characters5881
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique684 ?
Unique (%)79.1%

Sample

1st row#5d8aa8
2nd row#00308f
3rd row#72a0c1
4th row#a32638
5th row#f0f8ff

Common Values

ValueCountFrequency (%)
#c19a6b5
 
0.6%
#9671174
 
0.5%
#fada5e4
 
0.5%
#9003
 
0.3%
#0080003
 
0.3%
#0ff3
 
0.3%
#dda0dd3
 
0.3%
#f883793
 
0.3%
#d2691e3
 
0.3%
#483c323
 
0.3%
Other values (755)831
96.1%

Length

2021-05-11T22:13:46.751245image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
c19a6b5
 
0.6%
fada5e4
 
0.5%
9671174
 
0.5%
d2691e3
 
0.3%
8080803
 
0.3%
a52a2a3
 
0.3%
0080003
 
0.3%
cf03
 
0.3%
dda0dd3
 
0.3%
0ff3
 
0.3%
Other values (755)831
96.1%

Most occurring characters

ValueCountFrequency (%)
#865
14.7%
0665
 
11.3%
f625
 
10.6%
8317
 
5.4%
c300
 
5.1%
a292
 
5.0%
e269
 
4.6%
4268
 
4.6%
b268
 
4.6%
3267
 
4.5%
Other values (7)1745
29.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2997
51.0%
Lowercase Letter2019
34.3%
Other Punctuation865
 
14.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0665
22.2%
8317
10.6%
4268
8.9%
3267
8.9%
6265
 
8.8%
7252
 
8.4%
9250
 
8.3%
5248
 
8.3%
2243
 
8.1%
1222
 
7.4%
Lowercase Letter
ValueCountFrequency (%)
f625
31.0%
c300
14.9%
a292
14.5%
e269
13.3%
b268
13.3%
d265
13.1%
Other Punctuation
ValueCountFrequency (%)
#865
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common3862
65.7%
Latin2019
34.3%

Most frequent character per script

Common
ValueCountFrequency (%)
#865
22.4%
0665
17.2%
8317
 
8.2%
4268
 
6.9%
3267
 
6.9%
6265
 
6.9%
7252
 
6.5%
9250
 
6.5%
5248
 
6.4%
2243
 
6.3%
Latin
ValueCountFrequency (%)
f625
31.0%
c300
14.9%
a292
14.5%
e269
13.3%
b268
13.3%
d265
13.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII5881
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
#865
14.7%
0665
 
11.3%
f625
 
10.6%
8317
 
5.4%
c300
 
5.1%
a292
 
5.0%
e269
 
4.6%
4268
 
4.6%
b268
 
4.6%
3267
 
4.5%
Other values (7)1745
29.7%

R
Real number (ℝ≥0)

ZEROS

Distinct221
Distinct (%)25.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean158.5988439
Minimum0
Maximum255
Zeros81
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2021-05-11T22:13:46.912049image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1101
median178
Q3236
95-th percentile255
Maximum255
Range255
Interquartile range (IQR)135

Descriptive statistics

Standard deviation85.33843164
Coefficient of variation (CV)0.5380772617
Kurtosis-0.9264508707
Mean158.5988439
Median Absolute Deviation (MAD)66
Skewness-0.5936792074
Sum137188
Variance7282.647915
MonotonicityNot monotonic
2021-05-11T22:13:47.228551image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
255110
 
12.7%
081
 
9.4%
25015
 
1.7%
20413
 
1.5%
12811
 
1.3%
15011
 
1.3%
22710
 
1.2%
15310
 
1.2%
24410
 
1.2%
2309
 
1.0%
Other values (211)585
67.6%
ValueCountFrequency (%)
081
9.4%
14
 
0.5%
21
 
0.1%
32
 
0.2%
51
 
0.1%
61
 
0.1%
84
 
0.5%
101
 
0.1%
111
 
0.1%
131
 
0.1%
ValueCountFrequency (%)
255110
12.7%
2547
 
0.8%
2538
 
0.9%
2526
 
0.7%
2519
 
1.0%
25015
 
1.7%
2494
 
0.5%
2488
 
0.9%
2473
 
0.3%
2462
 
0.2%

G
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct234
Distinct (%)27.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean124.683237
Minimum0
Maximum255
Zeros58
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2021-05-11T22:13:47.394951image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q164
median123
Q3190
95-th percentile250
Maximum255
Range255
Interquartile range (IQR)126

Descriptive statistics

Standard deviation76.27022506
Coefficient of variation (CV)0.6117119422
Kurtosis-1.097846721
Mean124.683237
Median Absolute Deviation (MAD)63
Skewness0.0522334723
Sum107851
Variance5817.14723
MonotonicityNot monotonic
2021-05-11T22:13:47.562545image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
058
 
6.7%
25535
 
4.0%
12813
 
1.5%
10512
 
1.4%
5111
 
1.3%
20411
 
1.3%
669
 
1.0%
2189
 
1.0%
1609
 
1.0%
1029
 
1.0%
Other values (224)689
79.7%
ValueCountFrequency (%)
058
6.7%
12
 
0.2%
22
 
0.2%
32
 
0.2%
62
 
0.2%
82
 
0.2%
103
 
0.3%
112
 
0.2%
123
 
0.3%
142
 
0.2%
ValueCountFrequency (%)
25535
4.0%
2543
 
0.3%
2532
 
0.2%
2522
 
0.2%
2511
 
0.1%
2505
 
0.6%
2491
 
0.1%
2484
 
0.5%
2472
 
0.2%
2461
 
0.1%

B
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct230
Distinct (%)26.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean119.0878613
Minimum0
Maximum255
Zeros80
Zeros (%)9.2%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2021-05-11T22:13:47.726040image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q153
median119
Q3186
95-th percentile253.6
Maximum255
Range255
Interquartile range (IQR)133

Descriptive statistics

Standard deviation78.34386249
Coefficient of variation (CV)0.6578660634
Kurtosis-1.13796004
Mean119.0878613
Median Absolute Deviation (MAD)66
Skewness0.1072876893
Sum103011
Variance6137.76079
MonotonicityNot monotonic
2021-05-11T22:13:47.892188image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
080
 
9.2%
25541
 
4.7%
10715
 
1.7%
12814
 
1.6%
20410
 
1.2%
1209
 
1.0%
949
 
1.0%
598
 
0.9%
338
 
0.9%
968
 
0.9%
Other values (220)663
76.6%
ValueCountFrequency (%)
080
9.2%
23
 
0.3%
31
 
0.1%
52
 
0.2%
72
 
0.2%
83
 
0.3%
91
 
0.1%
102
 
0.2%
113
 
0.3%
123
 
0.3%
ValueCountFrequency (%)
25541
4.7%
2543
 
0.3%
2521
 
0.1%
2511
 
0.1%
2507
 
0.8%
2491
 
0.1%
2453
 
0.3%
2442
 
0.2%
2411
 
0.1%
2406
 
0.7%

Interactions

2021-05-11T22:13:44.076044image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-11T22:13:44.338593image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-11T22:13:44.473421image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-11T22:13:44.610784image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-11T22:13:44.747783image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-11T22:13:44.883219image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-11T22:13:45.018883image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/