Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory546.9 KiB
Average record size in memory56.0 B

Variable types

Numeric1
Text4
DateTime1

Dataset

Description인천광역시 서구 통신판매업 현황 정보 (관리번호, 법인 또는 상호명, 소재지주소(도로명,지번),취급품목 등) 에 관한 데이터를 제공합니다.
Author인천광역시 서구
URLhttps://www.data.go.kr/data/15039509/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 09:06:16.787583
Analysis finished2024-03-14 09:08:40.006188
Duration2 minutes and 23.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7952.8581
Minimum1
Maximum15824
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T18:08:40.201884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile874.9
Q14035.75
median7971.5
Q311860.25
95-th percentile15002.05
Maximum15824
Range15823
Interquartile range (IQR)7824.5

Descriptive statistics

Standard deviation4532.1658
Coefficient of variation (CV)0.56987887
Kurtosis-1.1938747
Mean7952.8581
Median Absolute Deviation (MAD)3911.5
Skewness-0.010713092
Sum79528581
Variance20540527
MonotonicityNot monotonic
2024-03-14T18:08:40.649372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9214 1
 
< 0.1%
13540 1
 
< 0.1%
3419 1
 
< 0.1%
4817 1
 
< 0.1%
3500 1
 
< 0.1%
7214 1
 
< 0.1%
4753 1
 
< 0.1%
11607 1
 
< 0.1%
9556 1
 
< 0.1%
880 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
8 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
ValueCountFrequency (%)
15824 1
< 0.1%
15822 1
< 0.1%
15820 1
< 0.1%
15818 1
< 0.1%
15817 1
< 0.1%
15816 1
< 0.1%
15814 1
< 0.1%
15813 1
< 0.1%
15809 1
< 0.1%
15806 1
< 0.1%

관리번호
Text

Distinct9978
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T18:08:41.424732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length13.9759
Min length1

Characters and Unicode

Total characters139759
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9956 ?
Unique (%)99.6%

Sample

1st row2020-인천서구-3136
2nd row2019-인천서구-2000
3rd row2023-인천서구-2038
4th row2016-인천서구-0018
5th row2023-인천서구-2972
ValueCountFrequency (%)
2023-인천서구-1672 2
 
< 0.1%
2023-인천서구-1675 2
 
< 0.1%
2023-인천서구-1693 2
 
< 0.1%
2023-인천서구-1692 2
 
< 0.1%
2023-인천서구-1673 2
 
< 0.1%
2023-인천서구-1688 2
 
< 0.1%
2023-인천서구-2390 2
 
< 0.1%
2023-인천서구-2507 2
 
< 0.1%
2023-인천서구-1679 2
 
< 0.1%
2023-인천서구-1682 2
 
< 0.1%
Other values (9968) 9980
99.8%
2024-03-14T18:08:42.585070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 24505
17.5%
- 19944
14.3%
0 18745
13.4%
1 10475
7.5%
서 9961
7.1%
구 9961
7.1%
인 9943
7.1%
천 9943
7.1%
3 6289
 
4.5%
9 3658
 
2.6%
Other values (9) 16335
11.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80003
57.2%
Other Letter 39812
28.5%
Dash Punctuation 19944
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 24505
30.6%
0 18745
23.4%
1 10475
13.1%
3 6289
 
7.9%
9 3658
 
4.6%
6 3370
 
4.2%
7 3334
 
4.2%
8 3305
 
4.1%
5 3195
 
4.0%
4 3127
 
3.9%
Other Letter
ValueCountFrequency (%)
서 9961
25.0%
구 9961
25.0%
인 9943
25.0%
천 9943
25.0%
충 1
 
< 0.1%
남 1
 
< 0.1%
아 1
 
< 0.1%
산 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 19944
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99947
71.5%
Hangul 39812
 
28.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 24505
24.5%
- 19944
20.0%
0 18745
18.8%
1 10475
10.5%
3 6289
 
6.3%
9 3658
 
3.7%
6 3370
 
3.4%
7 3334
 
3.3%
8 3305
 
3.3%
5 3195
 
3.2%
Hangul
ValueCountFrequency (%)
서 9961
25.0%
구 9961
25.0%
인 9943
25.0%
천 9943
25.0%
충 1
 
< 0.1%
남 1
 
< 0.1%
아 1
 
< 0.1%
산 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99947
71.5%
Hangul 39812
 
28.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 24505
24.5%
- 19944
20.0%
0 18745
18.8%
1 10475
10.5%
3 6289
 
6.3%
9 3658
 
3.7%
6 3370
 
3.4%
7 3334
 
3.3%
8 3305
 
3.3%
5 3195
 
3.2%
Hangul
ValueCountFrequency (%)
서 9961
25.0%
구 9961
25.0%
인 9943
25.0%
천 9943
25.0%
충 1
 
< 0.1%
남 1
 
< 0.1%
아 1
 
< 0.1%
산 1
 
< 0.1%

법인또는상호
Text

Distinct9880
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T18:08:43.753728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length38
Mean length6.4677
Min length1

Characters and Unicode

Total characters64677
Distinct characters1089
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9765 ?
Unique (%)97.7%

Sample

1st row라라마트
2nd row수창정밀
3rd row빌리컴퍼니
4th row주식회사 피에스홀딩스코리아PS Holdings Korea Co. Ltd.
5th row첸
ValueCountFrequency (%)
주식회사 985
 
7.5%
주 111
 
0.8%
ltd 39
 
0.3%
인셀덤 39
 
0.3%
co 39
 
0.3%
컴퍼니 36
 
0.3%
더 27
 
0.2%
스튜디오 26
 
0.2%
company 24
 
0.2%
korea 22
 
0.2%
Other values (10953) 11801
89.7%
2024-03-14T18:08:45.347900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3191
 
4.9%
이 2485
 
3.8%
스 1980
 
3.1%
주 1549
 
2.4%
사 1363
 
2.1%
리 1143
 
1.8%
회 1116
 
1.7%
식 1088
 
1.7%
아 829
 
1.3%
에 771
 
1.2%
Other values (1079) 49162
76.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50587
78.2%
Lowercase Letter 5098
 
7.9%
Uppercase Letter 4905
 
7.6%
Space Separator 3191
 
4.9%
Decimal Number 513
 
0.8%
Other Punctuation 292
 
0.5%
Dash Punctuation 52
 
0.1%
Connector Punctuation 30
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 2485
 
4.9%
스 1980
 
3.9%
주 1549
 
3.1%
사 1363
 
2.7%
리 1143
 
2.3%
회 1116
 
2.2%
식 1088
 
2.2%
아 829
 
1.6%
에 771
 
1.5%
니 719
 
1.4%
Other values (1000) 37544
74.2%
Lowercase Letter
ValueCountFrequency (%)
e 598
11.7%
o 556
10.9%
a 447
 
8.8%
n 418
 
8.2%
i 372
 
7.3%
r 316
 
6.2%
l 310
 
6.1%
t 281
 
5.5%
s 253
 
5.0%
m 180
 
3.5%
Other values (16) 1367
26.8%
Uppercase Letter
ValueCountFrequency (%)
A 396
 
8.1%
O 371
 
7.6%
E 351
 
7.2%
S 317
 
6.5%
T 304
 
6.2%
N 292
 
6.0%
C 268
 
5.5%
L 247
 
5.0%
R 247
 
5.0%
I 246
 
5.0%
Other values (16) 1866
38.0%
Decimal Number
ValueCountFrequency (%)
1 107
20.9%
2 93
18.1%
0 62
12.1%
3 62
12.1%
5 38
 
7.4%
9 38
 
7.4%
4 36
 
7.0%
6 29
 
5.7%
7 24
 
4.7%
8 24
 
4.7%
Other Punctuation
ValueCountFrequency (%)
. 172
58.9%
& 84
28.8%
' 19
 
6.5%
# 7
 
2.4%
: 5
 
1.7%
" 2
 
0.7%
/ 1
 
0.3%
＇ 1
 
0.3%
% 1
 
0.3%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Space Separator
ValueCountFrequency (%)
3191
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 30
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 3
100.0%
Close Punctuation
ValueCountFrequency (%)
] 3
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50576
78.2%
Latin 10003
 
15.5%
Common 4087
 
6.3%
Han 11
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 2485
 
4.9%
스 1980
 
3.9%
주 1549
 
3.1%
사 1363
 
2.7%
리 1143
 
2.3%
회 1116
 
2.2%
식 1088
 
2.2%
아 829
 
1.6%
에 771
 
1.5%
니 719
 
1.4%
Other values (990) 37533
74.2%
Latin
ValueCountFrequency (%)
e 598
 
6.0%
o 556
 
5.6%
a 447
 
4.5%
n 418
 
4.2%
A 396
 
4.0%
i 372
 
3.7%
O 371
 
3.7%
E 351
 
3.5%
S 317
 
3.2%
r 316
 
3.2%
Other values (42) 5861
58.6%
Common
ValueCountFrequency (%)
3191
78.1%
. 172
 
4.2%
1 107
 
2.6%
2 93
 
2.3%
& 84
 
2.1%
0 62
 
1.5%
3 62
 
1.5%
- 52
 
1.3%
5 38
 
0.9%
9 38
 
0.9%
Other values (17) 188
 
4.6%
Han
ValueCountFrequency (%)
靑 2
18.2%
潔 1
9.1%
家 1
9.1%
未 1
9.1%
愛 1
9.1%
詳 1
9.1%
朴 1
9.1%
脈 1
9.1%
獨 1
9.1%
也 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50576
78.2%
ASCII 14088
 
21.8%
CJK 11
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3191
22.7%
e 598
 
4.2%
o 556
 
3.9%
a 447
 
3.2%
n 418
 
3.0%
A 396
 
2.8%
i 372
 
2.6%
O 371
 
2.6%
E 351
 
2.5%
S 317
 
2.3%
Other values (67) 7071
50.2%
Hangul
ValueCountFrequency (%)
이 2485
 
4.9%
스 1980
 
3.9%
주 1549
 
3.1%
사 1363
 
2.7%
리 1143
 
2.3%
회 1116
 
2.2%
식 1088
 
2.2%
아 829
 
1.6%
에 771
 
1.5%
니 719
 
1.4%
Other values (990) 37533
74.2%
CJK
ValueCountFrequency (%)
靑 2
18.2%
潔 1
9.1%
家 1
9.1%
未 1
9.1%
愛 1
9.1%
詳 1
9.1%
朴 1
9.1%
脈 1
9.1%
獨 1
9.1%
也 1
9.1%
None
ValueCountFrequency (%)
´ 1
50.0%
＇ 1
50.0%

소재지주소
Text

Distinct5566
Distinct (%)55.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T18:08:46.387186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length81
Median length59
Mean length39.6775
Min length16

Characters and Unicode

Total characters396775
Distinct characters553
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4131 ?
Unique (%)41.3%

Sample

1st row인천광역시 서구 북항로 ** (원창동)
2nd row인천광역시 서구 염곡로 **， *층 (가좌동)
3rd row인천광역시 서구 서달로***번길 **-*， *동 ***호 (석남동， 드림빌라)
4th row인천광역시 서구 염곡로 ***， *층 (신현동)
5th row인천광역시 서구 고산후로***번안길 **， KM빌딩 ***호 (원당동)
ValueCountFrequency (%)
인천광역시 10000
 
13.3%
서구 9998
 
13.3%
， 8931
 
11.9%
호 7343
 
9.8%
동 4296
 
5.7%
층 2589
 
3.4%
청라동 1173
 
1.6%
청라동， 995
 
1.3%
925
 
1.2%
가좌동 854
 
1.1%
Other values (2561) 28028
37.3%
2024-03-14T18:08:47.942759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 79649
20.1%
65684
16.6%
동 15375
 
3.9%
， 13995
 
3.5%
서 11128
 
2.8%
시 10633
 
2.7%
로 10451
 
2.6%
인 10350
 
2.6%
천 10219
 
2.6%
광 10189
 
2.6%
Other values (543) 159102
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 212446
53.5%
Other Punctuation 93784
23.6%
Space Separator 65684
 
16.6%
Open Punctuation 9940
 
2.5%
Close Punctuation 9938
 
2.5%
Dash Punctuation 2197
 
0.6%
Uppercase Letter 2114
 
0.5%
Lowercase Letter 632
 
0.2%
Math Symbol 22
 
< 0.1%
Letter Number 18
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 15375
 
7.2%
서 11128
 
5.2%
시 10633
 
5.0%
로 10451
 
4.9%
인 10350
 
4.9%
천 10219
 
4.8%
광 10189
 
4.8%
구 10061
 
4.7%
역 10049
 
4.7%
호 8469
 
4.0%
Other values (489) 105522
49.7%
Uppercase Letter
ValueCountFrequency (%)
A 285
13.5%
B 266
12.6%
K 191
9.0%
L 185
8.8%
E 173
8.2%
S 163
7.7%
I 148
7.0%
W 131
 
6.2%
V 126
 
6.0%
C 116
 
5.5%
Other values (12) 330
15.6%
Lowercase Letter
ValueCountFrequency (%)
e 245
38.8%
a 95
 
15.0%
s 87
 
13.8%
d 86
 
13.6%
r 85
 
13.4%
b 11
 
1.7%
p 6
 
0.9%
l 5
 
0.8%
o 2
 
0.3%
t 2
 
0.3%
Other values (6) 8
 
1.3%
Other Punctuation
ValueCountFrequency (%)
* 79649
84.9%
， 13995
 
14.9%
' 89
 
0.1%
. 32
 
< 0.1%
& 14
 
< 0.1%
· 2
 
< 0.1%
/ 1
 
< 0.1%
# 1
 
< 0.1%
@ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 14
77.8%
Ⅰ 4
 
22.2%
Space Separator
ValueCountFrequency (%)
65684
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9940
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9938
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2197
100.0%
Math Symbol
ValueCountFrequency (%)
~ 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 212437
53.5%
Common 181565
45.8%
Latin 2764
 
0.7%
Han 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 15375
 
7.2%
서 11128
 
5.2%
시 10633
 
5.0%
로 10451
 
4.9%
인 10350
 
4.9%
천 10219
 
4.8%
광 10189
 
4.8%
구 10061
 
4.7%
역 10049
 
4.7%
호 8469
 
4.0%
Other values (487) 105513
49.7%
Latin
ValueCountFrequency (%)
A 285
 
10.3%
B 266
 
9.6%
e 245
 
8.9%
K 191
 
6.9%
L 185
 
6.7%
E 173
 
6.3%
S 163
 
5.9%
I 148
 
5.4%
W 131
 
4.7%
V 126
 
4.6%
Other values (30) 851
30.8%
Common
ValueCountFrequency (%)
* 79649
43.9%
65684
36.2%
， 13995
 
7.7%
( 9940
 
5.5%
) 9938
 
5.5%
- 2197
 
1.2%
' 89
 
< 0.1%
. 32
 
< 0.1%
~ 22
 
< 0.1%
& 14
 
< 0.1%
Other values (4) 5
 
< 0.1%
Han
ValueCountFrequency (%)
愛 8
88.9%
美 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 212436
53.5%
ASCII 170314
42.9%
None 13997
 
3.5%
Number Forms 18
 
< 0.1%
CJK 9
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 79649
46.8%
65684
38.6%
( 9940
 
5.8%
) 9938
 
5.8%
- 2197
 
1.3%
A 285
 
0.2%
B 266
 
0.2%
e 245
 
0.1%
K 191
 
0.1%
L 185
 
0.1%
Other values (40) 1734
 
1.0%
Hangul
ValueCountFrequency (%)
동 15375
 
7.2%
서 11128
 
5.2%
시 10633
 
5.0%
로 10451
 
4.9%
인 10350
 
4.9%
천 10219
 
4.8%
광 10189
 
4.8%
구 10061
 
4.7%
역 10049
 
4.7%
호 8469
 
4.0%
Other values (486) 105512
49.7%
None
ValueCountFrequency (%)
， 13995
> 99.9%
· 2
 
< 0.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 14
77.8%
Ⅰ 4
 
22.2%
CJK
ValueCountFrequency (%)
愛 8
88.9%
美 1
 
11.1%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

취급품목
Text

Distinct556
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T18:08:48.573350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length87
Median length84
Mean length9.2928
Min length1

Characters and Unicode

Total characters92928
Distinct characters51
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique346 ?
Unique (%)3.5%

Sample

1st row종합몰 교육/도서/완구/오락 가전 건강/식품 가구/수납용품 의류/패션/잡화/뷰티 자동차/자동차용품 기타
2nd row기타
3rd row종합몰
4th row의류/패션/잡화/뷰티
5th row기타
ValueCountFrequency (%)
종합몰 4639
30.7%
의류/패션/잡화/뷰티 3070
20.3%
기타 2151
14.2%
건강/식품 1260
 
8.3%
가구/수납용품 889
 
5.9%
교육/도서/완구/오락 739
 
4.9%
컴퓨터/사무용품 652
 
4.3%
가전 590
 
3.9%
자동차/자동차용품 513
 
3.4%
레져/여행/공연 383
 
2.5%
Other values (3) 243
 
1.6%
2024-03-14T18:08:49.670168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 15605
 
16.8%
5129
 
5.5%
합 4639
 
5.0%
종 4639
 
5.0%
몰 4639
 
5.0%
품 3537
 
3.8%
류 3070
 
3.3%
의 3070
 
3.3%
패 3070
 
3.3%
션 3070
 
3.3%
Other values (41) 42460
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 72174
77.7%
Other Punctuation 15605
 
16.8%
Space Separator 5129
 
5.5%
Dash Punctuation 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
합 4639
 
6.4%
종 4639
 
6.4%
몰 4639
 
6.4%
품 3537
 
4.9%
류 3070
 
4.3%
의 3070
 
4.3%
패 3070
 
4.3%
션 3070
 
4.3%
잡 3070
 
4.3%
뷰 3070
 
4.3%
Other values (38) 36300
50.3%
Other Punctuation
ValueCountFrequency (%)
/ 15605
100.0%
Space Separator
ValueCountFrequency (%)
5129
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 72174
77.7%
Common 20754
 
22.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
합 4639
 
6.4%
종 4639
 
6.4%
몰 4639
 
6.4%
품 3537
 
4.9%
류 3070
 
4.3%
의 3070
 
4.3%
패 3070
 
4.3%
션 3070
 
4.3%
잡 3070
 
4.3%
뷰 3070
 
4.3%
Other values (38) 36300
50.3%
Common
ValueCountFrequency (%)
/ 15605
75.2%
5129
 
24.7%
- 20
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 72174
77.7%
ASCII 20754
 
22.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 15605
75.2%
5129
 
24.7%
- 20
 
0.1%
Hangul
ValueCountFrequency (%)
합 4639
 
6.4%
종 4639
 
6.4%
몰 4639
 
6.4%
품 3537
 
4.9%
류 3070
 
4.3%
의 3070
 
4.3%
패 3070
 
4.3%
션 3070
 
4.3%
잡 3070
 
4.3%
뷰 3070
 
4.3%
Other values (38) 36300
50.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-02-01 00:00:00
Maximum2024-02-01 00:00:00
2024-03-14T18:08:50.008926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:08:50.306265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-14T18:06:18.545913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-03-14T18:08:39.472387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T18:08:39.839091image/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.

Sample

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