Overview

Dataset statistics

Number of variables28
Number of observations1835
Missing cells5435
Missing cells (%)10.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory412.3 KiB
Average record size in memory230.1 B

Variable types

Text6
Categorical8
Numeric5
DateTime9

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>자료실) 각 기관에서 등록한 표준데이터를 취합하여 제공하기 때문에 갱신주기는 개별 파일마다 다릅니다.(기관에서 등록한 데이터를 취합한 것으로 개별 파일별 갱신시점이 다름)
Author지방자치단체
URLhttps://www.data.go.kr/data/15034531/standard.do

Alerts

할인율 is highly imbalanced (50.1%)Imbalance
할인금액 is highly imbalanced (84.1%)Imbalance
소재지지번주소 has 1044 (56.9%) missing valuesMissing
할인대상서비스명 has 900 (49.0%) missing valuesMissing
할인부가정보 has 1663 (90.6%) missing valuesMissing
경로우대업소해제일자 has 1824 (99.4%) missing valuesMissing

Reproduction

Analysis started2024-04-29 23:35:45.598355
Analysis finished2024-04-29 23:35:46.880350
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct1731
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
2024-04-30T08:35:47.056986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length5.6768392
Min length1

Characters and Unicode

Total characters10417
Distinct characters670
Distinct categories9 ?
Distinct scripts5 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1648 ?
Unique (%)89.8%

Sample

1st row허당국시
2nd row카시아미용실
3rd row일성향균크리닝
4th row해남 진성옥
5th row열린공인중개사
ValueCountFrequency (%)
미용실 21
 
1.0%
헤어 9
 
0.4%
안경원 8
 
0.4%
헤어샵 6
 
0.3%
대성이용소 5
 
0.2%
안경 5
 
0.2%
정미용실 5
 
0.2%
목욕탕 4
 
0.2%
현대이용소 4
 
0.2%
월드사우나 4
 
0.2%
Other values (1890) 2009
96.6%
2024-04-30T08:35:47.413374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
용 513
 
4.9%
이 463
 
4.4%
어 383
 
3.7%
헤 363
 
3.5%
미 299
 
2.9%
소 284
 
2.7%
245
 
2.4%
실 216
 
2.1%
원 203
 
1.9%
리 165
 
1.6%
Other values (660) 7283
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9885
94.9%
Space Separator 245
 
2.4%
Uppercase Letter 78
 
0.7%
Lowercase Letter 59
 
0.6%
Decimal Number 54
 
0.5%
Open Punctuation 38
 
0.4%
Close Punctuation 38
 
0.4%
Other Punctuation 15
 
0.1%
Other Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 513
 
5.2%
이 463
 
4.7%
어 383
 
3.9%
헤 363
 
3.7%
미 299
 
3.0%
소 284
 
2.9%
실 216
 
2.2%
원 203
 
2.1%
리 165
 
1.7%
경 153
 
1.5%
Other values (604) 6843
69.2%
Uppercase Letter
ValueCountFrequency (%)
S 9
11.5%
H 7
 
9.0%
A 7
 
9.0%
K 6
 
7.7%
J 6
 
7.7%
M 6
 
7.7%
B 5
 
6.4%
Y 4
 
5.1%
C 4
 
5.1%
N 3
 
3.8%
Other values (12) 21
26.9%
Lowercase Letter
ValueCountFrequency (%)
e 10
16.9%
s 6
10.2%
a 6
10.2%
l 5
8.5%
o 5
8.5%
r 5
8.5%
t 4
 
6.8%
u 4
 
6.8%
i 3
 
5.1%
n 3
 
5.1%
Other values (7) 8
13.6%
Decimal Number
ValueCountFrequency (%)
0 18
33.3%
1 11
20.4%
2 10
18.5%
8 6
 
11.1%
4 4
 
7.4%
5 2
 
3.7%
9 1
 
1.9%
6 1
 
1.9%
3 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 10
66.7%
? 2
 
13.3%
& 2
 
13.3%
, 1
 
6.7%
Space Separator
ValueCountFrequency (%)
245
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9886
94.9%
Common 390
 
3.7%
Latin 136
 
1.3%
Han 4
 
< 0.1%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 513
 
5.2%
이 463
 
4.7%
어 383
 
3.9%
헤 363
 
3.7%
미 299
 
3.0%
소 284
 
2.9%
실 216
 
2.2%
원 203
 
2.1%
리 165
 
1.7%
경 153
 
1.5%
Other values (601) 6844
69.2%
Latin
ValueCountFrequency (%)
e 10
 
7.4%
S 9
 
6.6%
H 7
 
5.1%
A 7
 
5.1%
K 6
 
4.4%
s 6
 
4.4%
J 6
 
4.4%
M 6
 
4.4%
a 6
 
4.4%
l 5
 
3.7%
Other values (28) 68
50.0%
Common
ValueCountFrequency (%)
245
62.8%
( 38
 
9.7%
) 38
 
9.7%
0 18
 
4.6%
1 11
 
2.8%
. 10
 
2.6%
2 10
 
2.6%
8 6
 
1.5%
4 4
 
1.0%
? 2
 
0.5%
Other values (6) 8
 
2.1%
Han
ValueCountFrequency (%)
美 1
25.0%
林 1
25.0%
揚 1
25.0%
遣 1
25.0%
Greek
ValueCountFrequency (%)
Ζ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9881
94.9%
ASCII 526
 
5.0%
None 6
 
0.1%
CJK 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
용 513
 
5.2%
이 463
 
4.7%
어 383
 
3.9%
헤 363
 
3.7%
미 299
 
3.0%
소 284
 
2.9%
실 216
 
2.2%
원 203
 
2.1%
리 165
 
1.7%
경 153
 
1.5%
Other values (600) 6839
69.2%
ASCII
ValueCountFrequency (%)
245
46.6%
( 38
 
7.2%
) 38
 
7.2%
0 18
 
3.4%
1 11
 
2.1%
. 10
 
1.9%
e 10
 
1.9%
2 10
 
1.9%
S 9
 
1.7%
H 7
 
1.3%
Other values (44) 130
24.7%
None
ValueCountFrequency (%)
㈜ 5
83.3%
Ζ 1
 
16.7%
CJK
ValueCountFrequency (%)
美 1
25.0%
林 1
25.0%
揚 1
25.0%
遣 1
25.0%

업종명코드
Categorical

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
7
990 
2
506 
99
291 
8
 
46
6
 
2

Length

Max length2
Median length1
Mean length1.1585831
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row7
3rd row99
4th row2
5th row99

Common Values

ValueCountFrequency (%)
7 990
54.0%
2 506
27.6%
99 291
 
15.9%
8 46
 
2.5%
6 2
 
0.1%

Length

2024-04-30T08:35:47.538490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T08:35:47.633026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7 990
54.0%
2 506
27.6%
99 291
 
15.9%
8 46
 
2.5%
6 2
 
0.1%

시도명
Categorical

Distinct12
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
서울특별시
558 
대구광역시
387 
경기도
194 
인천광역시
187 
대전광역시
145 
Other values (7)
364 

Length

Max length7
Median length5
Mean length4.6850136
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 558
30.4%
대구광역시 387
21.1%
경기도 194
 
10.6%
인천광역시 187
 
10.2%
대전광역시 145
 
7.9%
경상남도 111
 
6.0%
울산광역시 83
 
4.5%
충청북도 75
 
4.1%
강원특별자치도 35
 
1.9%
강원도 35
 
1.9%
Other values (2) 25
 
1.4%

Length

2024-04-30T08:35:47.746964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 558
30.4%
대구광역시 387
21.1%
경기도 194
 
10.6%
인천광역시 187
 
10.2%
대전광역시 145
 
7.9%
경상남도 111
 
6.0%
울산광역시 83
 
4.5%
충청북도 75
 
4.1%
강원특별자치도 35
 
1.9%
강원도 35
 
1.9%
Other values (2) 25
 
1.4%

시군구명
Categorical

Distinct24
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
영등포구
259 
수원시
194 
광진구
168 
대덕구
145 
남동구
127 
Other values (19)
942 

Length

Max length4
Median length3
Mean length2.999455
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영등포구 259
14.1%
수원시 194
10.6%
광진구 168
 
9.2%
대덕구 145
 
7.9%
남동구 127
 
6.9%
달서구 123
 
6.7%
김해시 111
 
6.0%
성동구 102
 
5.6%
남구 95
 
5.2%
동구 83
 
4.5%
Other values (14) 428
23.3%

Length

2024-04-30T08:35:47.874354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
영등포구 259
14.1%
수원시 194
10.6%
광진구 168
 
9.2%
대덕구 145
 
7.9%
남동구 127
 
6.9%
달서구 123
 
6.7%
김해시 111
 
6.0%
성동구 102
 
5.6%
남구 95
 
5.2%
동구 83
 
4.5%
Other values (14) 428
23.3%

시군구코드
Real number (ℝ)

Distinct25
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27471.357
Minimum11200
Maximum57350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.3 KiB
2024-04-30T08:35:47.969229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11200
5-th percentile11200
Q111560
median27710
Q334100
95-th percentile48250
Maximum57350
Range46150
Interquartile range (IQR)22540

Descriptive statistics

Standard deviation12804.843
Coefficient of variation (CV)0.46611614
Kurtosis-0.75410784
Mean27471.357
Median Absolute Deviation (MAD)13400
Skewness0.23284751
Sum50409941
Variance1.63964 × 108
MonotonicityNot monotonic
2024-04-30T08:35:48.073360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
11560 259
14.1%
41110 194
10.6%
11215 168
 
9.2%
30230 145
 
7.9%
28200 127
 
6.9%
27290 123
 
6.7%
48250 111
 
6.0%
11200 102
 
5.6%
27200 95
 
5.2%
31170 82
 
4.5%
Other values (15) 429
23.4%
ValueCountFrequency (%)
11200 102
 
5.6%
11215 168
9.2%
11560 259
14.1%
11650 29
 
1.6%
26470 21
 
1.1%
27170 59
 
3.2%
27200 95
 
5.2%
27230 46
 
2.5%
27290 123
6.7%
27710 27
 
1.5%
ValueCountFrequency (%)
57350 8
 
0.4%
57300 11
 
0.6%
57250 14
 
0.8%
57200 18
 
1.0%
48250 111
6.0%
47700 4
 
0.2%
43760 24
 
1.3%
42210 70
 
3.8%
41110 194
10.6%
34100 37
 
2.0%

소재지도로명주소
Text

Distinct1805
Distinct (%)98.6%
Missing4
Missing (%)0.2%
Memory size14.5 KiB
2024-04-30T08:35:48.354017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length44
Mean length24.173129
Min length14

Characters and Unicode

Total characters44261
Distinct characters355
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1782 ?
Unique (%)97.3%

Sample

1st row서울특별시 영등포구 영등포로11길 20 (양평동1가)
2nd row서울특별시 영등포구 영등포로5길 39
3rd row서울특별시 영등포구 선유서로 115, 5호 (양평동3가, 삼천리아파트상가)
4th row서울특별시 영등포구 선유로33길 22(양평동3가)
5th row서울특별시 영등포구 영등포로 26
ValueCountFrequency (%)
서울특별시 555
 
6.3%
대구광역시 387
 
4.4%
영등포구 256
 
2.9%
수원시 194
 
2.2%
경기도 194
 
2.2%
인천광역시 187
 
2.1%
광진구 169
 
1.9%
대전광역시 144
 
1.6%
대덕구 144
 
1.6%
남동구 128
 
1.5%
Other values (2484) 6390
73.0%
2024-04-30T08:35:48.814340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6917
 
15.6%
구 2117
 
4.8%
시 1830
 
4.1%
1 1739
 
3.9%
로 1695
 
3.8%
동 1469
 
3.3%
길 1130
 
2.6%
2 1073
 
2.4%
광 1023
 
2.3%
) 1013
 
2.3%
Other values (345) 24255
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27265
61.6%
Decimal Number 7361
 
16.6%
Space Separator 6917
 
15.6%
Close Punctuation 1013
 
2.3%
Open Punctuation 1013
 
2.3%
Other Punctuation 351
 
0.8%
Dash Punctuation 329
 
0.7%
Uppercase Letter 10
 
< 0.1%
Lowercase Letter 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2117
 
7.8%
시 1830
 
6.7%
로 1695
 
6.2%
동 1469
 
5.4%
길 1130
 
4.1%
광 1023
 
3.8%
대 1001
 
3.7%
서 868
 
3.2%
역 829
 
3.0%
울 647
 
2.4%
Other values (319) 14656
53.8%
Decimal Number
ValueCountFrequency (%)
1 1739
23.6%
2 1073
14.6%
3 852
11.6%
4 679
 
9.2%
5 587
 
8.0%
6 545
 
7.4%
0 544
 
7.4%
7 498
 
6.8%
8 454
 
6.2%
9 390
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
A 3
30.0%
C 2
20.0%
H 1
 
10.0%
B 1
 
10.0%
L 1
 
10.0%
I 1
 
10.0%
S 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 347
98.9%
. 3
 
0.9%
@ 1
 
0.3%
Space Separator
ValueCountFrequency (%)
6917
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1013
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1013
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 329
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27265
61.6%
Common 16985
38.4%
Latin 11
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2117
 
7.8%
시 1830
 
6.7%
로 1695
 
6.2%
동 1469
 
5.4%
길 1130
 
4.1%
광 1023
 
3.8%
대 1001
 
3.7%
서 868
 
3.2%
역 829
 
3.0%
울 647
 
2.4%
Other values (319) 14656
53.8%
Common
ValueCountFrequency (%)
6917
40.7%
1 1739
 
10.2%
2 1073
 
6.3%
) 1013
 
6.0%
( 1013
 
6.0%
3 852
 
5.0%
4 679
 
4.0%
5 587
 
3.5%
6 545
 
3.2%
0 544
 
3.2%
Other values (8) 2023
 
11.9%
Latin
ValueCountFrequency (%)
A 3
27.3%
C 2
18.2%
a 1
 
9.1%
H 1
 
9.1%
B 1
 
9.1%
L 1
 
9.1%
I 1
 
9.1%
S 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27265
61.6%
ASCII 16996
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6917
40.7%
1 1739
 
10.2%
2 1073
 
6.3%
) 1013
 
6.0%
( 1013
 
6.0%
3 852
 
5.0%
4 679
 
4.0%
5 587
 
3.5%
6 545
 
3.2%
0 544
 
3.2%
Other values (16) 2034
 
12.0%
Hangul
ValueCountFrequency (%)
구 2117
 
7.8%
시 1830
 
6.7%
로 1695
 
6.2%
동 1469
 
5.4%
길 1130
 
4.1%
광 1023
 
3.8%
대 1001
 
3.7%
서 868
 
3.2%
역 829
 
3.0%
울 647
 
2.4%
Other values (319) 14656
53.8%

소재지지번주소
Text

MISSING 

Distinct785
Distinct (%)99.2%
Missing1044
Missing (%)56.9%
Memory size14.5 KiB
2024-04-30T08:35:49.122461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length39
Mean length20.557522
Min length14

Characters and Unicode

Total characters16261
Distinct characters207
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

Unique779 ?
Unique (%)98.5%

Sample

1st row경기도 수원시 장안구 영화동 130-6
2nd row경기도 수원시 팔달구 인계동 963-8
3rd row경기도 수원시 팔달구 고등동 45-1
4th row경기도 수원시 팔달구 인계동 1125-2
5th row경기도 수원시 팔달구 인계동 368-1
ValueCountFrequency (%)
경기도 194
 
5.6%
수원시 194
 
5.6%
대구광역시 188
 
5.4%
경상남도 111
 
3.2%
김해시 111
 
3.2%
대전광역시 110
 
3.2%
대덕구 110
 
3.2%
남구 95
 
2.7%
속초시 70
 
2.0%
대명동 70
 
2.0%
Other values (967) 2232
64.0%
2024-04-30T08:35:49.504163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2694
 
16.6%
1 820
 
5.0%
시 787
 
4.8%
구 782
 
4.8%
동 764
 
4.7%
- 728
 
4.5%
대 494
 
3.0%
2 440
 
2.7%
3 405
 
2.5%
4 389
 
2.4%
Other values (197) 7958
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9021
55.5%
Decimal Number 3703
22.8%
Space Separator 2694
 
16.6%
Dash Punctuation 728
 
4.5%
Other Punctuation 42
 
0.3%
Open Punctuation 36
 
0.2%
Close Punctuation 36
 
0.2%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 787
 
8.7%
구 782
 
8.7%
동 764
 
8.5%
대 494
 
5.5%
도 387
 
4.3%
광 380
 
4.2%
역 379
 
4.2%
경 307
 
3.4%
원 299
 
3.3%
남 216
 
2.4%
Other values (181) 4226
46.8%
Decimal Number
ValueCountFrequency (%)
1 820
22.1%
2 440
11.9%
3 405
10.9%
4 389
10.5%
5 306
 
8.3%
6 303
 
8.2%
0 287
 
7.8%
7 262
 
7.1%
8 254
 
6.9%
9 237
 
6.4%
Space Separator
ValueCountFrequency (%)
2694
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 728
100.0%
Other Punctuation
ValueCountFrequency (%)
, 42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9021
55.5%
Common 7239
44.5%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 787
 
8.7%
구 782
 
8.7%
동 764
 
8.5%
대 494
 
5.5%
도 387
 
4.3%
광 380
 
4.2%
역 379
 
4.2%
경 307
 
3.4%
원 299
 
3.3%
남 216
 
2.4%
Other values (181) 4226
46.8%
Common
ValueCountFrequency (%)
2694
37.2%
1 820
 
11.3%
- 728
 
10.1%
2 440
 
6.1%
3 405
 
5.6%
4 389
 
5.4%
5 306
 
4.2%
6 303
 
4.2%
0 287
 
4.0%
7 262
 
3.6%
Other values (5) 605
 
8.4%
Latin
ValueCountFrequency (%)
D 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9021
55.5%
ASCII 7240
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2694
37.2%
1 820
 
11.3%
- 728
 
10.1%
2 440
 
6.1%
3 405
 
5.6%
4 389
 
5.4%
5 306
 
4.2%
6 303
 
4.2%
0 287
 
4.0%
7 262
 
3.6%
Other values (6) 606
 
8.4%
Hangul
ValueCountFrequency (%)
시 787
 
8.7%
구 782
 
8.7%
동 764
 
8.5%
대 494
 
5.5%
도 387
 
4.3%
광 380
 
4.2%
역 379
 
4.2%
경 307
 
3.4%
원 299
 
3.3%
남 216
 
2.4%
Other values (181) 4226
46.8%

위도
Real number (ℝ)

Distinct1743
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.77952
Minimum35.168912
Maximum38.219298
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.3 KiB
2024-04-30T08:35:49.627447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.168912
5-th percentile35.240785
Q135.85848
median37.272666
Q337.513145
95-th percentile37.565685
Maximum38.219298
Range3.0503856
Interquartile range (IQR)1.6546653

Descriptive statistics

Standard deviation0.87548969
Coefficient of variation (CV)0.023803728
Kurtosis-1.3216563
Mean36.77952
Median Absolute Deviation (MAD)0.2930372
Skewness-0.38923664
Sum67490.418
Variance0.76648219
MonotonicityNot monotonic
2024-04-30T08:35:49.752423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.517463 5
 
0.3%
37.45555587 4
 
0.2%
37.502183 3
 
0.2%
35.1878529 3
 
0.2%
37.520326 3
 
0.2%
37.519252 3
 
0.2%
35.80397398 3
 
0.2%
37.516869 2
 
0.1%
38.2010274 2
 
0.1%
38.20179207 2
 
0.1%
Other values (1733) 1805
98.4%
ValueCountFrequency (%)
35.1689119 1
0.1%
35.16902504 1
0.1%
35.1713095 1
0.1%
35.17214444 2
0.1%
35.1724314 1
0.1%
35.17296216 1
0.1%
35.17334641 1
0.1%
35.174982 1
0.1%
35.175631 1
0.1%
35.17674321 1
0.1%
ValueCountFrequency (%)
38.21929754 2
0.1%
38.21578418 2
0.1%
38.20908591 2
0.1%
38.20825357 2
0.1%
38.20769387 2
0.1%
38.20624972 2
0.1%
38.20595486 2
0.1%
38.20560936 2
0.1%
38.20537092 2
0.1%
38.20528708 2
0.1%

경도
Real number (ℝ)

Distinct1743
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.6612
Minimum126.6353
Maximum129.45785
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.3 KiB
2024-04-30T08:35:49.865070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.6353
5-th percentile126.70907
Q1126.975
median127.09133
Q3128.5683
95-th percentile129.08546
Maximum129.45785
Range2.8225482
Interquartile range (IQR)1.5932986

Descriptive statistics

Standard deviation0.85804431
Coefficient of variation (CV)0.0067212613
Kurtosis-1.2455314
Mean127.6612
Median Absolute Deviation (MAD)0.3560512
Skewness0.55927727
Sum234258.31
Variance0.73624003
MonotonicityNot monotonic
2024-04-30T08:35:49.979934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.896494 5
 
0.3%
126.7333753 4
 
0.2%
126.906937 3
 
0.2%
128.8072551 3
 
0.2%
128.5348468 3
 
0.2%
126.892722 3
 
0.2%
126.912434 3
 
0.2%
128.5570446 2
 
0.1%
128.585528 2
 
0.1%
128.6115418 2
 
0.1%
Other values (1733) 1805
98.4%
ValueCountFrequency (%)
126.6353039 1
0.1%
126.6368814 1
0.1%
126.6381475 1
0.1%
126.6436072 1
0.1%
126.643722 1
0.1%
126.6485094 1
0.1%
126.6491202 1
0.1%
126.6494279 1
0.1%
126.6499284 1
0.1%
126.6518107 1
0.1%
ValueCountFrequency (%)
129.4578521 1
0.1%
129.457616 1
0.1%
129.4573588 1
0.1%
129.4548314 1
0.1%
129.4543209 1
0.1%
129.4522173 1
0.1%
129.4327928 1
0.1%
129.4326697 1
0.1%
129.4326527 1
0.1%
129.4326415 1
0.1%

업소전화번호
Text

Distinct1566
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
2024-04-30T08:35:50.260246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.887193
Min length9

Characters and Unicode

Total characters21813
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1516 ?
Unique (%)82.6%

Sample

1st row02-3667-3010
2nd row02-2679-8575
3rd row02-2677-5982
4th row02-2631-0600
5th row02-2632-6666
ValueCountFrequency (%)
000-0000-0000 94
 
5.1%
053-000-0000 46
 
2.5%
053-667-3595 37
 
2.0%
000-000-0000 22
 
1.2%
055-330-8663 21
 
1.1%
032-000-0000 8
 
0.4%
055-332-3062 5
 
0.3%
033-633-9601 2
 
0.1%
033-638-4733 2
 
0.1%
033-633-4371 2
 
0.1%
Other values (1556) 1596
87.0%
2024-04-30T08:35:50.651128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4232
19.4%
- 3668
16.8%
2 2604
11.9%
3 2513
11.5%
5 1883
8.6%
6 1457
 
6.7%
4 1452
 
6.7%
1 1149
 
5.3%
8 1064
 
4.9%
7 934
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18145
83.2%
Dash Punctuation 3668
 
16.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4232
23.3%
2 2604
14.4%
3 2513
13.8%
5 1883
10.4%
6 1457
 
8.0%
4 1452
 
8.0%
1 1149
 
6.3%
8 1064
 
5.9%
7 934
 
5.1%
9 857
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 3668
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21813
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4232
19.4%
- 3668
16.8%
2 2604
11.9%
3 2513
11.5%
5 1883
8.6%
6 1457
 
6.7%
4 1452
 
6.7%
1 1149
 
5.3%
8 1064
 
4.9%
7 934
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21813
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4232
19.4%
- 3668
16.8%
2 2604
11.9%
3 2513
11.5%
5 1883
8.6%
6 1457
 
6.7%
4 1452
 
6.7%
1 1149
 
5.3%
8 1064
 
4.9%
7 934
 
4.3%

할인적용최소연령
Real number (ℝ)

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.873569
Minimum60
Maximum80
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.3 KiB
2024-04-30T08:35:50.755841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile65
Q165
median65
Q370
95-th percentile70
Maximum80
Range20
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.6019735
Coefficient of variation (CV)0.038908847
Kurtosis0.27439606
Mean66.873569
Median Absolute Deviation (MAD)0
Skewness0.99462756
Sum122713
Variance6.7702662
MonotonicityNot monotonic
2024-04-30T08:35:50.846947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
65 1113
60.7%
70 603
32.9%
66 83
 
4.5%
75 32
 
1.7%
60 2
 
0.1%
80 2
 
0.1%
ValueCountFrequency (%)
60 2
 
0.1%
65 1113
60.7%
66 83
 
4.5%
70 603
32.9%
75 32
 
1.7%
80 2
 
0.1%
ValueCountFrequency (%)
80 2
 
0.1%
75 32
 
1.7%
70 603
32.9%
66 83
 
4.5%
65 1113
60.7%
60 2
 
0.1%

할인율
Categorical

IMBALANCE 

Distinct40
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
10
708 
50
397 
20
255 
<NA>
194 
5
89 
Other values (35)
192 

Length

Max length5
Median length2
Mean length2.2179837
Min length1

Unique

Unique16 ?
Unique (%)0.9%

Sample

1st row10
2nd row10
3rd row10
4th row10
5th row10

Common Values

ValueCountFrequency (%)
10 708
38.6%
50 397
21.6%
20 255
 
13.9%
<NA> 194
 
10.6%
5 89
 
4.9%
30 81
 
4.4%
15 20
 
1.1%
40 17
 
0.9%
25 15
 
0.8%
30+50 6
 
0.3%
Other values (30) 53
 
2.9%

Length

2024-04-30T08:35:50.967144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10 708
38.6%
50 397
21.6%
20 255
 
13.9%
na 194
 
10.6%
5 89
 
4.9%
30 81
 
4.4%
15 20
 
1.1%
40 17
 
0.9%
25 15
 
0.8%
30+50 6
 
0.3%
Other values (30) 53
 
2.9%

할인금액
Categorical

IMBALANCE 

Distinct37
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
<NA>
1649 
1000
 
79
2000
 
21
500
 
14
5000
 
9
Other values (32)
 
63

Length

Max length16
Median length4
Mean length4.1029973
Min length1

Unique

Unique16 ?
Unique (%)0.9%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1649
89.9%
1000 79
 
4.3%
2000 21
 
1.1%
500 14
 
0.8%
5000 9
 
0.5%
5000+20000 6
 
0.3%
10000+30000 4
 
0.2%
0 4
 
0.2%
20 4
 
0.2%
10000 4
 
0.2%
Other values (27) 41
 
2.2%

Length

2024-04-30T08:35:51.111191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1649
89.9%
1000 79
 
4.3%
2000 21
 
1.1%
500 14
 
0.8%
5000 9
 
0.5%
5000+20000 6
 
0.3%
10000+30000 4
 
0.2%
0 4
 
0.2%
20 4
 
0.2%
10000 4
 
0.2%
Other values (27) 41
 
2.2%

할인대상서비스명
Text

MISSING 

Distinct192
Distinct (%)20.5%
Missing900
Missing (%)49.0%
Memory size14.5 KiB
2024-04-30T08:35:51.301334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length16
Mean length4.2491979
Min length1

Characters and Unicode

Total characters3973
Distinct characters228
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)13.0%

Sample

1st row코팅(파마 시)
2nd row커트+파마
3rd row커트+파마
4th row커트+파마
5th row돋보기
ValueCountFrequency (%)
음식 106
 
10.3%
커트 88
 
8.6%
이발+면도 80
 
7.8%
미용서비스 75
 
7.3%
전품목 60
 
5.8%
염색 41
 
4.0%
펌 38
 
3.7%
커트+파마 33
 
3.2%
이발 29
 
2.8%
이용서비스 29
 
2.8%
Other values (193) 450
43.7%
2024-04-30T08:35:51.605199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 417
 
10.5%
트 195
 
4.9%
커 189
 
4.8%
이 164
 
4.1%
용 128
 
3.2%
비 128
 
3.2%
식 123
 
3.1%
발 122
 
3.1%
스 120
 
3.0%
펌 119
 
3.0%
Other values (218) 2268
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3436
86.5%
Math Symbol 417
 
10.5%
Space Separator 94
 
2.4%
Decimal Number 13
 
0.3%
Open Punctuation 6
 
0.2%
Close Punctuation 6
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 195
 
5.7%
커 189
 
5.5%
이 164
 
4.8%
용 128
 
3.7%
비 128
 
3.7%
식 123
 
3.6%
발 122
 
3.6%
스 120
 
3.5%
펌 119
 
3.5%
음 111
 
3.2%
Other values (210) 2037
59.3%
Decimal Number
ValueCountFrequency (%)
0 7
53.8%
1 4
30.8%
5 2
 
15.4%
Math Symbol
ValueCountFrequency (%)
+ 417
100.0%
Space Separator
ValueCountFrequency (%)
94
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3436
86.5%
Common 537
 
13.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 195
 
5.7%
커 189
 
5.5%
이 164
 
4.8%
용 128
 
3.7%
비 128
 
3.7%
식 123
 
3.6%
발 122
 
3.6%
스 120
 
3.5%
펌 119
 
3.5%
음 111
 
3.2%
Other values (210) 2037
59.3%
Common
ValueCountFrequency (%)
+ 417
77.7%
94
 
17.5%
0 7
 
1.3%
( 6
 
1.1%
) 6
 
1.1%
1 4
 
0.7%
5 2
 
0.4%
, 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3436
86.5%
ASCII 537
 
13.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 417
77.7%
94
 
17.5%
0 7
 
1.3%
( 6
 
1.1%
) 6
 
1.1%
1 4
 
0.7%
5 2
 
0.4%
, 1
 
0.2%
Hangul
ValueCountFrequency (%)
트 195
 
5.7%
커 189
 
5.5%
이 164
 
4.8%
용 128
 
3.7%
비 128
 
3.7%
식 123
 
3.6%
발 122
 
3.6%
스 120
 
3.5%
펌 119
 
3.5%
음 111
 
3.2%
Other values (210) 2037
59.3%

할인부가정보
Text

MISSING 

Distinct85
Distinct (%)49.4%
Missing1663
Missing (%)90.6%
Memory size14.5 KiB
2024-04-30T08:35:51.834253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length25
Mean length9.0232558
Min length2

Characters and Unicode

Total characters1552
Distinct characters177
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)39.0%

Sample

1st row일부품목(가죽 등 특수소재 제외)
2nd row일부품목(기름류)
3rd row할인메뉴 제외
4th row일부품목(파마, 컷트)
5th row일부품목(안경테+렌즈)
ValueCountFrequency (%)
일부품목 40
 
16.3%
전체품목 12
 
4.9%
제외 9
 
3.7%
전체 8
 
3.3%
매일(11:00~21:00 7
 
2.8%
수(11:00~21:00 7
 
2.8%
일부품목(식사류 5
 
2.0%
할인금액으로 4
 
1.6%
할인 4
 
1.6%
판매(전체 3
 
1.2%
Other values (125) 147
59.8%
2024-04-30T08:35:52.171701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
품 108
 
7.0%
0 108
 
7.0%
일 104
 
6.7%
목 101
 
6.5%
부 90
 
5.8%
( 88
 
5.7%
) 88
 
5.7%
1 76
 
4.9%
74
 
4.8%
: 42
 
2.7%
Other values (167) 673
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 979
63.1%
Decimal Number 228
 
14.7%
Open Punctuation 88
 
5.7%
Close Punctuation 88
 
5.7%
Space Separator 74
 
4.8%
Other Punctuation 61
 
3.9%
Math Symbol 33
 
2.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 108
 
11.0%
일 104
 
10.6%
목 101
 
10.3%
부 90
 
9.2%
전 26
 
2.7%
체 23
 
2.3%
인 22
 
2.2%
제 19
 
1.9%
할 18
 
1.8%
외 17
 
1.7%
Other values (147) 451
46.1%
Decimal Number
ValueCountFrequency (%)
0 108
47.4%
1 76
33.3%
2 25
 
11.0%
5 7
 
3.1%
3 7
 
3.1%
4 2
 
0.9%
8 1
 
0.4%
9 1
 
0.4%
6 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
: 42
68.9%
, 16
 
26.2%
※ 2
 
3.3%
/ 1
 
1.6%
Math Symbol
ValueCountFrequency (%)
~ 23
69.7%
+ 9
 
27.3%
⇒ 1
 
3.0%
Open Punctuation
ValueCountFrequency (%)
( 88
100.0%
Close Punctuation
ValueCountFrequency (%)
) 88
100.0%
Space Separator
ValueCountFrequency (%)
74
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 979
63.1%
Common 573
36.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 108
 
11.0%
일 104
 
10.6%
목 101
 
10.3%
부 90
 
9.2%
전 26
 
2.7%
체 23
 
2.3%
인 22
 
2.2%
제 19
 
1.9%
할 18
 
1.8%
외 17
 
1.7%
Other values (147) 451
46.1%
Common
ValueCountFrequency (%)
0 108
18.8%
( 88
15.4%
) 88
15.4%
1 76
13.3%
74
12.9%
: 42
 
7.3%
2 25
 
4.4%
~ 23
 
4.0%
, 16
 
2.8%
+ 9
 
1.6%
Other values (10) 24
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 979
63.1%
ASCII 570
36.7%
Punctuation 2
 
0.1%
Arrows 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
품 108
 
11.0%
일 104
 
10.6%
목 101
 
10.3%
부 90
 
9.2%
전 26
 
2.7%
체 23
 
2.3%
인 22
 
2.2%
제 19
 
1.9%
할 18
 
1.8%
외 17
 
1.7%
Other values (147) 451
46.1%
ASCII
ValueCountFrequency (%)
0 108
18.9%
( 88
15.4%
) 88
15.4%
1 76
13.3%
74
13.0%
: 42
 
7.4%
2 25
 
4.4%
~ 23
 
4.0%
, 16
 
2.8%
+ 9
 
1.6%
Other values (8) 21
 
3.7%
Punctuation
ValueCountFrequency (%)
※ 2
100.0%
Arrows
ValueCountFrequency (%)
⇒ 1
100.0%

평일운영시작시각
Date

Distinct27
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
Minimum2024-04-30 00:00:00
Maximum2024-04-30 17:00:00
2024-04-30T08:35:52.273034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:35:52.365584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

평일운영종료시각
Date

Distinct28
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
Minimum2024-04-30 00:00:00
Maximum2024-04-30 23:59:00
2024-04-30T08:35:52.471327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:35:52.746475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

토요일운영시작시각
Date

Distinct27
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
Minimum2024-04-30 00:00:00
Maximum2024-04-30 19:30:00
2024-04-30T08:35:52.836270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:35:52.935665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

토요일운영종료시각
Date

Distinct28
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
Minimum2024-04-30 00:00:00
Maximum2024-04-30 23:59:00
2024-04-30T08:35:53.041829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:35:53.148778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

공휴일운영시작시각
Date

Distinct28
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
Minimum2024-04-30 00:00:00
Maximum2024-04-30 20:00:00
2024-04-30T08:35:53.247446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:35:53.358294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

공휴일운영종료시각
Date

Distinct27
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
Minimum2024-04-30 00:00:00
Maximum2024-04-30 23:59:00
2024-04-30T08:35:53.473188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:35:53.576345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

경로우대업소지정일자
Date

Distinct253
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
Minimum1973-01-11 00:00:00
Maximum2024-01-12 00:00:00
2024-04-30T08:35:53.684619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:35:53.798955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

경로우대업소해제일자
Date

MISSING 

Distinct2
Distinct (%)18.2%
Missing1824
Missing (%)99.4%
Memory size14.5 KiB
Minimum2023-11-13 00:00:00
Maximum2023-12-31 00:00:00
2024-04-30T08:35:53.906002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:35:53.982342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

관리기관명
Categorical

Distinct30
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
서울특별시 영등포구
259 
경기도 수원시청
194 
서울특별시 광진구
168 
대전광역시 대덕구
145 
인천광역시 남동구청
127 
Other values (25)
942 

Length

Max length19
Median length11
Mean length9.3553134
Min length7

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row서울특별시 영등포구
2nd row서울특별시 영등포구
3rd row서울특별시 영등포구
4th row서울특별시 영등포구
5th row서울특별시 영등포구

Common Values

ValueCountFrequency (%)
서울특별시 영등포구 259
14.1%
경기도 수원시청 194
10.6%
서울특별시 광진구 168
 
9.2%
대전광역시 대덕구 145
 
7.9%
인천광역시 남동구청 127
 
6.9%
대구광역시 달서구청 123
 
6.7%
경상남도 김해시청 111
 
6.0%
서울특별시 성동구 102
 
5.6%
대구광역시 남구청 95
 
5.2%
울산광역시 동구청 83
 
4.5%
Other values (20) 428
23.3%

Length

2024-04-30T08:35:54.084722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 558
15.1%
대구광역시 387
 
10.5%
영등포구 259
 
7.0%
수원시청 194
 
5.2%
경기도 194
 
5.2%
인천광역시 187
 
5.1%
광진구 168
 
4.5%
대전광역시 145
 
3.9%
대덕구 145
 
3.9%
남동구청 127
 
3.4%
Other values (32) 1333
36.1%

관리기관전화번호
Categorical

Distinct33
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
02-2670-3390
259 
031-228-2227
194 
02-450-7788
168 
032-453-5856
127 
053-667-3595
123 
Other values (28)
964 

Length

Max length12
Median length12
Mean length11.908447
Min length11

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row02-2670-3390
2nd row02-2670-3390
3rd row02-2670-3390
4th row02-2670-3390
5th row02-2670-3390

Common Values

ValueCountFrequency (%)
02-2670-3390 259
14.1%
031-228-2227 194
 
10.6%
02-450-7788 168
 
9.2%
032-453-5856 127
 
6.9%
053-667-3595 123
 
6.7%
042-608-6883 110
 
6.0%
053-664-2538 95
 
5.2%
052-209-3436 83
 
4.5%
055-330-0882 72
 
3.9%
02-2286-7155 70
 
3.8%
Other values (23) 534
29.1%

Length

2024-04-30T08:35:54.186330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
02-2670-3390 259
14.1%
031-228-2227 194
 
10.6%
02-450-7788 168
 
9.2%
032-453-5856 127
 
6.9%
053-667-3595 123
 
6.7%
042-608-6883 110
 
6.0%
053-664-2538 95
 
5.2%
052-209-3436 83
 
4.5%
055-330-0882 72
 
3.9%
02-2286-7155 70
 
3.8%
Other values (23) 534
29.1%

데이터기준일자
Date

Distinct21
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
Minimum2022-06-15 00:00:00
Maximum2024-03-28 00:00:00
2024-04-30T08:35:54.275915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:35:54.360110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

제공기관코드
Real number (ℝ)

Distinct23
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3637829.4
Minimum3030000
Maximum5710000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.3 KiB
2024-04-30T08:35:54.461327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3030000
5-th percentile3030000
Q13180000
median3470000
Q33710000
95-th percentile5350000
Maximum5710000
Range2680000
Interquartile range (IQR)530000

Descriptive statistics

Standard deviation647229.36
Coefficient of variation (CV)0.17791636
Kurtosis3.1327001
Mean3637829.4
Median Absolute Deviation (MAD)270000
Skewness1.9238393
Sum6.675417 × 109
Variance4.1890585 × 1011
MonotonicityNot monotonic
2024-04-30T08:35:54.571133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
3180000 259
14.1%
3740000 194
10.6%
3040000 168
 
9.2%
3680000 145
 
7.9%
3530000 127
 
6.9%
3470000 123
 
6.7%
5350000 111
 
6.0%
3030000 102
 
5.6%
3440000 95
 
5.2%
3710000 83
 
4.5%
Other values (13) 428
23.3%
ValueCountFrequency (%)
3030000 102
 
5.6%
3040000 168
9.2%
3180000 259
14.1%
3210000 29
 
1.6%
3370000 21
 
1.1%
3410000 37
 
2.0%
3430000 59
 
3.2%
3440000 95
 
5.2%
3450000 46
 
2.5%
3470000 123
6.7%
ValueCountFrequency (%)
5710000 51
 
2.8%
5350000 111
6.0%
4771000 2
 
0.1%
4770000 2
 
0.1%
4460000 24
 
1.3%
4231000 35
 
1.9%
4230000 35
 
1.9%
3740000 194
10.6%
3710000 83
4.5%
3680000 145
7.9%

제공기관명
Categorical

Distinct23
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
서울특별시 영등포구
259 
경기도 수원시
194 
서울특별시 광진구
168 
대전광역시 대덕구
145 
인천광역시 남동구
127 
Other values (18)
942 

Length

Max length11
Median length10
Mean length8.6877384
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 영등포구
2nd row서울특별시 영등포구
3rd row서울특별시 영등포구
4th row서울특별시 영등포구
5th row서울특별시 영등포구

Common Values

ValueCountFrequency (%)
서울특별시 영등포구 259
14.1%
경기도 수원시 194
10.6%
서울특별시 광진구 168
 
9.2%
대전광역시 대덕구 145
 
7.9%
인천광역시 남동구 127
 
6.9%
대구광역시 달서구 123
 
6.7%
경상남도 김해시 111
 
6.0%
서울특별시 성동구 102
 
5.6%
대구광역시 남구 95
 
5.2%
울산광역시 동구 83
 
4.5%
Other values (13) 428
23.3%

Length

2024-04-30T08:35:54.700522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 558
15.2%
대구광역시 387
 
10.5%
영등포구 259
 
7.1%
경기도 194
 
5.3%
수원시 194
 
5.3%
인천광역시 187
 
5.1%
광진구 168
 
4.6%
대전광역시 145
 
4.0%
대덕구 145
 
4.0%
남동구 127
 
3.5%
Other values (24) 1306
35.6%

Sample

업소명업종명코드시도명시군구명시군구코드소재지도로명주소소재지지번주소위도경도업소전화번호할인적용최소연령할인율할인금액할인대상서비스명할인부가정보평일운영시작시각평일운영종료시각토요일운영시작시각토요일운영종료시각공휴일운영시작시각공휴일운영종료시각경로우대업소지정일자경로우대업소해제일자관리기관명관리기관전화번호데이터기준일자제공기관코드제공기관명
0허당국시2서울특별시영등포구11560서울특별시 영등포구 영등포로11길 20 (양평동1가)<NA>37.524319126.88828102-3667-30106510<NA><NA><NA>10:0022:0010:0022:0010:0021:002018-12-01<NA>서울특별시 영등포구02-2670-33902023-11-293180000서울특별시 영등포구
1카시아미용실7서울특별시영등포구11560서울특별시 영등포구 영등포로5길 39<NA>37.524982126.88469702-2679-85756510<NA><NA><NA>10:0022:0010:0022:0010:0021:002018-12-01<NA>서울특별시 영등포구02-2670-33902023-11-293180000서울특별시 영등포구
2일성향균크리닝99서울특별시영등포구11560서울특별시 영등포구 선유서로 115, 5호 (양평동3가, 삼천리아파트상가)<NA>37.526141126.88540902-2677-59826510<NA><NA>일부품목(가죽 등 특수소재 제외)10:0022:0010:0022:0010:0021:002018-12-01<NA>서울특별시 영등포구02-2670-33902023-11-293180000서울특별시 영등포구
3해남 진성옥2서울특별시영등포구11560서울특별시 영등포구 선유로33길 22(양평동3가)<NA>37.527211126.88837602-2631-06006510<NA><NA><NA>10:0022:0010:0022:0010:0021:002018-12-01<NA>서울특별시 영등포구02-2670-33902023-11-293180000서울특별시 영등포구
4열린공인중개사99서울특별시영등포구11560서울특별시 영등포구 영등포로 26<NA>37.522882126.88438102-2632-66666510<NA><NA><NA>10:0022:0010:0022:0010:0021:002018-12-01<NA>서울특별시 영등포구02-2670-33902023-11-293180000서울특별시 영등포구
5양평동 사진관99서울특별시영등포구11560서울특별시 영등포구 선유로33길 4, 2층<NA>37.526686126.89056902-2632-80856520<NA><NA><NA>10:0022:0010:0022:0010:0021:002018-12-01<NA>서울특별시 영등포구02-2670-33902023-11-293180000서울특별시 영등포구
6한강기름집99서울특별시영등포구11560서울특별시 영등포구 선유로51길 9<NA>37.536852126.89699502-2676-6235655<NA><NA>일부품목(기름류)10:0022:0010:0022:0010:0021:002018-12-01<NA>서울특별시 영등포구02-2670-33902023-11-293180000서울특별시 영등포구
7향원2서울특별시영등포구11560서울특별시 영등포구 선유로51길 20-2<NA>37.537487126.89605402-2672-44256510<NA><NA>할인메뉴 제외10:0022:0010:0022:0010:0021:002018-12-01<NA>서울특별시 영등포구02-2670-33902023-11-293180000서울특별시 영등포구
8천웅상사99서울특별시영등포구11560서울특별시 영등포구 선유로51길 29<NA>37.537791126.89508202-2631-78736510<NA><NA><NA>10:0022:0010:0022:0010:0021:002018-12-01<NA>서울특별시 영등포구02-2670-33902023-11-293180000서울특별시 영등포구
9세븐미용실7서울특별시영등포구11560서울특별시 영등포구 양평로24길 9<NA>37.54028126.89174602-2671-04306510<NA><NA>일부품목(파마, 컷트)10:0022:0010:0022:0010:0021:002018-12-01<NA>서울특별시 영등포구02-2670-33902023-11-293180000서울특별시 영등포구
업소명업종명코드시도명시군구명시군구코드소재지도로명주소소재지지번주소위도경도업소전화번호할인적용최소연령할인율할인금액할인대상서비스명할인부가정보평일운영시작시각평일운영종료시각토요일운영시작시각토요일운영종료시각공휴일운영시작시각공휴일운영종료시각경로우대업소지정일자경로우대업소해제일자관리기관명관리기관전화번호데이터기준일자제공기관코드제공기관명
1825용문각2부산광역시연제구26470부산광역시 연제구 거제천로 209(거제동)부산광역시 연제구 거제동 1-7535.191515129.079768051-864-60057510<NA>짜장면수(11:00~21:00)11:0021:0011:0021:0011:0021:002021-08-31<NA>부산광역시 연제구청051-665-43252023-10-303370000부산광역시 연제구
1826한방장어구이2부산광역시연제구26470부산광역시 연제구 아시아드대로 8, 2층(거제동)부산광역시 연제구 거제동 879-1335.186286129.070751051-503-33537510<NA>추어탕월(11:00~21:00)11:0021:0011:0021:0011:0021:002021-08-31<NA>부산광역시 연제구청051-665-43252023-10-303370000부산광역시 연제구
1827멧집찌개2부산광역시연제구26470부산광역시 연제구 거제시장로14번길 52(거제동)부산광역시 연제구 거제동 457-3335.182964129.073342051-852-44587510<NA>김치찌개+된장찌개금(11:00~21:00)11:0021:0011:0021:0011:0021:002021-08-31<NA>부산광역시 연제구청051-665-43252023-10-303370000부산광역시 연제구
1828이백집2부산광역시연제구26470부산광역시 연제구 해맞이로31번길 62-7(거제동)부산광역시 연제구 거제동 676-29135.179364129.064614051-507-02457510<NA>추어탕수(11:00~21:00)11:0021:0011:0021:0011:0021:002021-08-31<NA>부산광역시 연제구청051-665-43252023-10-303370000부산광역시 연제구
1829합천식당2부산광역시연제구26470부산광역시 연제구 해맞이로67번길 3(거제동)부산광역시 연제구 거제동 676-7235.180279129.068136051-501-96407510<NA>오리불고기수(11:00~21:00)11:0021:0011:0021:0011:0021:002021-08-31<NA>부산광역시 연제구청051-665-43252023-10-303370000부산광역시 연제구
1830삼우정식육식당2부산광역시연제구26470부산광역시 연제구 과정로344번길 26, 1층(연산동)부산광역시 연제구 연산동 307-6335.191109129.09183051-862-11827510<NA>갈비탕매일(11:00~21:00)11:0021:0011:0021:0011:0021:002021-08-31<NA>부산광역시 연제구청051-665-43252023-10-303370000부산광역시 연제구
1831연산명오리2부산광역시연제구26470부산광역시 연제구 과정로 314, 3층(연산동)부산광역시 연제구 연산동 309-935.189636129.093337051-868-52047520<NA>삼계탕매일(11:00~21:00)11:0021:0011:0021:0011:0021:002021-08-31<NA>부산광역시 연제구청051-665-43252023-10-303370000부산광역시 연제구
1832배산정2부산광역시연제구26470부산광역시 연제구 금련로 6(연산동)부산광역시 연제구 연산동 1811-21435.172962129.096077051-853-19777510<NA>오리불고기화(11:00~21:00)11:0021:0011:0021:0011:0021:002021-08-31<NA>부산광역시 연제구청051-665-43252023-10-303370000부산광역시 연제구
1833남도횟집2부산광역시연제구26470부산광역시 연제구 연수로208번길 7(연산동)부산광역시 연제구 연산동 1832-735.173346129.093458051-853-98907510<NA>모듬회월(11:00~21:00)11:0021:0011:0021:0011:0021:002021-08-31<NA>부산광역시 연제구청051-665-43252023-10-303370000부산광역시 연제구
1834쿡찜닭2부산광역시연제구26470부산광역시 연제구 쌍미천로151번길 34(연산동)부산광역시 연제구 연산동 630-3335.186264129.085419051-866-95407510<NA>안동찜닭수(11:00~21:00)11:0021:0011:0021:0011:0021:002021-08-31<NA>부산광역시 연제구청051-665-43252023-10-303370000부산광역시 연제구