Overview

Dataset statistics

Number of variables34
Number of observations30
Missing cells438
Missing cells (%)42.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.9 KiB
Average record size in memory304.4 B

Variable types

Text6
Numeric10
Categorical9
Unsupported9

Dataset

Description샘플 데이터
Author서울시
URLhttps://bigdata.seoul.go.kr/data/selectSampleData.do?sample_data_seq=27

Alerts

점용면적_가로(PLACE_L) is highly imbalanced (73.5%)Imbalance
일매출액(DAY_SALES) is highly imbalanced (73.5%)Imbalance
주변정보(WITH_INFO) has 10 (33.3%) missing valuesMissing
도로정보(ROAD_INFO) has 23 (76.7%) missing valuesMissing
지역정보(AR_TXT) has 26 (86.7%) missing valuesMissing
인접시설_메모(UC_TXT) has 26 (86.7%) missing valuesMissing
설치일자(FOUND_DATE) has 13 (43.3%) missing valuesMissing
시설규격_가로(FACIL_L) has 30 (100.0%) missing valuesMissing
시설규격_세로(FACIL_W) has 30 (100.0%) missing valuesMissing
시설규격_높이(FACIL_H) has 30 (100.0%) missing valuesMissing
개점시간(IPEN_TIME) has 18 (60.0%) missing valuesMissing
폐점시간(CLOSE_TIME) has 18 (60.0%) missing valuesMissing
허가일자(PERMIT_DATE) has 11 (36.7%) missing valuesMissing
가입단체(UN_TYP) has 30 (100.0%) missing valuesMissing
가입단체명(UN_TXT) has 30 (100.0%) missing valuesMissing
기타정보(NOTES) has 23 (76.7%) missing valuesMissing
폐쇄일(DISUSE_DATE) has 30 (100.0%) missing valuesMissing
폐쇄사유(DISUSE_REASON) has 30 (100.0%) missing valuesMissing
반환날짜(RETURN_DATE) has 30 (100.0%) missing valuesMissing
반환여부(RETURN_YN) has 30 (100.0%) missing valuesMissing
관리번호(GAPAN_NO) has unique valuesUnique
도형중심점X좌표(X_COORD) has unique valuesUnique
도형중심점Y좌표(Y_COORD) has unique valuesUnique
시설규격_가로(FACIL_L) is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설규격_세로(FACIL_W) is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설규격_높이(FACIL_H) is an unsupported type, check if it needs cleaning or further analysisUnsupported
가입단체(UN_TYP) is an unsupported type, check if it needs cleaning or further analysisUnsupported
가입단체명(UN_TXT) is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐쇄일(DISUSE_DATE) is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐쇄사유(DISUSE_REASON) is an unsupported type, check if it needs cleaning or further analysisUnsupported
반환날짜(RETURN_DATE) is an unsupported type, check if it needs cleaning or further analysisUnsupported
반환여부(RETURN_YN) is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-17 20:13:14.582782
Analysis finished2024-04-17 20:13:14.902346
Duration0.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호(GAPAN_NO)
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-04-18T05:13:15.008233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters390
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

Unique30 ?
Unique (%)100.0%

Sample

1st row680107_4_0004
2nd row620103_4_0002
3rd row680105_4_0021
4th row140116_4_0019
5th row305101_4_0022
ValueCountFrequency (%)
680107_4_0004 1
 
3.3%
620103_4_0002 1
 
3.3%
680101_4_0038 1
 
3.3%
710107_4_0033 1
 
3.3%
560132_4_0051 1
 
3.3%
110119_4_0005 1
 
3.3%
680108_4_0012 1
 
3.3%
560105_4_0076 1
 
3.3%
215107_4_0006 1
 
3.3%
170125_4_0019 1
 
3.3%
Other values (20) 20
66.7%
2024-04-18T05:13:15.253752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 127
32.6%
_ 60
15.4%
1 58
14.9%
4 43
 
11.0%
2 21
 
5.4%
5 21
 
5.4%
6 18
 
4.6%
7 15
 
3.8%
3 12
 
3.1%
8 9
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 330
84.6%
Connector Punctuation 60
 
15.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 127
38.5%
1 58
17.6%
4 43
 
13.0%
2 21
 
6.4%
5 21
 
6.4%
6 18
 
5.5%
7 15
 
4.5%
3 12
 
3.6%
8 9
 
2.7%
9 6
 
1.8%
Connector Punctuation
ValueCountFrequency (%)
_ 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 390
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 127
32.6%
_ 60
15.4%
1 58
14.9%
4 43
 
11.0%
2 21
 
5.4%
5 21
 
5.4%
6 18
 
4.6%
7 15
 
3.8%
3 12
 
3.1%
8 9
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 390
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 127
32.6%
_ 60
15.4%
1 58
14.9%
4 43
 
11.0%
2 21
 
5.4%
5 21
 
5.4%
6 18
 
4.6%
7 15
 
3.8%
3 12
 
3.1%
8 9
 
2.3%

도형중심점X좌표(X_COORD)
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean200255.48
Minimum187800.44
Maximum209575
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-18T05:13:15.355550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum187800.44
5-th percentile192074.53
Q1197922.08
median199255.87
Q3205118.28
95-th percentile206991.55
Maximum209575
Range21774.554
Interquartile range (IQR)7196.2073

Descriptive statistics

Standard deviation5229.1521
Coefficient of variation (CV)0.026112404
Kurtosis-0.28591547
Mean200255.48
Median Absolute Deviation (MAD)3994.4619
Skewness-0.29665755
Sum6007664.5
Variance27344032
MonotonicityNot monotonic
2024-04-18T05:13:15.457766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
191582.53625 1
 
3.3%
197807.48127 1
 
3.3%
192675.85985 1
 
3.3%
198265.86045 1
 
3.3%
205665.89228 1
 
3.3%
199430.84329 1
 
3.3%
204042.21897 1
 
3.3%
199615.23223 1
 
3.3%
199080.89844 1
 
3.3%
198437.72083 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
187800.44258 1
3.3%
191582.53625 1
3.3%
192675.85985 1
3.3%
193608.22104 1
3.3%
195179.41507 1
3.3%
195413.64166 1
3.3%
197626.41297 1
3.3%
197807.48127 1
3.3%
198265.86045 1
3.3%
198395.78531 1
3.3%
ValueCountFrequency (%)
209574.99674 1
3.3%
207084.78198 1
3.3%
206877.59352 1
3.3%
206599.08528 1
3.3%
206261.07452 1
3.3%
205665.89228 1
3.3%
205576.79062 1
3.3%
205476.97151 1
3.3%
204042.21897 1
3.3%
204030.13146 1
3.3%

도형중심점Y좌표(Y_COORD)
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean451584.4
Minimum442632.96
Maximum463802.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-18T05:13:15.545745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442632.96
5-th percentile444337.61
Q1447734.1
median451289
Q3453239.77
95-th percentile460817.3
Maximum463802.26
Range21169.299
Interquartile range (IQR)5505.6698

Descriptive statistics

Standard deviation5041.617
Coefficient of variation (CV)0.011164285
Kurtosis0.30966328
Mean451584.4
Median Absolute Deviation (MAD)3149.6819
Skewness0.55297832
Sum13547532
Variance25417902
MonotonicityNot monotonic
2024-04-18T05:13:15.635165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
445987.67648 1
 
3.3%
450887.12517 1
 
3.3%
447136.09824 1
 
3.3%
451324.4237 1
 
3.3%
442632.96118 1
 
3.3%
447186.95502 1
 
3.3%
451650.18812 1
 
3.3%
452488.82577 1
 
3.3%
460785.60645 1
 
3.3%
451253.57309 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
442632.96118 1
3.3%
442987.55162 1
3.3%
445987.67648 1
3.3%
446405.96474 1
3.3%
446878.25593 1
3.3%
447136.09824 1
3.3%
447186.95502 1
3.3%
447629.52303 1
3.3%
448047.84721 1
3.3%
449092.49312 1
3.3%
ValueCountFrequency (%)
463802.26033 1
3.3%
460843.23401 1
3.3%
460785.60645 1
3.3%
458434.9302 1
3.3%
456941.57729 1
3.3%
455962.07607 1
3.3%
454347.21107 1
3.3%
453490.08991 1
3.3%
452488.82577 1
3.3%
452241.24208 1
3.3%

인접지지적(WITH_PNU)
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1395616 × 1018
Minimum1.1110124 × 1018
Maximum1.1740109 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-18T05:13:15.719830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110124 × 1018
5-th percentile1.1110156 × 1018
Q11.1177609 × 1018
median1.1440112 × 1018
Q31.1552608 × 1018
95-th percentile1.1740105 × 1018
Maximum1.1740109 × 1018
Range6.29985 × 1016
Interquartile range (IQR)3.7499925 × 1016

Descriptive statistics

Standard deviation2.2052855 × 1016
Coefficient of variation (CV)0.019352051
Kurtosis-1.3858669
Mean1.1395616 × 1018
Median Absolute Deviation (MAD)2.100055 × 1016
Skewness0.045955843
Sum-2.7066388 × 1018
Variance4.8632843 × 1032
MonotonicityNot monotonic
2024-04-18T05:13:15.812776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1153010200111230001 2
 
6.7%
1174010100103120092 1
 
3.3%
1153010200100030025 1
 
3.3%
1141011900102920001 1
 
3.3%
1171010100100500004 1
 
3.3%
1165010800113290008 1
 
3.3%
1123010700103170000 1
 
3.3%
1144012000104590007 1
 
3.3%
1111015600101440001 1
 
3.3%
1156011000100350000 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
1111012400100490000 1
3.3%
1111015600100390003 1
3.3%
1111015600101130000 1
3.3%
1111015600101440001 1
3.3%
1111016300100870001 1
3.3%
1114011700100030006 1
3.3%
1114016000100020032 1
3.3%
1117011100101110058 1
3.3%
1120010200109660014 1
3.3%
1121510500107940000 1
3.3%
ValueCountFrequency (%)
1174010900103600000 1
3.3%
1174010800104400030 1
3.3%
1174010100103120092 1
3.3%
1171010100100500004 1
3.3%
1165010800113290008 1
3.3%
1159010300103910000 1
3.3%
1156011000100350000 1
3.3%
1156011000100250003 1
3.3%
1153010200111230001 2
6.7%
1153010200104350000 1
3.3%

주변정보(WITH_INFO)
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing10
Missing (%)33.3%
Memory size372.0 B
2024-04-18T05:13:15.953892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length7.9
Min length4

Characters and Unicode

Total characters158
Distinct characters90
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)100.0%

Sample

1st rowING 타워 앞
2nd row우리은행앞
3rd row현민빌딩 앞
4th row신림시장 입구
5th row로즈데일 앞
ValueCountFrequency (%)
앞 8
22.9%
피자헛 1
 
2.9%
대양빌딩 1
 
2.9%
성임빌딩(아이월드안경점 1
 
2.9%
양재프라자약국앞 1
 
2.9%
848 1
 
2.9%
방화2동 1
 
2.9%
공덕역7번출구 1
 
2.9%
유니온빌딩 1
 
2.9%
디지털엘지 1
 
2.9%
Other values (18) 18
51.4%
2024-04-18T05:13:16.221070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
 
9.5%
앞 12
 
7.6%
지 5
 
3.2%
빌 4
 
2.5%
딩 4
 
2.5%
구 4
 
2.5%
역 3
 
1.9%
8 3
 
1.9%
아 3
 
1.9%
털 2
 
1.3%
Other values (80) 103
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 128
81.0%
Space Separator 15
 
9.5%
Decimal Number 10
 
6.3%
Uppercase Letter 3
 
1.9%
Open Punctuation 1
 
0.6%
Close Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 12
 
9.4%
지 5
 
3.9%
빌 4
 
3.1%
딩 4
 
3.1%
구 4
 
3.1%
역 3
 
2.3%
아 3
 
2.3%
털 2
 
1.6%
동 2
 
1.6%
상 2
 
1.6%
Other values (68) 87
68.0%
Decimal Number
ValueCountFrequency (%)
8 3
30.0%
3 2
20.0%
2 2
20.0%
4 1
 
10.0%
7 1
 
10.0%
0 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
I 1
33.3%
N 1
33.3%
G 1
33.3%
Space Separator
ValueCountFrequency (%)
15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 128
81.0%
Common 27
 
17.1%
Latin 3
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 12
 
9.4%
지 5
 
3.9%
빌 4
 
3.1%
딩 4
 
3.1%
구 4
 
3.1%
역 3
 
2.3%
아 3
 
2.3%
털 2
 
1.6%
동 2
 
1.6%
상 2
 
1.6%
Other values (68) 87
68.0%
Common
ValueCountFrequency (%)
15
55.6%
8 3
 
11.1%
3 2
 
7.4%
2 2
 
7.4%
4 1
 
3.7%
( 1
 
3.7%
7 1
 
3.7%
0 1
 
3.7%
) 1
 
3.7%
Latin
ValueCountFrequency (%)
I 1
33.3%
N 1
33.3%
G 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 128
81.0%
ASCII 30
 
19.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15
50.0%
8 3
 
10.0%
3 2
 
6.7%
2 2
 
6.7%
4 1
 
3.3%
( 1
 
3.3%
7 1
 
3.3%
0 1
 
3.3%
I 1
 
3.3%
N 1
 
3.3%
Other values (2) 2
 
6.7%
Hangul
ValueCountFrequency (%)
앞 12
 
9.4%
지 5
 
3.9%
빌 4
 
3.1%
딩 4
 
3.1%
구 4
 
3.1%
역 3
 
2.3%
아 3
 
2.3%
털 2
 
1.6%
동 2
 
1.6%
상 2
 
1.6%
Other values (68) 87
68.0%

도로정보(ROAD_INFO)
Text

MISSING 

Distinct6
Distinct (%)85.7%
Missing23
Missing (%)76.7%
Memory size372.0 B
2024-04-18T05:13:16.350780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length7.1428571
Min length2

Characters and Unicode

Total characters50
Distinct characters25
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

Unique5 ?
Unique (%)71.4%

Sample

1st row시도
2nd row창동 330-4
3rd row양재대로101길 46
4th row동남로81길 100 건너편
5th row시도
ValueCountFrequency (%)
시도 2
16.7%
창동 1
8.3%
330-4 1
8.3%
양재대로101길 1
8.3%
46 1
8.3%
동남로81길 1
8.3%
100 1
8.3%
건너편 1
8.3%
도봉동 1
8.3%
637-37 1
8.3%
2024-04-18T05:13:16.570652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
 
10.0%
3 4
 
8.0%
0 4
 
8.0%
1 4
 
8.0%
로 3
 
6.0%
도 3
 
6.0%
동 3
 
6.0%
7 2
 
4.0%
6 2
 
4.0%
길 2
 
4.0%
Other values (15) 18
36.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24
48.0%
Decimal Number 19
38.0%
Space Separator 5
 
10.0%
Dash Punctuation 2
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 3
12.5%
도 3
12.5%
동 3
12.5%
길 2
 
8.3%
시 2
 
8.3%
대 1
 
4.2%
재 1
 
4.2%
양 1
 
4.2%
남 1
 
4.2%
건 1
 
4.2%
Other values (6) 6
25.0%
Decimal Number
ValueCountFrequency (%)
3 4
21.1%
0 4
21.1%
1 4
21.1%
7 2
10.5%
6 2
10.5%
4 2
10.5%
8 1
 
5.3%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26
52.0%
Hangul 24
48.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 3
12.5%
도 3
12.5%
동 3
12.5%
길 2
 
8.3%
시 2
 
8.3%
대 1
 
4.2%
재 1
 
4.2%
양 1
 
4.2%
남 1
 
4.2%
건 1
 
4.2%
Other values (6) 6
25.0%
Common
ValueCountFrequency (%)
5
19.2%
3 4
15.4%
0 4
15.4%
1 4
15.4%
7 2
 
7.7%
6 2
 
7.7%
4 2
 
7.7%
- 2
 
7.7%
8 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26
52.0%
Hangul 24
48.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
19.2%
3 4
15.4%
0 4
15.4%
1 4
15.4%
7 2
 
7.7%
6 2
 
7.7%
4 2
 
7.7%
- 2
 
7.7%
8 1
 
3.8%
Hangul
ValueCountFrequency (%)
로 3
12.5%
도 3
12.5%
동 3
12.5%
길 2
 
8.3%
시 2
 
8.3%
대 1
 
4.2%
재 1
 
4.2%
양 1
 
4.2%
남 1
 
4.2%
건 1
 
4.2%
Other values (6) 6
25.0%

지역정보(AR_SEL)
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
17 
1
12 
2
 
1

Length

Max length4
Median length4
Mean length2.7
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row1
2nd row<NA>
3rd row<NA>
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 17
56.7%
1 12
40.0%
2 1
 
3.3%

Length

2024-04-18T05:13:16.671967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:13:16.749262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 17
56.7%
1 12
40.0%
2 1
 
3.3%

지역정보(AR_TXT)
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing26
Missing (%)86.7%
Memory size372.0 B
2024-04-18T05:13:16.830445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.75
Min length3

Characters and Unicode

Total characters15
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row천호대로
2nd row천호대로
3rd row왕산로
4th row올림픽로
ValueCountFrequency (%)
천호대로 2
50.0%
왕산로 1
25.0%
올림픽로 1
25.0%
2024-04-18T05:13:17.027045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 4
26.7%
천 2
13.3%
호 2
13.3%
대 2
13.3%
왕 1
 
6.7%
산 1
 
6.7%
올 1
 
6.7%
림 1
 
6.7%
픽 1
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 4
26.7%
천 2
13.3%
호 2
13.3%
대 2
13.3%
왕 1
 
6.7%
산 1
 
6.7%
올 1
 
6.7%
림 1
 
6.7%
픽 1
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 4
26.7%
천 2
13.3%
호 2
13.3%
대 2
13.3%
왕 1
 
6.7%
산 1
 
6.7%
올 1
 
6.7%
림 1
 
6.7%
픽 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 4
26.7%
천 2
13.3%
호 2
13.3%
대 2
13.3%
왕 1
 
6.7%
산 1
 
6.7%
올 1
 
6.7%
림 1
 
6.7%
픽 1
 
6.7%

인접시설(UC_SEL)
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
13 
9
7 
1
5 
3
4 
4
 
1

Length

Max length4
Median length1
Mean length2.3
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row<NA>
2nd row9
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 13
43.3%
9 7
23.3%
1 5
 
16.7%
3 4
 
13.3%
4 1
 
3.3%

Length

2024-04-18T05:13:17.132763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:13:17.215154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 13
43.3%
9 7
23.3%
1 5
 
16.7%
3 4
 
13.3%
4 1
 
3.3%

인접시설_메모(UC_TXT)
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing26
Missing (%)86.7%
Memory size372.0 B
2024-04-18T05:13:17.316594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10.5
Mean length10
Min length6

Characters and Unicode

Total characters40
Distinct characters23
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

Unique4 ?
Unique (%)100.0%

Sample

1st row대오빌딩 앞
2nd row5호선 장한평역 3번출구
3rd row여의역 4번 출구 앞
4th row여의나루역 2번출구
ValueCountFrequency (%)
앞 2
18.2%
대오빌딩 1
9.1%
5호선 1
9.1%
장한평역 1
9.1%
3번출구 1
9.1%
여의역 1
9.1%
4번 1
9.1%
출구 1
9.1%
여의나루역 1
9.1%
2번출구 1
9.1%
2024-04-18T05:13:17.526019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
17.5%
구 3
 
7.5%
출 3
 
7.5%
번 3
 
7.5%
역 3
 
7.5%
앞 2
 
5.0%
의 2
 
5.0%
여 2
 
5.0%
대 1
 
2.5%
3 1
 
2.5%
Other values (13) 13
32.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29
72.5%
Space Separator 7
 
17.5%
Decimal Number 4
 
10.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3
 
10.3%
출 3
 
10.3%
번 3
 
10.3%
역 3
 
10.3%
앞 2
 
6.9%
의 2
 
6.9%
여 2
 
6.9%
대 1
 
3.4%
루 1
 
3.4%
나 1
 
3.4%
Other values (8) 8
27.6%
Decimal Number
ValueCountFrequency (%)
3 1
25.0%
4 1
25.0%
5 1
25.0%
2 1
25.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29
72.5%
Common 11
 
27.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3
 
10.3%
출 3
 
10.3%
번 3
 
10.3%
역 3
 
10.3%
앞 2
 
6.9%
의 2
 
6.9%
여 2
 
6.9%
대 1
 
3.4%
루 1
 
3.4%
나 1
 
3.4%
Other values (8) 8
27.6%
Common
ValueCountFrequency (%)
7
63.6%
3 1
 
9.1%
4 1
 
9.1%
5 1
 
9.1%
2 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29
72.5%
ASCII 11
 
27.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
63.6%
3 1
 
9.1%
4 1
 
9.1%
5 1
 
9.1%
2 1
 
9.1%
Hangul
ValueCountFrequency (%)
구 3
 
10.3%
출 3
 
10.3%
번 3
 
10.3%
역 3
 
10.3%
앞 2
 
6.9%
의 2
 
6.9%
여 2
 
6.9%
대 1
 
3.4%
루 1
 
3.4%
나 1
 
3.4%
Other values (8) 8
27.6%

설치일자(FOUND_DATE)
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)82.4%
Missing13
Missing (%)43.3%
Infinite0
Infinite (%)0.0%
Mean20055704
Minimum19900101
Maximum20160617
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-18T05:13:17.619700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19900101
5-th percentile19940507
Q120000520
median20090402
Q320090416
95-th percentile20120455
Maximum20160617
Range260516
Interquartile range (IQR)89896

Descriptive statistics

Standard deviation66789.644
Coefficient of variation (CV)0.0033302069
Kurtosis0.38841347
Mean20055704
Median Absolute Deviation (MAD)627
Skewness-0.91206576
Sum3.4094697 × 108
Variance4.4608566 × 109
MonotonicityNot monotonic
2024-04-18T05:13:17.705220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
20090101 2
 
6.7%
20000101 2
 
6.7%
20090414 2
 
6.7%
20091029 1
 
3.3%
20160617 1
 
3.3%
20000520 1
 
3.3%
20010620 1
 
3.3%
20090416 1
 
3.3%
20110415 1
 
3.3%
20090402 1
 
3.3%
Other values (4) 4
 
13.3%
(Missing) 13
43.3%
ValueCountFrequency (%)
19900101 1
3.3%
19950608 1
3.3%
20000101 2
6.7%
20000520 1
3.3%
20010620 1
3.3%
20090101 2
6.7%
20090402 1
3.3%
20090407 1
3.3%
20090414 2
6.7%
20090416 1
3.3%
ValueCountFrequency (%)
20160617 1
3.3%
20110415 1
3.3%
20091029 1
3.3%
20090605 1
3.3%
20090416 1
3.3%
20090414 2
6.7%
20090407 1
3.3%
20090402 1
3.3%
20090101 2
6.7%
20010620 1
3.3%

시설물타입(FT_TYP)
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
12
21 
11
9 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11
2nd row12
3rd row12
4th row12
5th row11

Common Values

ValueCountFrequency (%)
12 21
70.0%
11 9
30.0%

Length

2024-04-18T05:13:17.792526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:13:17.864297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
12 21
70.0%
11 9
30.0%

시설물명(FT_SEL)
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
121
19 
112
9 
119
 
1
111
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row121
2nd row121
3rd row112
4th row112
5th row121

Common Values

ValueCountFrequency (%)
121 19
63.3%
112 9
30.0%
119 1
 
3.3%
111 1
 
3.3%

Length

2024-04-18T05:13:17.937332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:13:18.030880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
121 19
63.3%
112 9
30.0%
119 1
 
3.3%
111 1
 
3.3%

시설규격_가로(FACIL_L)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

시설규격_세로(FACIL_W)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

시설규격_높이(FACIL_H)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

점용면적_가로(PLACE_L)
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2.8
28 
1.3
 
1
2.5
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row2.8
2nd row2.8
3rd row2.8
4th row2.8
5th row2.8

Common Values

ValueCountFrequency (%)
2.8 28
93.3%
1.3 1
 
3.3%
2.5 1
 
3.3%

Length

2024-04-18T05:13:18.113374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:13:18.183949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2.8 28
93.3%
1.3 1
 
3.3%
2.5 1
 
3.3%

점용면적_세로(PLACE_H)
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
1.6
15 
1.4
14 
2.2
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row1.6
2nd row1.6
3rd row1.6
4th row1.4
5th row1.6

Common Values

ValueCountFrequency (%)
1.6 15
50.0%
1.4 14
46.7%
2.2 1
 
3.3%

Length

2024-04-18T05:13:18.260737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:13:18.331583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1.6 15
50.0%
1.4 14
46.7%
2.2 1
 
3.3%

점용면적_면적(PLACE_A)
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
4.48
16 
3.92
13 
3.5
 
1

Length

Max length4
Median length4
Mean length3.9666667
Min length3

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row3.92
2nd row3.92
3rd row3.92
4th row3.92
5th row4.48

Common Values

ValueCountFrequency (%)
4.48 16
53.3%
3.92 13
43.3%
3.5 1
 
3.3%

Length

2024-04-18T05:13:18.703559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:13:18.778312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4.48 16
53.3%
3.92 13
43.3%
3.5 1
 
3.3%

개점시간(IPEN_TIME)
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)91.7%
Missing18
Missing (%)60.0%
Infinite0
Infinite (%)0.0%
Mean1056.0833
Minimum600
Maximum1412
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-18T05:13:18.853860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600
5-th percentile620.35
Q1816.5
median1074
Q31326
95-th percentile1375.15
Maximum1412
Range812
Interquartile range (IQR)509.5

Descriptive statistics

Standard deviation287.26436
Coefficient of variation (CV)0.27200918
Kurtosis-1.3328493
Mean1056.0833
Median Absolute Deviation (MAD)252
Skewness-0.37468281
Sum12673
Variance82520.811
MonotonicityNot monotonic
2024-04-18T05:13:18.939360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1326 2
 
6.7%
800 1
 
3.3%
1345 1
 
3.3%
1257 1
 
3.3%
600 1
 
3.3%
1412 1
 
3.3%
822 1
 
3.3%
1031 1
 
3.3%
1000 1
 
3.3%
637 1
 
3.3%
(Missing) 18
60.0%
ValueCountFrequency (%)
600 1
3.3%
637 1
3.3%
800 1
3.3%
822 1
3.3%
1000 1
3.3%
1031 1
3.3%
1117 1
3.3%
1257 1
3.3%
1326 2
6.7%
1345 1
3.3%
ValueCountFrequency (%)
1412 1
3.3%
1345 1
3.3%
1326 2
6.7%
1257 1
3.3%
1117 1
3.3%
1031 1
3.3%
1000 1
3.3%
822 1
3.3%
800 1
3.3%
637 1
3.3%

폐점시간(CLOSE_TIME)
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)75.0%
Missing18
Missing (%)60.0%
Infinite0
Infinite (%)0.0%
Mean1773.9167
Minimum1017
Maximum2300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-18T05:13:19.022778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1017
5-th percentile1022.5
Q11311.25
median1950
Q32225
95-th percentile2300
Maximum2300
Range1283
Interquartile range (IQR)913.75

Descriptive statistics

Standard deviation516.65171
Coefficient of variation (CV)0.29124915
Kurtosis-1.3484514
Mean1773.9167
Median Absolute Deviation (MAD)350
Skewness-0.59723611
Sum21287
Variance266928.99
MonotonicityNot monotonic
2024-04-18T05:13:19.106885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2300 3
 
10.0%
2000 2
 
6.7%
1017 1
 
3.3%
1800 1
 
3.3%
1042 1
 
3.3%
2200 1
 
3.3%
1900 1
 
3.3%
1027 1
 
3.3%
1401 1
 
3.3%
(Missing) 18
60.0%
ValueCountFrequency (%)
1017 1
 
3.3%
1027 1
 
3.3%
1042 1
 
3.3%
1401 1
 
3.3%
1800 1
 
3.3%
1900 1
 
3.3%
2000 2
6.7%
2200 1
 
3.3%
2300 3
10.0%
ValueCountFrequency (%)
2300 3
10.0%
2200 1
 
3.3%
2000 2
6.7%
1900 1
 
3.3%
1800 1
 
3.3%
1401 1
 
3.3%
1042 1
 
3.3%
1027 1
 
3.3%
1017 1
 
3.3%

영업인원(MEN_NUM)
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
13 
<NA>
11 
0
5 
2
 
1

Length

Max length4
Median length1
Mean length2.1
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row1
2nd row1
3rd row<NA>
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
1 13
43.3%
<NA> 11
36.7%
0 5
 
16.7%
2 1
 
3.3%

Length

2024-04-18T05:13:19.211324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:13:19.296934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 13
43.3%
na 11
36.7%
0 5
 
16.7%
2 1
 
3.3%

허가일자(PERMIT_DATE)
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)63.2%
Missing11
Missing (%)36.7%
Infinite0
Infinite (%)0.0%
Mean20099788
Minimum20090101
Maximum20140725
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-18T05:13:19.371327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090101
5-th percentile20090101
Q120090101
median20090407
Q320095659
95-th percentile20140163
Maximum20140725
Range50624
Interquartile range (IQR)5558

Descriptive statistics

Standard deviation18121.224
Coefficient of variation (CV)0.00090156294
Kurtosis1.1791727
Mean20099788
Median Absolute Deviation (MAD)306
Skewness1.6584686
Sum3.8189597 × 108
Variance3.2837876 × 108
MonotonicityNot monotonic
2024-04-18T05:13:19.459655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
20090101 6
20.0%
20090406 2
 
6.7%
20090617 2
 
6.7%
20140101 1
 
3.3%
20090421 1
 
3.3%
20120101 1
 
3.3%
20100701 1
 
3.3%
20130320 1
 
3.3%
20090407 1
 
3.3%
20090428 1
 
3.3%
Other values (2) 2
 
6.7%
(Missing) 11
36.7%
ValueCountFrequency (%)
20090101 6
20.0%
20090116 1
 
3.3%
20090406 2
 
6.7%
20090407 1
 
3.3%
20090421 1
 
3.3%
20090428 1
 
3.3%
20090617 2
 
6.7%
20100701 1
 
3.3%
20120101 1
 
3.3%
20130320 1
 
3.3%
ValueCountFrequency (%)
20140725 1
3.3%
20140101 1
3.3%
20130320 1
3.3%
20120101 1
3.3%
20100701 1
3.3%
20090617 2
6.7%
20090428 1
3.3%
20090421 1
3.3%
20090407 1
3.3%
20090406 2
6.7%

일매출액(DAY_SALES)
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
28 
70000
 
1
200000
 
1

Length

Max length6
Median length4
Mean length4.1
Min length4

Unique

Unique2 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 28
93.3%
70000 1
 
3.3%
200000 1
 
3.3%

Length

2024-04-18T05:13:19.558997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:13:19.640135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 28
93.3%
70000 1
 
3.3%
200000 1
 
3.3%

가입단체(UN_TYP)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

가입단체명(UN_TXT)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

기타정보(NOTES)
Text

MISSING 

Distinct6
Distinct (%)85.7%
Missing23
Missing (%)76.7%
Memory size372.0 B
2024-04-18T05:13:19.774198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length113
Median length48
Mean length46.714286
Min length17

Characters and Unicode

Total characters327
Distinct characters96
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

Unique5 ?
Unique (%)71.4%

Sample

1st row로또판매점.우편번호 : 120-805
2nd row2011.7.21 접지공사 완료
3rd row2019.7.25. 도로명주소 부여됨(부동산정보과-12184. 2019.7.18)
4th row핫도그,햄버거,샌드위치,오징어류,김밥,신문,잡지류,음료,과자류,교통카드판매 및 카드충전
5th row도로점용허가 변경 처리 (2018.11.12.)기존 점용지 : 창동74-5 앞 도로 (창동311-1, 시도)도로점용허가 변경 처리 (2018.12.17.)도로점용허가 변경 처리 (2019. 3. 26.)
ValueCountFrequency (%)
처리 3
 
6.5%
변경 3
 
6.5%
2011.7.21 2
 
4.3%
완료 2
 
4.3%
접지공사 2
 
4.3%
2
 
4.3%
시설물 1
 
2.2%
2019 1
 
2.2%
3 1
 
2.2%
26 1
 
2.2%
Other values (28) 28
60.9%
2024-04-18T05:13:20.019284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
 
11.9%
1 28
 
8.6%
. 22
 
6.7%
2 17
 
5.2%
로 11
 
3.4%
0 10
 
3.1%
, 10
 
3.1%
도 8
 
2.4%
7 8
 
2.4%
용 7
 
2.1%
Other values (86) 167
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 155
47.4%
Decimal Number 82
25.1%
Space Separator 39
 
11.9%
Other Punctuation 34
 
10.4%
Close Punctuation 6
 
1.8%
Open Punctuation 6
 
1.8%
Dash Punctuation 5
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 11
 
7.1%
도 8
 
5.2%
용 7
 
4.5%
지 6
 
3.9%
점 6
 
3.9%
가 5
 
3.2%
변 4
 
2.6%
료 4
 
2.6%
공 4
 
2.6%
동 4
 
2.6%
Other values (69) 96
61.9%
Decimal Number
ValueCountFrequency (%)
1 28
34.1%
2 17
20.7%
0 10
 
12.2%
7 8
 
9.8%
8 5
 
6.1%
5 4
 
4.9%
3 3
 
3.7%
4 3
 
3.7%
9 3
 
3.7%
6 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 22
64.7%
, 10
29.4%
: 2
 
5.9%
Space Separator
ValueCountFrequency (%)
39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 172
52.6%
Hangul 155
47.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 11
 
7.1%
도 8
 
5.2%
용 7
 
4.5%
지 6
 
3.9%
점 6
 
3.9%
가 5
 
3.2%
변 4
 
2.6%
료 4
 
2.6%
공 4
 
2.6%
동 4
 
2.6%
Other values (69) 96
61.9%
Common
ValueCountFrequency (%)
39
22.7%
1 28
16.3%
. 22
12.8%
2 17
9.9%
0 10
 
5.8%
, 10
 
5.8%
7 8
 
4.7%
) 6
 
3.5%
( 6
 
3.5%
8 5
 
2.9%
Other values (7) 21
12.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 172
52.6%
Hangul 155
47.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
22.7%
1 28
16.3%
. 22
12.8%
2 17
9.9%
0 10
 
5.8%
, 10
 
5.8%
7 8
 
4.7%
) 6
 
3.5%
( 6
 
3.5%
8 5
 
2.9%
Other values (7) 21
12.2%
Hangul
ValueCountFrequency (%)
로 11
 
7.1%
도 8
 
5.2%
용 7
 
4.5%
지 6
 
3.9%
점 6
 
3.9%
가 5
 
3.2%
변 4
 
2.6%
료 4
 
2.6%
공 4
 
2.6%
동 4
 
2.6%
Other values (69) 96
61.9%

점용기간_시작일(MUL_FROMDATE)
Real number (ℝ)

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20187454
Minimum20150101
Maximum20200101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-18T05:13:20.124116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20150101
5-th percentile20150101
Q120180101
median20200101
Q320200101
95-th percentile20200101
Maximum20200101
Range50000
Interquartile range (IQR)20000

Descriptive statistics

Standard deviation17801.796
Coefficient of variation (CV)0.00088182473
Kurtosis0.01564524
Mean20187454
Median Absolute Deviation (MAD)0
Skewness-1.2212101
Sum6.0562363 × 108
Variance3.1690395 × 108
MonotonicityNot monotonic
2024-04-18T05:13:20.223919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20200101 16
53.3%
20190101 4
 
13.3%
20180101 3
 
10.0%
20150101 3
 
10.0%
20160101 3
 
10.0%
20190701 1
 
3.3%
ValueCountFrequency (%)
20150101 3
 
10.0%
20160101 3
 
10.0%
20180101 3
 
10.0%
20190101 4
 
13.3%
20190701 1
 
3.3%
20200101 16
53.3%
ValueCountFrequency (%)
20200101 16
53.3%
20190701 1
 
3.3%
20190101 4
 
13.3%
20180101 3
 
10.0%
20160101 3
 
10.0%
20150101 3
 
10.0%

점용기간_종료일(MUL_TODATE)
Real number (ℝ)

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20185231
Minimum20141231
Maximum20201231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-18T05:13:20.303141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20141231
5-th percentile20141231
Q120181231
median20191231
Q320201231
95-th percentile20201231
Maximum20201231
Range60000
Interquartile range (IQR)20000

Descriptive statistics

Standard deviation20611.346
Coefficient of variation (CV)0.0010211102
Kurtosis0.68225866
Mean20185231
Median Absolute Deviation (MAD)10000
Skewness-1.4166909
Sum6.0555693 × 108
Variance4.2482759 × 108
MonotonicityNot monotonic
2024-04-18T05:13:20.382486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20201231 11
36.7%
20191231 10
33.3%
20141231 4
 
13.3%
20181231 3
 
10.0%
20151231 1
 
3.3%
20171231 1
 
3.3%
ValueCountFrequency (%)
20141231 4
 
13.3%
20151231 1
 
3.3%
20171231 1
 
3.3%
20181231 3
 
10.0%
20191231 10
33.3%
20201231 11
36.7%
ValueCountFrequency (%)
20201231 11
36.7%
20191231 10
33.3%
20181231 3
 
10.0%
20171231 1
 
3.3%
20151231 1
 
3.3%
20141231 4
 
13.3%

점용지_동_행정동코드(HJ_CD)
Real number (ℝ)

Distinct20
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59403.333
Minimum51000
Maximum79000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-18T05:13:20.467998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum51000
5-th percentile51725
Q154125
median58550
Q361500
95-th percentile71300
Maximum79000
Range28000
Interquartile range (IQR)7375

Descriptive statistics

Standard deviation6565.1369
Coefficient of variation (CV)0.11051799
Kurtosis1.780466
Mean59403.333
Median Absolute Deviation (MAD)3800
Skewness1.1629794
Sum1782100
Variance43101023
MonotonicityNot monotonic
2024-04-18T05:13:20.555931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
58000 3
 
10.0%
61500 3
 
10.0%
52000 3
 
10.0%
59000 2
 
6.7%
54000 2
 
6.7%
60500 2
 
6.7%
65000 2
 
6.7%
62000 1
 
3.3%
57000 1
 
3.3%
51500 1
 
3.3%
Other values (10) 10
33.3%
ValueCountFrequency (%)
51000 1
 
3.3%
51500 1
 
3.3%
52000 3
10.0%
53500 1
 
3.3%
54000 2
6.7%
54500 1
 
3.3%
55000 1
 
3.3%
57000 1
 
3.3%
58000 3
10.0%
58100 1
 
3.3%
ValueCountFrequency (%)
79000 1
 
3.3%
74000 1
 
3.3%
68000 1
 
3.3%
66000 1
 
3.3%
65000 2
6.7%
62000 1
 
3.3%
61500 3
10.0%
61000 1
 
3.3%
60500 2
6.7%
59000 2
6.7%

폐쇄일(DISUSE_DATE)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

폐쇄사유(DISUSE_REASON)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

반환날짜(RETURN_DATE)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

반환여부(RETURN_YN)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

Sample

관리번호(GAPAN_NO)도형중심점X좌표(X_COORD)도형중심점Y좌표(Y_COORD)인접지지적(WITH_PNU)주변정보(WITH_INFO)도로정보(ROAD_INFO)지역정보(AR_SEL)지역정보(AR_TXT)인접시설(UC_SEL)인접시설_메모(UC_TXT)설치일자(FOUND_DATE)시설물타입(FT_TYP)시설물명(FT_SEL)시설규격_가로(FACIL_L)시설규격_세로(FACIL_W)시설규격_높이(FACIL_H)점용면적_가로(PLACE_L)점용면적_세로(PLACE_H)점용면적_면적(PLACE_A)개점시간(IPEN_TIME)폐점시간(CLOSE_TIME)영업인원(MEN_NUM)허가일자(PERMIT_DATE)일매출액(DAY_SALES)가입단체(UN_TYP)가입단체명(UN_TXT)기타정보(NOTES)점용기간_시작일(MUL_FROMDATE)점용기간_종료일(MUL_TODATE)점용지_동_행정동코드(HJ_CD)폐쇄일(DISUSE_DATE)폐쇄사유(DISUSE_REASON)반환날짜(RETURN_DATE)반환여부(RETURN_YN)
0680107_4_0004191582.53625445987.676481174010100103120092ING 타워 앞시도1<NA><NA><NA><NA>11121<NA><NA><NA>2.81.63.92<NA><NA>120090406<NA><NA><NA><NA>201801012020123158000<NA><NA><NA><NA>
1620103_4_0002203168.33893451245.318091159010300103910000우리은행앞<NA><NA><NA>9<NA><NA>12121<NA><NA><NA>2.81.63.92<NA><NA>120090617<NA><NA><NA>로또판매점.우편번호 : 120-805201501012018123154000<NA><NA><NA><NA>
2680105_4_0021204030.13146448047.847211174010800104400030<NA><NA><NA>천호대로<NA><NA>2009010112112<NA><NA><NA>2.81.63.928002300<NA>20140101<NA><NA><NA><NA>202001012020123155000<NA><NA><NA><NA>
3140116_4_0019209574.99674451794.851241153010200104350000현민빌딩 앞<NA>1<NA><NA><NA><NA>12112<NA><NA><NA>2.81.43.921345<NA>1<NA><NA><NA><NA>2011.7.21 접지공사 완료202001012019123159000<NA><NA><NA><NA>
4305101_4_0022198408.85204446878.255931138010600100040001신림시장 입구<NA>1<NA><NA><NA>2009102911121<NA><NA><NA>2.81.64.48<NA>2000<NA>20090421<NA><NA><NA>2019.7.25. 도로명주소 부여됨(부동산정보과-12184. 2019.7.18)202001012020123158100<NA><NA><NA><NA>
5470103_4_0006195179.41507458434.93021153010200111230001로즈데일 앞<NA>1<NA><NA><NA>2009010112121<NA><NA><NA>2.81.64.48<NA><NA><NA>20120101<NA><NA><NA>핫도그,햄버거,샌드위치,오징어류,김밥,신문,잡지류,음료,과자류,교통카드판매 및 카드충전201501012019123168000<NA><NA><NA><NA>
6320107_4_0010200606.08364453490.089911147010300101460001역삼하이츠 앞<NA><NA>천호대로<NA><NA>2000010111121<NA><NA><NA>2.81.44.48<NA>1017<NA><NA><NA><NA><NA><NA>201601012020123161500<NA><NA><NA><NA>
7170131_4_0002187800.44258460843.234011114016000100020032삼익아파트 208동 옆<NA><NA><NA><NA><NA><NA>11121<NA><NA><NA>2.81.63.5<NA><NA>020090101<NA><NA><NA><NA>201901012019123179000<NA><NA><NA><NA>
8140114_4_0004201777.21067449092.493121117011100101110058상계주공3단지아파트 상가<NA><NA><NA>1<NA>2016061712121<NA><NA><NA>2.81.64.48<NA>180012009010170000<NA><NA><NA>202001012020123152000<NA><NA><NA><NA>
9290105_4_0002206261.07452454347.211071121510500107940000구로디지털단지역3번출구<NA>1<NA>3대오빌딩 앞<NA>12121<NA><NA><NA>2.81.44.481257<NA>020090101<NA><NA><NA><NA>201901012019123151000<NA><NA><NA><NA>
관리번호(GAPAN_NO)도형중심점X좌표(X_COORD)도형중심점Y좌표(Y_COORD)인접지지적(WITH_PNU)주변정보(WITH_INFO)도로정보(ROAD_INFO)지역정보(AR_SEL)지역정보(AR_TXT)인접시설(UC_SEL)인접시설_메모(UC_TXT)설치일자(FOUND_DATE)시설물타입(FT_TYP)시설물명(FT_SEL)시설규격_가로(FACIL_L)시설규격_세로(FACIL_W)시설규격_높이(FACIL_H)점용면적_가로(PLACE_L)점용면적_세로(PLACE_H)점용면적_면적(PLACE_A)개점시간(IPEN_TIME)폐점시간(CLOSE_TIME)영업인원(MEN_NUM)허가일자(PERMIT_DATE)일매출액(DAY_SALES)가입단체(UN_TYP)가입단체명(UN_TXT)기타정보(NOTES)점용기간_시작일(MUL_FROMDATE)점용기간_종료일(MUL_TODATE)점용지_동_행정동코드(HJ_CD)폐쇄일(DISUSE_DATE)폐쇄사유(DISUSE_REASON)반환날짜(RETURN_DATE)반환여부(RETURN_YN)
20620102_4_0016195413.64166463802.260331144010400105590000<NA><NA><NA><NA>4<NA>2009041411121<NA><NA><NA>2.81.64.481326<NA>1<NA><NA><NA><NA><NA>202001012020123161500<NA><NA><NA><NA>
21170125_4_0019198743.48135452089.31661156011000100250003답십리변정형외과앞<NA><NA><NA>9<NA><NA>12121<NA><NA><NA>2.81.63.92<NA><NA><NA><NA><NA><NA><NA><NA>202001012014123152000<NA><NA><NA><NA>
22215107_4_0006198437.72083451253.573091111016300100870001디지털엘지 앞<NA><NA><NA><NA><NA>2009060512121<NA><NA><NA>2.81.43.92<NA><NA>120090101<NA><NA><NA><NA>201801012019123165000<NA><NA><NA><NA>
23560105_4_0076199080.89844460785.606451156011000100350000유니온빌딩 앞동남로81길 100 건너편2<NA>9<NA><NA>12112<NA><NA><NA>2.81.64.48<NA><NA>2<NA><NA><NA><NA><NA>202001012020123152000<NA><NA><NA><NA>
24680108_4_0012199615.23223452488.825771111015600101440001공덕역7번출구<NA><NA><NA><NA><NA>1995060811121<NA><NA><NA>2.81.64.488222300<NA><NA><NA><NA><NA>2011.7.21 접지공사 완료202001012019123161000<NA><NA><NA><NA>
25110119_4_0005204042.21897451650.188121144012000104590007<NA><NA>1<NA>9<NA><NA>12112<NA><NA><NA>2.81.64.4810311401<NA><NA><NA><NA><NA><NA>202001012014123166000<NA><NA><NA><NA>
26560132_4_0051199430.84329447186.955021123010700103170000방화2동 848시도<NA><NA><NA><NA>2009040712121<NA><NA><NA>2.81.44.481000<NA><NA>20090617<NA><NA><NA><NA>201901012020123158000<NA><NA><NA><NA>
27710107_4_0033205665.89228442632.961181165010800113290008<NA>도봉동 637-371<NA>9<NA>1990010112112<NA><NA><NA>2.82.23.926372000020090116<NA><NA><NA><NA>202001012017123154500<NA><NA><NA><NA>
28680101_4_0038198265.86045451324.42371171010100100500004양재프라자약국앞뚝섬로1<NA><NA><NA>2000010112112<NA><NA><NA>2.81.44.481117<NA>120090406200000<NA><NA>중앙차로노선공사로 시설물 이전(2017.11.14 )으로 인한 도로점용료 변동공시지가 적용은 종로5가 273-1번지 적용201901012018123151500<NA><NA><NA><NA>
29110174_4_0008192675.85985447136.098241141011900102920001국민은행앞<NA>1<NA>3<NA><NA>12112<NA><NA><NA>2.81.43.92<NA><NA>120140725<NA><NA><NA><NA>201601012014123157000<NA><NA><NA><NA>