Overview

Dataset statistics

Number of variables12
Number of observations10000
Missing cells8083
Missing cells (%)6.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 MiB
Average record size in memory107.0 B

Variable types

Numeric1
Categorical6
Text3
DateTime2

Dataset

Description일련번호,분류,품목명,원산지,수거일자,수거장소,검사일자,기준세슘수치,검출량,기준요오드수치,검출량,판정(적합여부)
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15505/S/1/datasetView.do

Alerts

판정(적합여부) has constant value ""Constant
검출량 is highly overall correlated with 기준세슘수치 and 2 other fieldsHigh correlation
분류 is highly overall correlated with 검출량.1High correlation
검출량.1 is highly overall correlated with 일련번호 and 4 other fieldsHigh correlation
기준세슘수치 is highly overall correlated with 검출량 and 1 other fieldsHigh correlation
기준요오드수치 is highly overall correlated with 일련번호 and 2 other fieldsHigh correlation
일련번호 is highly overall correlated with 기준요오드수치 and 1 other fieldsHigh correlation
분류 is highly imbalanced (71.8%)Imbalance
기준세슘수치 is highly imbalanced (99.3%)Imbalance
검출량 is highly imbalanced (98.8%)Imbalance
기준요오드수치 is highly imbalanced (69.3%)Imbalance
검출량.1 is highly imbalanced (99.9%)Imbalance
수거장소 has 8077 (80.8%) missing valuesMissing
일련번호 has unique valuesUnique

Reproduction

Analysis started2024-05-04 06:04:30.230980
Analysis finished2024-05-04 06:04:34.695425
Duration4.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30008.53
Minimum1
Maximum53459
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T06:04:34.934241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1434.95
Q115197.75
median32985
Q345764.5
95-th percentile51947.3
Maximum53459
Range53458
Interquartile range (IQR)30566.75

Descriptive statistics

Standard deviation17060.28
Coefficient of variation (CV)0.56851435
Kurtosis-1.2134674
Mean30008.53
Median Absolute Deviation (MAD)14229.5
Skewness-0.37613573
Sum3.000853 × 108
Variance2.9105315 × 108
MonotonicityNot monotonic
2024-05-04T06:04:35.369014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49649 1
 
< 0.1%
36394 1
 
< 0.1%
3107 1
 
< 0.1%
45803 1
 
< 0.1%
15358 1
 
< 0.1%
49917 1
 
< 0.1%
50864 1
 
< 0.1%
44938 1
 
< 0.1%
48331 1
 
< 0.1%
16303 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
8 1
< 0.1%
14 1
< 0.1%
16 1
< 0.1%
17 1
< 0.1%
19 1
< 0.1%
27 1
< 0.1%
31 1
< 0.1%
ValueCountFrequency (%)
53459 1
< 0.1%
53457 1
< 0.1%
53456 1
< 0.1%
53455 1
< 0.1%
53452 1
< 0.1%
53451 1
< 0.1%
53450 1
< 0.1%
53445 1
< 0.1%
53443 1
< 0.1%
53441 1
< 0.1%

분류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수산물
7635 
가공식품
1337 
농산물
774 
수산물가공품
 
141
축산물
 
62
Other values (12)
 
51

Length

Max length11
Median length3
Mean length3.1902
Min length2

Unique

Unique7 ?
Unique (%)0.1%

Sample

1st row수산물
2nd row수산물
3rd row농산물
4th row가공식품
5th row수산물

Common Values

ValueCountFrequency (%)
수산물 7635
76.3%
가공식품 1337
 
13.4%
농산물 774
 
7.7%
수산물가공품 141
 
1.4%
축산물 62
 
0.6%
축산물가공품 29
 
0.3%
냉동수산물 7
 
0.1%
기타수산물가공품 4
 
< 0.1%
기타건포류 2
 
< 0.1%
곡류가공품 2
 
< 0.1%
Other values (7) 7
 
0.1%

Length

2024-05-04T06:04:35.917439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수산물 7635
76.3%
가공식품 1337
 
13.4%
농산물 774
 
7.7%
수산물가공품 141
 
1.4%
축산물 62
 
0.6%
축산물가공품 29
 
0.3%
냉동수산물 7
 
0.1%
기타수산물가공품 4
 
< 0.1%
곡류가공품 2
 
< 0.1%
기타건포류 2
 
< 0.1%
Other values (7) 7
 
0.1%

품목명
Text

Distinct2166
Distinct (%)21.7%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-04T06:04:36.680696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length73
Mean length3.7876788
Min length1

Characters and Unicode

Total characters37873
Distinct characters751
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1571 ?
Unique (%)15.7%

Sample

1st row참돔
2nd row낙지
3rd row알배기
4th row바지락
5th row조기
ValueCountFrequency (%)
고등어 294
 
2.6%
참돔 284
 
2.5%
광어 277
 
2.5%
오징어 247
 
2.2%
농어 241
 
2.1%
삼치 222
 
2.0%
갈치 205
 
1.8%
낙지 191
 
1.7%
우럭 167
 
1.5%
가자미 157
 
1.4%
Other values (2667) 8939
79.6%
2024-05-04T06:04:38.086586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 2566
 
6.8%
1255
 
3.3%
치 910
 
2.4%
리 797
 
2.1%
미 774
 
2.0%
고 648
 
1.7%
우 582
 
1.5%
오 559
 
1.5%
가 548
 
1.4%
살 536
 
1.4%
Other values (741) 28698
75.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 32739
86.4%
Uppercase Letter 2728
 
7.2%
Space Separator 1255
 
3.3%
Close Punctuation 318
 
0.8%
Open Punctuation 316
 
0.8%
Decimal Number 283
 
0.7%
Lowercase Letter 145
 
0.4%
Other Punctuation 55
 
0.1%
Dash Punctuation 32
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 2566
 
7.8%
치 910
 
2.8%
리 797
 
2.4%
미 774
 
2.4%
고 648
 
2.0%
우 582
 
1.8%
오 559
 
1.7%
가 548
 
1.7%
살 536
 
1.6%
돔 493
 
1.5%
Other values (671) 24326
74.3%
Uppercase Letter
ValueCountFrequency (%)
A 326
 
12.0%
S 232
 
8.5%
O 218
 
8.0%
E 217
 
8.0%
I 208
 
7.6%
N 166
 
6.1%
U 155
 
5.7%
R 134
 
4.9%
C 127
 
4.7%
T 120
 
4.4%
Other values (16) 825
30.2%
Lowercase Letter
ValueCountFrequency (%)
l 19
13.1%
m 17
11.7%
g 17
11.7%
e 12
 
8.3%
i 9
 
6.2%
r 9
 
6.2%
t 8
 
5.5%
a 8
 
5.5%
u 8
 
5.5%
o 8
 
5.5%
Other values (9) 30
20.7%
Decimal Number
ValueCountFrequency (%)
0 77
27.2%
1 54
19.1%
5 30
 
10.6%
9 27
 
9.5%
2 26
 
9.2%
3 26
 
9.2%
6 15
 
5.3%
8 13
 
4.6%
4 10
 
3.5%
7 5
 
1.8%
Other Punctuation
ValueCountFrequency (%)
/ 16
29.1%
& 15
27.3%
% 13
23.6%
, 3
 
5.5%
. 3
 
5.5%
! 2
 
3.6%
: 1
 
1.8%
? 1
 
1.8%
？ 1
 
1.8%
Math Symbol
ValueCountFrequency (%)
~ 1
50.0%
+ 1
50.0%
Space Separator
ValueCountFrequency (%)
1255
100.0%
Close Punctuation
ValueCountFrequency (%)
) 318
100.0%
Open Punctuation
ValueCountFrequency (%)
( 316
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 32738
86.4%
Latin 2873
 
7.6%
Common 2261
 
6.0%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 2566
 
7.8%
치 910
 
2.8%
리 797
 
2.4%
미 774
 
2.4%
고 648
 
2.0%
우 582
 
1.8%
오 559
 
1.7%
가 548
 
1.7%
살 536
 
1.6%
돔 493
 
1.5%
Other values (670) 24325
74.3%
Latin
ValueCountFrequency (%)
A 326
 
11.3%
S 232
 
8.1%
O 218
 
7.6%
E 217
 
7.6%
I 208
 
7.2%
N 166
 
5.8%
U 155
 
5.4%
R 134
 
4.7%
C 127
 
4.4%
T 120
 
4.2%
Other values (35) 970
33.8%
Common
ValueCountFrequency (%)
1255
55.5%
) 318
 
14.1%
( 316
 
14.0%
0 77
 
3.4%
1 54
 
2.4%
- 32
 
1.4%
5 30
 
1.3%
9 27
 
1.2%
2 26
 
1.1%
3 26
 
1.1%
Other values (15) 100
 
4.4%
Han
ValueCountFrequency (%)
上 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 32738
86.4%
ASCII 5133
 
13.6%
CJK 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 2566
 
7.8%
치 910
 
2.8%
리 797
 
2.4%
미 774
 
2.4%
고 648
 
2.0%
우 582
 
1.8%
오 559
 
1.7%
가 548
 
1.7%
살 536
 
1.6%
돔 493
 
1.5%
Other values (670) 24325
74.3%
ASCII
ValueCountFrequency (%)
1255
24.4%
A 326
 
6.4%
) 318
 
6.2%
( 316
 
6.2%
S 232
 
4.5%
O 218
 
4.2%
E 217
 
4.2%
I 208
 
4.1%
N 166
 
3.2%
U 155
 
3.0%
Other values (59) 1722
33.5%
CJK
ValueCountFrequency (%)
上 1
100.0%
None
ValueCountFrequency (%)
？ 1
100.0%

원산지
Text

Distinct186
Distinct (%)1.9%
Missing5
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-04T06:04:38.852958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length2
Mean length2.3996998
Min length2

Characters and Unicode

Total characters23985
Distinct characters174
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)0.7%

Sample

1st row일본
2nd row국산
3rd row국내산
4th row중국산
5th row중국
ValueCountFrequency (%)
국내 1972
19.7%
국내산 1967
19.7%
중국 758
 
7.6%
국산 740
 
7.4%
국외 560
 
5.6%
일본 555
 
5.5%
러시아 366
 
3.7%
수입산 265
 
2.6%
완도 214
 
2.1%
통영 199
 
2.0%
Other values (176) 2404
24.0%
2024-05-04T06:04:39.970636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 6278
26.2%
내 3944
16.4%
산 3402
14.2%
중 845
 
3.5%
일 596
 
2.5%
본 585
 
2.4%
외 561
 
2.3%
수 537
 
2.2%
아 471
 
2.0%
시 413
 
1.7%
Other values (164) 6353
26.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23929
99.8%
Close Punctuation 21
 
0.1%
Open Punctuation 21
 
0.1%
Other Punctuation 7
 
< 0.1%
Space Separator 5
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 6278
26.2%
내 3944
16.5%
산 3402
14.2%
중 845
 
3.5%
일 596
 
2.5%
본 585
 
2.4%
외 561
 
2.3%
수 537
 
2.2%
아 471
 
2.0%
시 413
 
1.7%
Other values (158) 6297
26.3%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
: 1
 
14.3%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23929
99.8%
Common 56
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 6278
26.2%
내 3944
16.5%
산 3402
14.2%
중 845
 
3.5%
일 596
 
2.5%
본 585
 
2.4%
외 561
 
2.3%
수 537
 
2.2%
아 471
 
2.0%
시 413
 
1.7%
Other values (158) 6297
26.3%
Common
ValueCountFrequency (%)
) 21
37.5%
( 21
37.5%
, 6
 
10.7%
5
 
8.9%
- 2
 
3.6%
: 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23929
99.8%
ASCII 56
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 6278
26.2%
내 3944
16.5%
산 3402
14.2%
중 845
 
3.5%
일 596
 
2.5%
본 585
 
2.4%
외 561
 
2.3%
수 537
 
2.2%
아 471
 
2.0%
시 413
 
1.7%
Other values (158) 6297
26.3%
ASCII
ValueCountFrequency (%)
) 21
37.5%
( 21
37.5%
, 6
 
10.7%
5
 
8.9%
- 2
 
3.6%
: 1
 
1.8%

수거일자
Date

Distinct960
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2011-01-01 00:00:00
Maximum2024-05-03 00:00:00
2024-05-04T06:04:40.458363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:04:40.994596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수거장소
Text

MISSING 

Distinct583
Distinct (%)30.3%
Missing8077
Missing (%)80.8%
Memory size156.2 KiB
2024-05-04T06:04:41.680548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length20
Mean length8.2532501
Min length2

Characters and Unicode

Total characters15871
Distinct characters330
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique255 ?
Unique (%)13.3%

Sample

1st row가락시장 현진상회
2nd row㈜홈플러스 강동점
3rd row해당업소(위생과)
4th row부경수산(주)
5th row서부일광
ValueCountFrequency (%)
이마트 141
 
5.2%
가락시장 98
 
3.6%
롯데마트 91
 
3.4%
홈플러스 81
 
3.0%
하나로마트 74
 
2.8%
양재점 74
 
2.8%
잠실점 51
 
1.9%
가든5점 42
 
1.6%
강동점 37
 
1.4%
구례상회 33
 
1.2%
Other values (616) 1968
73.2%
2024-05-04T06:04:42.861919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
787
 
5.0%
점 772
 
4.9%
마 629
 
4.0%
트 593
 
3.7%
수 349
 
2.2%
) 345
 
2.2%
( 333
 
2.1%
산 328
 
2.1%
이 321
 
2.0%
동 302
 
1.9%
Other values (320) 11112
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13954
87.9%
Space Separator 787
 
5.0%
Close Punctuation 352
 
2.2%
Open Punctuation 340
 
2.1%
Other Symbol 212
 
1.3%
Decimal Number 171
 
1.1%
Uppercase Letter 36
 
0.2%
Other Punctuation 11
 
0.1%
Dash Punctuation 4
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 772
 
5.5%
마 629
 
4.5%
트 593
 
4.2%
수 349
 
2.5%
산 328
 
2.4%
이 321
 
2.3%
동 302
 
2.2%
시 254
 
1.8%
양 245
 
1.8%
가 241
 
1.7%
Other values (291) 9920
71.1%
Decimal Number
ValueCountFrequency (%)
5 72
42.1%
1 24
 
14.0%
2 23
 
13.5%
6 13
 
7.6%
3 9
 
5.3%
8 8
 
4.7%
7 7
 
4.1%
0 7
 
4.1%
4 5
 
2.9%
9 3
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
S 12
33.3%
G 9
25.0%
C 5
13.9%
U 4
 
11.1%
A 2
 
5.6%
K 2
 
5.6%
B 1
 
2.8%
J 1
 
2.8%
Close Punctuation
ValueCountFrequency (%)
) 345
98.0%
] 7
 
2.0%
Open Punctuation
ValueCountFrequency (%)
( 333
97.9%
[ 7
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 8
72.7%
? 3
 
27.3%
Lowercase Letter
ValueCountFrequency (%)
c 2
50.0%
j 2
50.0%
Space Separator
ValueCountFrequency (%)
787
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 212
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14166
89.3%
Common 1665
 
10.5%
Latin 40
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 772
 
5.4%
마 629
 
4.4%
트 593
 
4.2%
수 349
 
2.5%
산 328
 
2.3%
이 321
 
2.3%
동 302
 
2.1%
시 254
 
1.8%
양 245
 
1.7%
가 241
 
1.7%
Other values (292) 10132
71.5%
Common
ValueCountFrequency (%)
787
47.3%
) 345
20.7%
( 333
20.0%
5 72
 
4.3%
1 24
 
1.4%
2 23
 
1.4%
6 13
 
0.8%
3 9
 
0.5%
8 8
 
0.5%
. 8
 
0.5%
Other values (8) 43
 
2.6%
Latin
ValueCountFrequency (%)
S 12
30.0%
G 9
22.5%
C 5
12.5%
U 4
 
10.0%
A 2
 
5.0%
K 2
 
5.0%
c 2
 
5.0%
j 2
 
5.0%
B 1
 
2.5%
J 1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13954
87.9%
ASCII 1705
 
10.7%
None 212
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
787
46.2%
) 345
20.2%
( 333
19.5%
5 72
 
4.2%
1 24
 
1.4%
2 23
 
1.3%
6 13
 
0.8%
S 12
 
0.7%
G 9
 
0.5%
3 9
 
0.5%
Other values (18) 78
 
4.6%
Hangul
ValueCountFrequency (%)
점 772
 
5.5%
마 629
 
4.5%
트 593
 
4.2%
수 349
 
2.5%
산 328
 
2.4%
이 321
 
2.3%
동 302
 
2.2%
시 254
 
1.8%
양 245
 
1.8%
가 241
 
1.7%
Other values (291) 9920
71.1%
None
ValueCountFrequency (%)
㈜ 212
100.0%

검사일자
Date

Distinct900
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2011-01-01 00:00:00
Maximum2024-05-03 00:00:00
2024-05-04T06:04:43.462779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:04:44.002847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

기준세슘수치
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
100
9991 
370
 
8
<NA>
 
1

Length

Max length4
Median length3
Mean length3.0001
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row100
2nd row100
3rd row100
4th row100
5th row100

Common Values

ValueCountFrequency (%)
100 9991
99.9%
370 8
 
0.1%
<NA> 1
 
< 0.1%

Length

2024-05-04T06:04:44.524167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T06:04:44.953489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
100 9991
99.9%
370 8
 
0.1%
na 1
 
< 0.1%

검출량
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
불검출
9963 
1
 
15
2
 
8
3
 
3
36
 
2
Other values (8)
 
9

Length

Max length4
Median length3
Mean length2.9937
Min length1

Unique

Unique7 ?
Unique (%)0.1%

Sample

1st row불검출
2nd row불검출
3rd row불검출
4th row불검출
5th row불검출

Common Values

ValueCountFrequency (%)
불검출 9963
99.6%
1 15
 
0.1%
2 8
 
0.1%
3 3
 
< 0.1%
36 2
 
< 0.1%
4 2
 
< 0.1%
<NA> 1
 
< 0.1%
19 1
 
< 0.1%
32 1
 
< 0.1%
48 1
 
< 0.1%
Other values (3) 3
 
< 0.1%

Length

2024-05-04T06:04:45.397641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
불검출 9963
99.6%
1 15
 
0.1%
2 8
 
0.1%
3 3
 
< 0.1%
36 2
 
< 0.1%
4 2
 
< 0.1%
na 1
 
< 0.1%
19 1
 
< 0.1%
32 1
 
< 0.1%
48 1
 
< 0.1%
Other values (3) 3
 
< 0.1%

기준요오드수치
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
100
8489 
300
1509 
<NA>
 
1
370
 
1

Length

Max length4
Median length3
Mean length3.0001
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row100
2nd row100
3rd row300
4th row100
5th row100

Common Values

ValueCountFrequency (%)
100 8489
84.9%
300 1509
 
15.1%
<NA> 1
 
< 0.1%
370 1
 
< 0.1%

Length

2024-05-04T06:04:45.883595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T06:04:46.269317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
100 8489
84.9%
300 1509
 
15.1%
na 1
 
< 0.1%
370 1
 
< 0.1%

검출량.1
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
불검출
9999 
<NA>
 
1

Length

Max length4
Median length3
Mean length3.0001
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row불검출
2nd row불검출
3rd row불검출
4th row불검출
5th row불검출

Common Values

ValueCountFrequency (%)
불검출 9999
> 99.9%
<NA> 1
 
< 0.1%

Length

2024-05-04T06:04:46.684448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T06:04:47.042031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불검출 9999
> 99.9%
na 1
 
< 0.1%

판정(적합여부)
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
적합
10000 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row적합
2nd row적합
3rd row적합
4th row적합
5th row적합

Common Values

ValueCountFrequency (%)
적합 10000
100.0%

Length

2024-05-04T06:04:47.456530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T06:04:47.865370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적합 10000
100.0%

Interactions

2024-05-04T06:04:32.887341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T06:04:48.167761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호분류기준세슘수치검출량기준요오드수치
일련번호1.0000.4480.0620.0730.925
분류0.4481.0000.0000.0000.456
기준세슘수치0.0620.0001.0000.8640.218
검출량0.0730.0000.8641.0000.784
기준요오드수치0.9250.4560.2180.7841.000
2024-05-04T06:04:48.528563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
검출량분류검출량.1기준세슘수치기준요오드수치
검출량1.0000.0001.0000.7060.505
분류0.0001.0001.0000.0000.281
검출량.11.0001.0001.0001.0001.000
기준세슘수치0.7060.0001.0001.0000.357
기준요오드수치0.5050.2811.0000.3571.000
2024-05-04T06:04:48.870132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호분류기준세슘수치검출량기준요오드수치검출량.1
일련번호1.0000.2020.0620.0310.6801.000
분류0.2021.0000.0000.0000.2811.000
기준세슘수치0.0620.0001.0000.7060.3571.000
검출량0.0310.0000.7061.0000.5051.000
기준요오드수치0.6800.2810.3570.5051.0001.000
검출량.11.0001.0001.0001.0001.0001.000

Missing values

2024-05-04T06:04:33.265519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T06:04:34.018053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-05-04T06:04:34.438435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

일련번호분류품목명원산지수거일자수거장소검사일자기준세슘수치검출량기준요오드수치검출량.1판정(적합여부)
2335149649수산물참돔일본2024.03.25<NA>2024.03.25100불검출100불검출적합
1985644918수산물낙지국산2024.02.05<NA>2024.02.05100불검출100불검출적합
42275235농산물알배기국내산2018.12.19가락시장 현진상회2018.12.26100불검출300불검출적합
2282645663가공식품바지락중국산2024.02.15<NA>2024.02.15100불검출100불검출적합
2027446401수산물조기중국2023.02.23<NA>2023.02.23100불검출100불검출적합
1421335498수산물방어제주2023.11.20<NA>2023.11.20100불검출100불검출적합
1433835926수산물새우태안2023.11.24<NA>2023.11.24100불검출100불검출적합
49607798가공식품조미건어포류국내산2019.10.16㈜홈플러스 강동점2019.10.23100불검출100불검출적합
2662651629수산물김서천2024.04.16<NA>2024.04.16100불검출100불검출적합
27474329농산물시금치국내산2018.06.08해당업소(위생과)2018.06.18100불검출300불검출적합
일련번호분류품목명원산지수거일자수거장소검사일자기준세슘수치검출량기준요오드수치검출량.1판정(적합여부)
1773733998수산물흰다리새우에콰도르2023.11.02<NA>2023.11.02100불검출100불검출적합
1920632279수산물능성어일본2023.10.06<NA>2023.10.06100불검출100불검출적합
1842829558수산물우럭페루2023.09.01<NA>2023.09.01100불검출100불검출적합
1827232058수산물참돔일본2023.10.06<NA>2023.10.06100불검출100불검출적합
2321150332수산물동태러시아2024.04.01<NA>2024.04.01100불검출100불검출적합
2522743677수산물해삼남해2024.01.15<NA>2024.01.15100불검출100불검출적합
2539443681수산물대합여수2024.01.15<NA>2024.01.15100불검출100불검출적합
2421548608수산물전복국내2024.03.15<NA>2024.03.15100불검출100불검출적합
42725280수산물생삼치국내산2019.01.29이마트 역삼점2019.02.07100불검출300불검출적합
1312136672수산물홍가리비국내2023.12.06<NA>2023.12.06100불검출100불검출적합