Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells3275
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory126.0 B

Variable types

Numeric5
Text4
DateTime2
Categorical3

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-1170/S/1/datasetView.do

Alerts

시장유형 구분(시장/마트) 코드 is highly overall correlated with 시장유형 구분(시장/마트) 이름High correlation
시장유형 구분(시장/마트) 이름 is highly overall correlated with 시장유형 구분(시장/마트) 코드High correlation
시장/마트 번호 is highly overall correlated with 자치구 코드 and 1 other fieldsHigh correlation
자치구 코드 is highly overall correlated with 시장/마트 번호 and 1 other fieldsHigh correlation
자치구 이름 is highly overall correlated with 시장/마트 번호 and 1 other fieldsHigh correlation
비고 has 3275 (32.8%) missing valuesMissing
일련번호 has unique valuesUnique
가격(원) has 148 (1.5%) zerosZeros

Reproduction

Analysis started2024-05-11 06:36:19.367847
Analysis finished2024-05-11 06:36:26.731779
Duration7.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1267149
Minimum1188922
Maximum1348746
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:36:26.876921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1188922
5-th percentile1189971.9
Q11231453
median1261824.5
Q31312350.8
95-th percentile1344746.2
Maximum1348746
Range159824
Interquartile range (IQR)80897.75

Descriptive statistics

Standard deviation48848.574
Coefficient of variation (CV)0.038549984
Kurtosis-1.2163851
Mean1267149
Median Absolute Deviation (MAD)44294.5
Skewness-0.025515173
Sum1.267149 × 1010
Variance2.3861832 × 109
MonotonicityNot monotonic
2024-05-11T15:36:27.106413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1189186 1
 
< 0.1%
1330594 1
 
< 0.1%
1231460 1
 
< 0.1%
1190268 1
 
< 0.1%
1232696 1
 
< 0.1%
1301208 1
 
< 0.1%
1329980 1
 
< 0.1%
1274537 1
 
< 0.1%
1330044 1
 
< 0.1%
1260436 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1188922 1
< 0.1%
1188923 1
< 0.1%
1188927 1
< 0.1%
1188928 1
< 0.1%
1188931 1
< 0.1%
1188933 1
< 0.1%
1188935 1
< 0.1%
1188941 1
< 0.1%
1188946 1
< 0.1%
1188948 1
< 0.1%
ValueCountFrequency (%)
1348746 1
< 0.1%
1348742 1
< 0.1%
1348740 1
< 0.1%
1348738 1
< 0.1%
1348737 1
< 0.1%
1348736 1
< 0.1%
1348735 1
< 0.1%
1348734 1
< 0.1%
1348733 1
< 0.1%
1348730 1
< 0.1%

시장/마트 번호
Real number (ℝ)

HIGH CORRELATION 

Distinct102
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean102.0199
Minimum1
Maximum224
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:36:27.305495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11
Q145
median92
Q3145
95-th percentile219
Maximum224
Range223
Interquartile range (IQR)100

Descriptive statistics

Standard deviation67.015789
Coefficient of variation (CV)0.65688938
Kurtosis-0.92391659
Mean102.0199
Median Absolute Deviation (MAD)48
Skewness0.40333145
Sum1020199
Variance4491.116
MonotonicityNot monotonic
2024-05-11T15:36:27.482149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
133 116
 
1.2%
40 116
 
1.2%
62 114
 
1.1%
222 114
 
1.1%
223 112
 
1.1%
91 111
 
1.1%
44 111
 
1.1%
217 111
 
1.1%
16 110
 
1.1%
11 109
 
1.1%
Other values (92) 8876
88.8%
ValueCountFrequency (%)
1 93
0.9%
2 88
0.9%
6 102
1.0%
8 100
1.0%
10 93
0.9%
11 109
1.1%
13 107
1.1%
14 104
1.0%
15 86
0.9%
16 110
1.1%
ValueCountFrequency (%)
224 22
 
0.2%
223 112
1.1%
222 114
1.1%
221 103
1.0%
220 85
0.9%
219 101
1.0%
218 97
1.0%
217 111
1.1%
216 99
1.0%
215 100
1.0%

시장/마트 이름
Text

Distinct102
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:36:27.746517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.251
Min length4

Characters and Unicode

Total characters62510
Distinct characters141
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

Unique0 ?
Unique (%)0.0%

Sample

1st row이마트왕십리점
2nd row홈플러스독산점
3rd row롯데마트서울역점
4th row홈플러스영등포점
5th row롯데마트강변점
ValueCountFrequency (%)
원당종합시장 116
 
1.2%
홈플러스등촌점 116
 
1.2%
후암시장 114
 
1.1%
홈플러스독산점 114
 
1.1%
홈플러스목동점 112
 
1.1%
동원시장 111
 
1.1%
이마트역삼점 111
 
1.1%
방림시장 111
 
1.1%
현대백화점미아점 110
 
1.1%
남대문시장 109
 
1.1%
Other values (92) 8876
88.8%
2024-05-11T15:36:28.236726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 5861
 
9.4%
장 5163
 
8.3%
시 5072
 
8.1%
마 2164
 
3.5%
트 1952
 
3.1%
이 1677
 
2.7%
화 1567
 
2.5%
백 1366
 
2.2%
동 1344
 
2.2%
스 1233
 
2.0%
Other values (131) 35111
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61373
98.2%
Decimal Number 715
 
1.1%
Close Punctuation 211
 
0.3%
Open Punctuation 211
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 5861
 
9.5%
장 5163
 
8.4%
시 5072
 
8.3%
마 2164
 
3.5%
트 1952
 
3.2%
이 1677
 
2.7%
화 1567
 
2.6%
백 1366
 
2.2%
동 1344
 
2.2%
스 1233
 
2.0%
Other values (124) 33974
55.4%
Decimal Number
ValueCountFrequency (%)
1 207
29.0%
0 200
28.0%
3 104
14.5%
4 104
14.5%
2 100
14.0%
Close Punctuation
ValueCountFrequency (%)
) 211
100.0%
Open Punctuation
ValueCountFrequency (%)
( 211
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61373
98.2%
Common 1137
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 5861
 
9.5%
장 5163
 
8.4%
시 5072
 
8.3%
마 2164
 
3.5%
트 1952
 
3.2%
이 1677
 
2.7%
화 1567
 
2.6%
백 1366
 
2.2%
동 1344
 
2.2%
스 1233
 
2.0%
Other values (124) 33974
55.4%
Common
ValueCountFrequency (%)
) 211
18.6%
( 211
18.6%
1 207
18.2%
0 200
17.6%
3 104
9.1%
4 104
9.1%
2 100
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61373
98.2%
ASCII 1137
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 5861
 
9.5%
장 5163
 
8.4%
시 5072
 
8.3%
마 2164
 
3.5%
트 1952
 
3.2%
이 1677
 
2.7%
화 1567
 
2.6%
백 1366
 
2.2%
동 1344
 
2.2%
스 1233
 
2.0%
Other values (124) 33974
55.4%
ASCII
ValueCountFrequency (%)
) 211
18.6%
( 211
18.6%
1 207
18.2%
0 200
17.6%
3 104
9.1%
4 104
9.1%
2 100
8.8%

품목 번호
Real number (ℝ)

Distinct90
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean225.0214
Minimum13
Maximum321
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:36:28.423269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile24
Q1152
median266
Q3308
95-th percentile320
Maximum321
Range308
Interquartile range (IQR)156

Descriptive statistics

Standard deviation101.8542
Coefficient of variation (CV)0.45264227
Kurtosis-0.71516683
Mean225.0214
Median Absolute Deviation (MAD)44
Skewness-0.89196123
Sum2250214
Variance10374.278
MonotonicityNot monotonic
2024-05-11T15:36:28.661173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
320 579
 
5.8%
171 548
 
5.5%
311 472
 
4.7%
307 456
 
4.6%
58 455
 
4.5%
309 440
 
4.4%
305 423
 
4.2%
283 410
 
4.1%
306 405
 
4.0%
310 390
 
3.9%
Other values (80) 5422
54.2%
ValueCountFrequency (%)
13 29
 
0.3%
17 8
 
0.1%
18 136
1.4%
22 102
1.0%
23 224
2.2%
24 140
1.4%
25 114
1.1%
26 50
 
0.5%
27 57
 
0.6%
28 90
0.9%
ValueCountFrequency (%)
321 1
 
< 0.1%
320 579
5.8%
318 13
 
0.1%
316 35
 
0.4%
315 25
 
0.2%
314 14
 
0.1%
312 330
3.3%
311 472
4.7%
310 390
3.9%
309 440
4.4%

품목 이름
Text

Distinct82
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:36:29.017013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length8.0197
Min length1

Characters and Unicode

Total characters80197
Distinct characters88
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row조기(국산,생물)
2nd row명태(러시아,냉동)
3rd row쇠고기(한우,불고기)
4th row쇠고기(한우1등급)
5th row양파
ValueCountFrequency (%)
달걀(30개 579
 
5.3%
달걀(10개 548
 
5.0%
오이(다다기 471
 
4.3%
배(신고 458
 
4.2%
배추(2.5~3kg 456
 
4.2%
쇠고기(한우,불고기 455
 
4.2%
사과(부사 451
 
4.2%
양파(1.5kg망 440
 
4.1%
300g 423
 
3.9%
돼지고기(생삼겹살 418
 
3.9%
Other values (73) 6153
56.7%
2024-05-11T15:36:29.625655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 8508
 
10.6%
) 8508
 
10.6%
0 3627
 
4.5%
, 3516
 
4.4%
고 3327
 
4.1%
기 3261
 
4.1%
g 2471
 
3.1%
1 1825
 
2.3%
산 1805
 
2.3%
3 1506
 
1.9%
Other values (78) 41843
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44768
55.8%
Decimal Number 8796
 
11.0%
Open Punctuation 8508
 
10.6%
Close Punctuation 8508
 
10.6%
Other Punctuation 4412
 
5.5%
Lowercase Letter 3897
 
4.9%
Space Separator 852
 
1.1%
Math Symbol 456
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 3327
 
7.4%
기 3261
 
7.3%
산 1805
 
4.0%
생 1262
 
2.8%
국 1252
 
2.8%
동 1228
 
2.7%
냉 1189
 
2.7%
추 1182
 
2.6%
어 1172
 
2.6%
걀 1172
 
2.6%
Other values (61) 27918
62.4%
Decimal Number
ValueCountFrequency (%)
0 3627
41.2%
1 1825
20.7%
3 1506
17.1%
5 922
 
10.5%
2 486
 
5.5%
6 405
 
4.6%
4 25
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
g 2471
63.4%
k 1252
32.1%
m 87
 
2.2%
c 87
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 3516
79.7%
. 896
 
20.3%
Open Punctuation
ValueCountFrequency (%)
( 8508
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8508
100.0%
Space Separator
ValueCountFrequency (%)
852
100.0%
Math Symbol
ValueCountFrequency (%)
~ 456
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44768
55.8%
Common 31532
39.3%
Latin 3897
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 3327
 
7.4%
기 3261
 
7.3%
산 1805
 
4.0%
생 1262
 
2.8%
국 1252
 
2.8%
동 1228
 
2.7%
냉 1189
 
2.7%
추 1182
 
2.6%
어 1172
 
2.6%
걀 1172
 
2.6%
Other values (61) 27918
62.4%
Common
ValueCountFrequency (%)
( 8508
27.0%
) 8508
27.0%
0 3627
11.5%
, 3516
11.2%
1 1825
 
5.8%
3 1506
 
4.8%
5 922
 
2.9%
. 896
 
2.8%
852
 
2.7%
2 486
 
1.5%
Other values (3) 886
 
2.8%
Latin
ValueCountFrequency (%)
g 2471
63.4%
k 1252
32.1%
m 87
 
2.2%
c 87
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44768
55.8%
ASCII 35429
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 8508
24.0%
) 8508
24.0%
0 3627
10.2%
, 3516
9.9%
g 2471
 
7.0%
1 1825
 
5.2%
3 1506
 
4.3%
k 1252
 
3.5%
5 922
 
2.6%
. 896
 
2.5%
Other values (7) 2398
 
6.8%
Hangul
ValueCountFrequency (%)
고 3327
 
7.4%
기 3261
 
7.3%
산 1805
 
4.0%
생 1262
 
2.8%
국 1252
 
2.8%
동 1228
 
2.7%
냉 1189
 
2.7%
추 1182
 
2.6%
어 1172
 
2.6%
걀 1172
 
2.6%
Other values (61) 27918
62.4%

실판매규격
Text

Distinct577
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:36:30.260325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length4.2165
Min length1

Characters and Unicode

Total characters42165
Distinct characters85
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique280 ?
Unique (%)2.8%

Sample

1st row1마리
2nd row1마리(45cm)
3rd row1근
4th row600g
5th row1망2.0kg
ValueCountFrequency (%)
1개 2588
24.4%
1마리 1453
13.7%
600g 960
 
9.0%
30개 503
 
4.7%
10개 473
 
4.5%
100g 472
 
4.4%
1포기 433
 
4.1%
1망 295
 
2.8%
1마리(25cm 249
 
2.3%
1 168
 
1.6%
Other values (401) 3033
28.5%
2024-05-11T15:36:31.112084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8872
21.0%
0 5441
12.9%
개 4011
9.5%
g 2705
 
6.4%
리 2703
 
6.4%
마 2703
 
6.4%
( 1855
 
4.4%
) 1840
 
4.4%
6 1245
 
3.0%
m 1227
 
2.9%
Other values (75) 9563
22.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18950
44.9%
Other Letter 12046
28.6%
Lowercase Letter 5879
 
13.9%
Open Punctuation 1884
 
4.5%
Close Punctuation 1869
 
4.4%
Space Separator 964
 
2.3%
Other Punctuation 458
 
1.1%
Math Symbol 75
 
0.2%
Uppercase Letter 33
 
0.1%
Dash Punctuation 3
 
< 0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 4011
33.3%
리 2703
22.4%
마 2703
22.4%
기 495
 
4.1%
포 493
 
4.1%
망 430
 
3.6%
급 186
 
1.5%
란 167
 
1.4%
등 164
 
1.4%
특 128
 
1.1%
Other values (36) 566
 
4.7%
Decimal Number
ValueCountFrequency (%)
1 8872
46.8%
0 5441
28.7%
6 1245
 
6.6%
3 1074
 
5.7%
5 919
 
4.8%
2 850
 
4.5%
4 278
 
1.5%
8 177
 
0.9%
7 52
 
0.3%
9 42
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
g 2705
46.0%
m 1227
20.9%
c 1209
20.6%
k 730
 
12.4%
q 2
 
< 0.1%
a 2
 
< 0.1%
f 2
 
< 0.1%
l 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 386
84.3%
, 69
 
15.1%
* 2
 
0.4%
! 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
K 11
33.3%
G 11
33.3%
C 6
18.2%
M 5
15.2%
Open Punctuation
ValueCountFrequency (%)
( 1855
98.5%
[ 25
 
1.3%
{ 4
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 1840
98.4%
] 25
 
1.3%
} 4
 
0.2%
Math Symbol
ValueCountFrequency (%)
+ 72
96.0%
~ 3
 
4.0%
Space Separator
ValueCountFrequency (%)
964
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Format
ValueCountFrequency (%)
­ 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
¸ 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24207
57.4%
Hangul 12046
28.6%
Latin 5912
 
14.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 4011
33.3%
리 2703
22.4%
마 2703
22.4%
기 495
 
4.1%
포 493
 
4.1%
망 430
 
3.6%
급 186
 
1.5%
란 167
 
1.4%
등 164
 
1.4%
특 128
 
1.1%
Other values (36) 566
 
4.7%
Common
ValueCountFrequency (%)
1 8872
36.7%
0 5441
22.5%
( 1855
 
7.7%
) 1840
 
7.6%
6 1245
 
5.1%
3 1074
 
4.4%
964
 
4.0%
5 919
 
3.8%
2 850
 
3.5%
. 386
 
1.6%
Other values (17) 761
 
3.1%
Latin
ValueCountFrequency (%)
g 2705
45.8%
m 1227
20.8%
c 1209
20.4%
k 730
 
12.3%
K 11
 
0.2%
G 11
 
0.2%
C 6
 
0.1%
M 5
 
0.1%
q 2
 
< 0.1%
a 2
 
< 0.1%
Other values (2) 4
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30116
71.4%
Hangul 12045
 
28.6%
None 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8872
29.5%
0 5441
18.1%
g 2705
 
9.0%
( 1855
 
6.2%
) 1840
 
6.1%
6 1245
 
4.1%
m 1227
 
4.1%
c 1209
 
4.0%
3 1074
 
3.6%
964
 
3.2%
Other values (27) 3684
12.2%
Hangul
ValueCountFrequency (%)
개 4011
33.3%
리 2703
22.4%
마 2703
22.4%
기 495
 
4.1%
포 493
 
4.1%
망 430
 
3.6%
급 186
 
1.5%
란 167
 
1.4%
등 164
 
1.4%
특 128
 
1.1%
Other values (35) 565
 
4.7%
None
ValueCountFrequency (%)
­ 2
66.7%
¸ 1
33.3%
Compat Jamo
ValueCountFrequency (%)
ㅏ 1
100.0%

가격(원)
Real number (ℝ)

ZEROS 

Distinct888
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5315.7153
Minimum0
Maximum53400
Zeros148
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:36:31.422661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile600
Q11980
median3000
Q35000
95-th percentile23940
Maximum53400
Range53400
Interquartile range (IQR)3020

Descriptive statistics

Standard deviation7011.9845
Coefficient of variation (CV)1.3191046
Kurtosis10.076102
Mean5315.7153
Median Absolute Deviation (MAD)1500
Skewness3.0217155
Sum53157153
Variance49167926
MonotonicityNot monotonic
2024-05-11T15:36:32.068302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3000 602
 
6.0%
2000 547
 
5.5%
2500 445
 
4.5%
4000 324
 
3.2%
5000 319
 
3.2%
3500 271
 
2.7%
1500 269
 
2.7%
1000 242
 
2.4%
500 201
 
2.0%
6000 159
 
1.6%
Other values (878) 6621
66.2%
ValueCountFrequency (%)
0 148
1.5%
200 4
 
< 0.1%
250 5
 
0.1%
300 2
 
< 0.1%
330 4
 
< 0.1%
333 7
 
0.1%
350 2
 
< 0.1%
360 1
 
< 0.1%
375 2
 
< 0.1%
380 1
 
< 0.1%
ValueCountFrequency (%)
53400 1
 
< 0.1%
52800 4
< 0.1%
51000 6
0.1%
50001 1
 
< 0.1%
47400 5
0.1%
46800 2
 
< 0.1%
46200 2
 
< 0.1%
45000 5
0.1%
44950 1
 
< 0.1%
44400 1
 
< 0.1%

년도-월
Date

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-01-01 00:00:00
Maximum2018-12-01 00:00:00
2024-05-11T15:36:32.266900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:32.446037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

비고
Text

MISSING 

Distinct2536
Distinct (%)37.7%
Missing3275
Missing (%)32.8%
Memory size156.2 KiB
2024-05-11T15:36:32.895548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length30
Mean length5.5924164
Min length1

Characters and Unicode

Total characters37609
Distinct characters394
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

Unique1888 ?
Unique (%)28.1%

Sample

1st row국내산 참조기제주
2nd row러시아
3rd row안심한우100/5390
4th row국산
5th row6개10000홍로
ValueCountFrequency (%)
국산 821
 
9.8%
국내산 519
 
6.2%
국내 250
 
3.0%
100g 165
 
2.0%
러시아 133
 
1.6%
하림 128
 
1.5%
무안 107
 
1.3%
특란 98
 
1.2%
3개 83
 
1.0%
제주 81
 
1.0%
Other values (2238) 6023
71.6%
2024-05-11T15:36:33.709512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4968
 
13.2%
국 1968
 
5.2%
1924
 
5.1%
산 1817
 
4.8%
1 1514
 
4.0%
원 1265
 
3.4%
9 892
 
2.4%
내 867
 
2.3%
2 853
 
2.3%
5 750
 
2.0%
Other values (384) 20791
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21146
56.2%
Decimal Number 11306
30.1%
Space Separator 1924
 
5.1%
Other Punctuation 1022
 
2.7%
Lowercase Letter 915
 
2.4%
Close Punctuation 554
 
1.5%
Open Punctuation 552
 
1.5%
Uppercase Letter 86
 
0.2%
Dash Punctuation 52
 
0.1%
Math Symbol 46
 
0.1%
Other values (2) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 1968
 
9.3%
산 1817
 
8.6%
원 1265
 
6.0%
내 867
 
4.1%
개 701
 
3.3%
란 575
 
2.7%
리 337
 
1.6%
부 335
 
1.6%
마 332
 
1.6%
기 308
 
1.5%
Other values (330) 12641
59.8%
Uppercase Letter
ValueCountFrequency (%)
P 15
17.4%
L 14
16.3%
C 14
16.3%
K 9
10.5%
A 9
10.5%
G 5
 
5.8%
J 5
 
5.8%
F 3
 
3.5%
S 2
 
2.3%
V 2
 
2.3%
Other values (8) 8
9.3%
Lowercase Letter
ValueCountFrequency (%)
g 632
69.1%
c 100
 
10.9%
m 94
 
10.3%
k 59
 
6.4%
p 15
 
1.6%
l 6
 
0.7%
a 2
 
0.2%
e 2
 
0.2%
s 1
 
0.1%
d 1
 
0.1%
Other values (3) 3
 
0.3%
Decimal Number
ValueCountFrequency (%)
0 4968
43.9%
1 1514
 
13.4%
9 892
 
7.9%
2 853
 
7.5%
5 750
 
6.6%
3 724
 
6.4%
8 572
 
5.1%
4 464
 
4.1%
6 303
 
2.7%
7 266
 
2.4%
Other Punctuation
ValueCountFrequency (%)
, 738
72.2%
. 211
 
20.6%
/ 37
 
3.6%
\ 34
 
3.3%
% 2
 
0.2%
Math Symbol
ValueCountFrequency (%)
+ 37
80.4%
~ 9
 
19.6%
Space Separator
ValueCountFrequency (%)
1924
100.0%
Close Punctuation
ValueCountFrequency (%)
) 554
100.0%
Open Punctuation
ValueCountFrequency (%)
( 552
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21132
56.2%
Common 15462
41.1%
Latin 1001
 
2.7%
Han 14
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 1968
 
9.3%
산 1817
 
8.6%
원 1265
 
6.0%
내 867
 
4.1%
개 701
 
3.3%
란 575
 
2.7%
리 337
 
1.6%
부 335
 
1.6%
마 332
 
1.6%
기 308
 
1.5%
Other values (327) 12627
59.8%
Latin
ValueCountFrequency (%)
g 632
63.1%
c 100
 
10.0%
m 94
 
9.4%
k 59
 
5.9%
p 15
 
1.5%
P 15
 
1.5%
L 14
 
1.4%
C 14
 
1.4%
K 9
 
0.9%
A 9
 
0.9%
Other values (21) 40
 
4.0%
Common
ValueCountFrequency (%)
0 4968
32.1%
1924
 
12.4%
1 1514
 
9.8%
9 892
 
5.8%
2 853
 
5.5%
5 750
 
4.9%
, 738
 
4.8%
3 724
 
4.7%
8 572
 
3.7%
) 554
 
3.6%
Other values (13) 1973
 
12.8%
Han
ValueCountFrequency (%)
大 8
57.1%
小 5
35.7%
中 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21131
56.2%
ASCII 16463
43.8%
CJK 14
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4968
30.2%
1924
 
11.7%
1 1514
 
9.2%
9 892
 
5.4%
2 853
 
5.2%
5 750
 
4.6%
, 738
 
4.5%
3 724
 
4.4%
g 632
 
3.8%
8 572
 
3.5%
Other values (44) 2896
17.6%
Hangul
ValueCountFrequency (%)
국 1968
 
9.3%
산 1817
 
8.6%
원 1265
 
6.0%
내 867
 
4.1%
개 701
 
3.3%
란 575
 
2.7%
리 337
 
1.6%
부 335
 
1.6%
마 332
 
1.6%
기 308
 
1.5%
Other values (326) 12626
59.8%
CJK
ValueCountFrequency (%)
大 8
57.1%
小 5
35.7%
中 1
 
7.1%
Compat Jamo
ValueCountFrequency (%)
ㅎ 1
100.0%

시장유형 구분(시장/마트) 코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
5031 
1
4969 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 5031
50.3%
1 4969
49.7%

Length

2024-05-11T15:36:33.989600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:34.164772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 5031
50.3%
1 4969
49.7%

시장유형 구분(시장/마트) 이름
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대형마트
5031 
전통시장
4969 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대형마트 5031
50.3%
전통시장 4969
49.7%

Length

2024-05-11T15:36:34.362870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:34.541746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대형마트 5031
50.3%
전통시장 4969
49.7%

자치구 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean418667
Minimum110000
Maximum740000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:36:34.737298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110000
5-th percentile140000
Q1260000
median410000
Q3560000
95-th percentile710000
Maximum740000
Range630000
Interquartile range (IQR)300000

Descriptive statistics

Standard deviation185158.94
Coefficient of variation (CV)0.44225825
Kurtosis-1.2212069
Mean418667
Median Absolute Deviation (MAD)150000
Skewness0.0890176
Sum4.18667 × 109
Variance3.4283831 × 1010
MonotonicityNot monotonic
2024-05-11T15:36:35.010586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
140000 587
 
5.9%
620000 521
 
5.2%
560000 498
 
5.0%
260000 426
 
4.3%
680000 418
 
4.2%
305000 417
 
4.2%
530000 416
 
4.2%
380000 414
 
4.1%
500000 410
 
4.1%
470000 409
 
4.1%
Other values (15) 5484
54.8%
ValueCountFrequency (%)
110000 183
 
1.8%
140000 587
5.9%
170000 406
4.1%
200000 381
3.8%
215000 400
4.0%
230000 392
3.9%
260000 426
4.3%
290000 407
4.1%
305000 417
4.2%
320000 393
3.9%
ValueCountFrequency (%)
740000 395
4.0%
710000 401
4.0%
680000 418
4.2%
650000 401
4.0%
620000 521
5.2%
590000 181
 
1.8%
560000 498
5.0%
545000 403
4.0%
530000 416
4.2%
500000 410
4.1%

자치구 이름
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
중구
 
587
관악구
 
521
영등포구
 
498
중랑구
 
426
강남구
 
418
Other values (20)
7550 

Length

Max length4
Median length3
Mean length3.0671
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row성동구
2nd row금천구
3rd row중구
4th row영등포구
5th row광진구

Common Values

ValueCountFrequency (%)
중구 587
 
5.9%
관악구 521
 
5.2%
영등포구 498
 
5.0%
중랑구 426
 
4.3%
강남구 418
 
4.2%
강북구 417
 
4.2%
구로구 416
 
4.2%
은평구 414
 
4.1%
강서구 410
 
4.1%
양천구 409
 
4.1%
Other values (15) 5484
54.8%

Length

2024-05-11T15:36:35.285444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
중구 587
 
5.9%
관악구 521
 
5.2%
영등포구 498
 
5.0%
중랑구 426
 
4.3%
강남구 418
 
4.2%
강북구 417
 
4.2%
구로구 416
 
4.2%
은평구 414
 
4.1%
강서구 410
 
4.1%
양천구 409
 
4.1%
Other values (15) 5484
54.8%

점검일자
Date

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-01-28 00:00:00
Maximum2018-12-31 00:00:00
2024-05-11T15:36:35.515599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:35.780023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)

Interactions

2024-05-11T15:36:25.333878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:21.801383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:22.936453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:23.761511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:24.512243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:25.520422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:22.037481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:23.117651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:23.903040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:24.682221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:25.689172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:22.271937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:23.303585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:24.038667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:24.823086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:25.872783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:22.527828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:23.489080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:24.197444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:25.009438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:26.043700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:22.722430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:23.624406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:24.356383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:25.179410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:36:35.969135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호시장/마트 번호품목 번호품목 이름가격(원)년도-월시장유형 구분(시장/마트) 코드시장유형 구분(시장/마트) 이름자치구 코드자치구 이름점검일자
일련번호1.0000.0590.0300.0180.0600.9950.0000.0000.1320.1551.000
시장/마트 번호0.0591.0000.1420.4600.0780.0000.1870.1870.8180.9480.450
품목 번호0.0300.1421.0000.9950.7660.0000.1030.1030.2680.3470.000
품목 이름0.0180.4600.9951.0000.8290.0000.2190.2190.5710.7160.129
가격(원)0.0600.0780.7660.8291.0000.0560.2000.2000.1530.2060.103
년도-월0.9950.0000.0000.0000.0561.0000.0000.0000.0000.0001.000
시장유형 구분(시장/마트) 코드0.0000.1870.1030.2190.2000.0001.0001.0000.0650.2150.071
시장유형 구분(시장/마트) 이름0.0000.1870.1030.2190.2000.0001.0001.0000.0650.2150.071
자치구 코드0.1320.8180.2680.5710.1530.0000.0650.0651.0001.0000.565
자치구 이름0.1550.9480.3470.7160.2060.0000.2150.2151.0001.0000.730
점검일자1.0000.4500.0000.1290.1031.0000.0710.0710.5650.7301.000
2024-05-11T15:36:36.244392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시장유형 구분(시장/마트) 코드시장유형 구분(시장/마트) 이름자치구 이름
시장유형 구분(시장/마트) 코드1.0001.0000.186
시장유형 구분(시장/마트) 이름1.0001.0000.186
자치구 이름0.1860.1861.000
2024-05-11T15:36:36.431393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호시장/마트 번호품목 번호가격(원)자치구 코드시장유형 구분(시장/마트) 코드시장유형 구분(시장/마트) 이름자치구 이름
일련번호1.0000.0370.016-0.0180.0560.0000.0000.055
시장/마트 번호0.0371.0000.064-0.0010.5040.1870.1870.763
품목 번호0.0160.0641.000-0.2410.0020.0790.0790.129
가격(원)-0.018-0.001-0.2411.0000.0080.1540.1540.074
자치구 코드0.0560.5040.0020.0081.0000.0190.0190.999
시장유형 구분(시장/마트) 코드0.0000.1870.0790.1540.0191.0001.0000.186
시장유형 구분(시장/마트) 이름0.0000.1870.0790.1540.0191.0001.0000.186
자치구 이름0.0550.7630.1290.0740.9990.1860.1861.000

Missing values

2024-05-11T15:36:26.267562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:36:26.592493image/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

일련번호시장/마트 번호시장/마트 이름품목 번호품목 이름실판매규격가격(원)년도-월비고시장유형 구분(시장/마트) 코드시장유형 구분(시장/마트) 이름자치구 코드자치구 이름점검일자
18965118918674이마트왕십리점136조기(국산,생물)1마리19802018-01국내산 참조기제주2대형마트200000성동구2018-01-29
96671275695222홈플러스독산점152명태(러시아,냉동)1마리(45cm)39902018-07러시아2대형마트545000금천구2018-07-30
520713004248롯데마트서울역점58쇠고기(한우,불고기)1근310002018-09<NA>2대형마트140000중구2018-09-27
19827119018421홈플러스영등포점131쇠고기(한우1등급)600g323402018-01안심한우100/53902대형마트560000영등포구2018-01-29
8603127461482롯데마트강변점24양파1망2.0kg28002018-07국산2대형마트215000광진구2018-07-29
7103128909431인왕시장305사과(부사, 300g)1개16672018-086개10000홍로1전통시장410000서대문구2018-08-30
6855128884655광장시장119호박(인큐베이터)1 개15002018-08<NA>1전통시장110000종로구2018-08-30
20082119043945롯데백화점강남점58쇠고기(한우,불고기)600g270002018-01삼도명가2대형마트680000강남구2018-01-28
279134429511남대문시장118호박(인큐베이터),중간1개14502018-12<NA>1전통시장140000중구2018-12-31
64351301720146방이시장320달걀(30개)30개45002018-09<NA>1전통시장710000송파구2018-09-27
일련번호시장/마트 번호시장/마트 이름품목 번호품목 이름실판매규격가격(원)년도-월비고시장유형 구분(시장/마트) 코드시장유형 구분(시장/마트) 이름자치구 코드자치구 이름점검일자
17510120134715이마트미아점25무1개26802018-02국내2대형마트290000성북구2018-02-26
1246212467362신세계백화점309양파(1.5kg망)1망44702018-05<NA>2대형마트140000중구2018-05-31
113091260695151암사종합시장312애호박1개6002018-06<NA>1전통시장740000강동구2018-06-28
12145124641980이마트자양점283닭고기(육계)1마리46002018-05하림2대형마트215000광진구2018-05-30
95051275533219대조시장310상추(100g)100g6002018-07<NA>1전통시장380000은평구2018-07-30
15959121654138송화시장266고등어(생물,국산)1마리(22cm)30002018-03부산1전통시장500000강서구2018-03-29
6727130208013돈암제일시장254오징어(생물,국산)1마리25002018-09국내 2마리 5,000원1전통시장290000성북구2018-09-27
18252120217433현대백화점신촌점265명태(생물,수입산)1마리 (45cm)120002018-02생태 카나다2대형마트410000서대문구2018-02-26
161021216684206하나로클럽미아점311오이(다다기)1개9202018-03<NA>2대형마트305000강북구2018-03-29
10303125967356롯데백화점309양파(1.5kg망)1망55002018-06<NA>2대형마트140000중구2018-06-28