Overview

Dataset statistics

Number of variables64
Number of observations1238
Missing cells26688
Missing cells (%)33.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory673.5 KiB
Average record size in memory557.1 B

Variable types

Numeric19
Categorical25
Text6
Unsupported13
DateTime1

Dataset

Description2021-09-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123072

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
문화체육업종명 has constant value ""Constant
상세영업상태명 is highly imbalanced (52.1%)Imbalance
휴업시작일자 is highly imbalanced (98.2%)Imbalance
휴업종료일자 is highly imbalanced (98.2%)Imbalance
지역구분명 is highly imbalanced (68.5%)Imbalance
주변환경명 is highly imbalanced (73.1%)Imbalance
건물용도명 is highly imbalanced (71.6%)Imbalance
객실수 is highly imbalanced (82.7%)Imbalance
건축연면적 is highly imbalanced (82.7%)Imbalance
영문상호주소 is highly imbalanced (93.6%)Imbalance
선박총톤수 is highly imbalanced (82.7%)Imbalance
선박척수 is highly imbalanced (82.7%)Imbalance
무대면적 is highly imbalanced (82.7%)Imbalance
좌석수 is highly imbalanced (82.7%)Imbalance
회의실별동시수용인원 is highly imbalanced (82.7%)Imbalance
놀이시설수 is highly imbalanced (82.7%)Imbalance
기획여행보험시작일자 is highly imbalanced (99.1%)Imbalance
기획여행보험종료일자 is highly imbalanced (99.1%)Imbalance
인허가취소일자 has 1192 (96.3%) missing valuesMissing
폐업일자 has 633 (51.1%) missing valuesMissing
재개업일자 has 1238 (100.0%) missing valuesMissing
소재지전화 has 300 (24.2%) missing valuesMissing
소재지면적 has 1238 (100.0%) missing valuesMissing
소재지우편번호 has 570 (46.0%) missing valuesMissing
도로명전체주소 has 56 (4.5%) missing valuesMissing
도로명우편번호 has 400 (32.3%) missing valuesMissing
업태구분명 has 1238 (100.0%) missing valuesMissing
좌표정보(x) has 37 (3.0%) missing valuesMissing
좌표정보(y) has 37 (3.0%) missing valuesMissing
총층수 has 998 (80.6%) missing valuesMissing
제작취급품목내용 has 1238 (100.0%) missing valuesMissing
지상층수 has 978 (79.0%) missing valuesMissing
지하층수 has 1087 (87.8%) missing valuesMissing
영문상호명 has 1209 (97.7%) missing valuesMissing
선박제원 has 1238 (100.0%) missing valuesMissing
기념품종류 has 1238 (100.0%) missing valuesMissing
시설면적 has 916 (74.0%) missing valuesMissing
놀이기구수내역 has 1238 (100.0%) missing valuesMissing
방송시설유무 has 1238 (100.0%) missing valuesMissing
발전시설유무 has 1238 (100.0%) missing valuesMissing
의무실유무 has 1238 (100.0%) missing valuesMissing
안내소유무 has 1238 (100.0%) missing valuesMissing
자본금 has 426 (34.4%) missing valuesMissing
보험시작일자 has 420 (33.9%) missing valuesMissing
보험종료일자 has 419 (33.8%) missing valuesMissing
부대시설내역 has 1238 (100.0%) missing valuesMissing
시설규모 has 916 (74.0%) missing valuesMissing
Unnamed: 63 has 1238 (100.0%) missing valuesMissing
번호 has unique valuesUnique
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
제작취급품목내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
선박제원 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기념품종류 is an unsupported type, check if it needs cleaning or further analysisUnsupported
놀이기구수내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방송시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
발전시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
의무실유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
안내소유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부대시설내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 63 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총층수 has 43 (3.5%) zerosZeros
지상층수 has 39 (3.2%) zerosZeros
지하층수 has 55 (4.4%) zerosZeros
시설면적 has 40 (3.2%) zerosZeros
시설규모 has 40 (3.2%) zerosZeros

Reproduction

Analysis started2024-04-16 06:50:02.594760
Analysis finished2024-04-16 06:50:03.656551
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1238
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean619.5
Minimum1
Maximum1238
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:03.712334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile62.85
Q1310.25
median619.5
Q3928.75
95-th percentile1176.15
Maximum1238
Range1237
Interquartile range (IQR)618.5

Descriptive statistics

Standard deviation357.52413
Coefficient of variation (CV)0.57711723
Kurtosis-1.2
Mean619.5
Median Absolute Deviation (MAD)309.5
Skewness0
Sum766941
Variance127823.5
MonotonicityStrictly increasing
2024-04-16T15:50:03.821071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
825 1
 
0.1%
832 1
 
0.1%
831 1
 
0.1%
830 1
 
0.1%
829 1
 
0.1%
828 1
 
0.1%
827 1
 
0.1%
826 1
 
0.1%
824 1
 
0.1%
Other values (1228) 1228
99.2%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1238 1
0.1%
1237 1
0.1%
1236 1
0.1%
1235 1
0.1%
1234 1
0.1%
1233 1
0.1%
1232 1
0.1%
1231 1
0.1%
1230 1
0.1%
1229 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
국내여행업
1238 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내여행업 1238
100.0%

Length

2024-04-16T15:50:03.922985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:03.992042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내여행업 1238
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
03_12_01_P
1238 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row03_12_01_P
2nd row03_12_01_P
3rd row03_12_01_P
4th row03_12_01_P
5th row03_12_01_P

Common Values

ValueCountFrequency (%)
03_12_01_P 1238
100.0%

Length

2024-04-16T15:50:04.276014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:04.349810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_12_01_p 1238
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3310274.6
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:04.417454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3250000
Q13290000
median3300000
Q33340000
95-th percentile3380000
Maximum3400000
Range150000
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation41240.923
Coefficient of variation (CV)0.01245846
Kurtosis-0.86010401
Mean3310274.6
Median Absolute Deviation (MAD)30000
Skewness0.37448591
Sum4.09812 × 109
Variance1.7008138 × 109
MonotonicityNot monotonic
2024-04-16T15:50:04.508044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 266
21.5%
3250000 143
11.6%
3330000 138
11.1%
3270000 131
10.6%
3300000 100
 
8.1%
3370000 97
 
7.8%
3310000 71
 
5.7%
3350000 61
 
4.9%
3380000 59
 
4.8%
3340000 39
 
3.2%
Other values (6) 133
10.7%
ValueCountFrequency (%)
3250000 143
11.6%
3260000 13
 
1.1%
3270000 131
10.6%
3280000 18
 
1.5%
3290000 266
21.5%
3300000 100
 
8.1%
3310000 71
 
5.7%
3320000 34
 
2.7%
3330000 138
11.1%
3340000 39
 
3.2%
ValueCountFrequency (%)
3400000 14
 
1.1%
3390000 35
 
2.8%
3380000 59
4.8%
3370000 97
7.8%
3360000 19
 
1.5%
3350000 61
4.9%
3340000 39
 
3.2%
3330000 138
11.1%
3320000 34
 
2.7%
3310000 71
5.7%
Distinct356
Distinct (%)28.8%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
2024-04-16T15:50:04.672507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters24760
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)9.0%

Sample

1st rowCDFI2260012007000013
2nd rowCDFI2260012019000002
3rd rowCDFI2260012019000006
4th rowCDFI2260011997000006
5th rowCDFI2260011994000001
ValueCountFrequency (%)
cdfi2260012011000001 15
 
1.2%
cdfi2260012019000001 14
 
1.1%
cdfi2260012020000001 14
 
1.1%
cdfi2260012021000001 13
 
1.1%
cdfi2260012016000001 13
 
1.1%
cdfi2260012019000002 13
 
1.1%
cdfi2260012020000002 12
 
1.0%
cdfi2260012001000001 12
 
1.0%
cdfi2260012017000002 12
 
1.0%
cdfi2260012018000002 12
 
1.0%
Other values (346) 1108
89.5%
2024-04-16T15:50:04.931253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10178
41.1%
2 4033
 
16.3%
1 2556
 
10.3%
6 1470
 
5.9%
C 1238
 
5.0%
D 1238
 
5.0%
F 1238
 
5.0%
I 1238
 
5.0%
9 432
 
1.7%
4 246
 
1.0%
Other values (4) 893
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19808
80.0%
Uppercase Letter 4952
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10178
51.4%
2 4033
 
20.4%
1 2556
 
12.9%
6 1470
 
7.4%
9 432
 
2.2%
4 246
 
1.2%
5 244
 
1.2%
3 241
 
1.2%
7 232
 
1.2%
8 176
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
C 1238
25.0%
D 1238
25.0%
F 1238
25.0%
I 1238
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19808
80.0%
Latin 4952
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10178
51.4%
2 4033
 
20.4%
1 2556
 
12.9%
6 1470
 
7.4%
9 432
 
2.2%
4 246
 
1.2%
5 244
 
1.2%
3 241
 
1.2%
7 232
 
1.2%
8 176
 
0.9%
Latin
ValueCountFrequency (%)
C 1238
25.0%
D 1238
25.0%
F 1238
25.0%
I 1238
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24760
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10178
41.1%
2 4033
 
16.3%
1 2556
 
10.3%
6 1470
 
5.9%
C 1238
 
5.0%
D 1238
 
5.0%
F 1238
 
5.0%
I 1238
 
5.0%
9 432
 
1.7%
4 246
 
1.0%
Other values (4) 893
 
3.6%

인허가일자
Real number (ℝ)

Distinct1093
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20095205
Minimum19840924
Maximum20210727
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:05.051195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19840924
5-th percentile19970420
Q120041147
median20101117
Q320151118
95-th percentile20200133
Maximum20210727
Range369803
Interquartile range (IQR)109971.25

Descriptive statistics

Standard deviation72151.37
Coefficient of variation (CV)0.0035904769
Kurtosis-0.46634608
Mean20095205
Median Absolute Deviation (MAD)50807.5
Skewness-0.46942783
Sum2.4877864 × 1010
Variance5.2058203 × 109
MonotonicityNot monotonic
2024-04-16T15:50:05.163267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20051123 4
 
0.3%
20190328 4
 
0.3%
20120402 3
 
0.2%
20150209 3
 
0.2%
20151006 3
 
0.2%
20140721 3
 
0.2%
20020302 3
 
0.2%
20180628 3
 
0.2%
20160129 3
 
0.2%
20160713 3
 
0.2%
Other values (1083) 1206
97.4%
ValueCountFrequency (%)
19840924 1
0.1%
19861025 1
0.1%
19890220 1
0.1%
19890710 1
0.1%
19900313 1
0.1%
19900802 1
0.1%
19910325 1
0.1%
19910423 1
0.1%
19910918 1
0.1%
19911001 1
0.1%
ValueCountFrequency (%)
20210727 1
0.1%
20210719 1
0.1%
20210707 1
0.1%
20210625 2
0.2%
20210616 1
0.1%
20210609 1
0.1%
20210608 1
0.1%
20210603 1
0.1%
20210506 1
0.1%
20210414 1
0.1%

인허가취소일자
Real number (ℝ)

MISSING 

Distinct40
Distinct (%)87.0%
Missing1192
Missing (%)96.3%
Infinite0
Infinite (%)0.0%
Mean20142395
Minimum20030822
Maximum20200226
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:05.277798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030822
5-th percentile20061065
Q120110712
median20160576
Q320171224
95-th percentile20190515
Maximum20200226
Range169404
Interquartile range (IQR)60512

Descriptive statistics

Standard deviation46665.128
Coefficient of variation (CV)0.0023167616
Kurtosis-0.44030539
Mean20142395
Median Absolute Deviation (MAD)24991
Skewness-0.83392341
Sum9.2655018 × 108
Variance2.1776342 × 109
MonotonicityNot monotonic
2024-04-16T15:50:05.388239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
20190305 3
 
0.2%
20190515 2
 
0.2%
20141007 2
 
0.2%
20170424 2
 
0.2%
20170705 2
 
0.2%
20070123 1
 
0.1%
20080813 1
 
0.1%
20040902 1
 
0.1%
20030822 1
 
0.1%
20151117 1
 
0.1%
Other values (30) 30
 
2.4%
(Missing) 1192
96.3%
ValueCountFrequency (%)
20030822 1
0.1%
20040902 1
0.1%
20061011 1
0.1%
20061228 1
0.1%
20070123 1
0.1%
20070510 1
0.1%
20080509 1
0.1%
20080813 1
0.1%
20090724 1
0.1%
20091007 1
0.1%
ValueCountFrequency (%)
20200226 1
 
0.1%
20200224 1
 
0.1%
20190515 2
0.2%
20190305 3
0.2%
20190213 1
 
0.1%
20180921 1
 
0.1%
20180917 1
 
0.1%
20180530 1
 
0.1%
20171229 1
 
0.1%
20171211 1
 
0.1%
Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
3
601 
1
566 
4
66 
2
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 601
48.5%
1 566
45.7%
4 66
 
5.3%
2 5
 
0.4%

Length

2024-04-16T15:50:05.499949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:05.583558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 601
48.5%
1 566
45.7%
4 66
 
5.3%
2 5
 
0.4%

영업상태명
Categorical

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
폐업
601 
영업/정상
566 
취소/말소/만료/정지/중지
66 
휴업
 
5

Length

Max length14
Median length5
Mean length4.0113086
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row휴업
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 601
48.5%
영업/정상 566
45.7%
취소/말소/만료/정지/중지 66
 
5.3%
휴업 5
 
0.4%

Length

2024-04-16T15:50:05.673548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:05.754019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 601
48.5%
영업/정상 566
45.7%
취소/말소/만료/정지/중지 66
 
5.3%
휴업 5
 
0.4%

상세영업상태코드
Real number (ℝ)

Distinct7
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.0662359
Minimum2
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:05.823346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q13
median13
Q313
95-th percentile30
Maximum35
Range33
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.152489
Coefficient of variation (CV)0.78891495
Kurtosis2.22198
Mean9.0662359
Median Absolute Deviation (MAD)10
Skewness1.3540638
Sum11224
Variance51.158099
MonotonicityNot monotonic
2024-04-16T15:50:05.902295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3 601
48.5%
13 566
45.7%
31 45
 
3.6%
30 15
 
1.2%
2 5
 
0.4%
35 5
 
0.4%
33 1
 
0.1%
ValueCountFrequency (%)
2 5
 
0.4%
3 601
48.5%
13 566
45.7%
30 15
 
1.2%
31 45
 
3.6%
33 1
 
0.1%
35 5
 
0.4%
ValueCountFrequency (%)
35 5
 
0.4%
33 1
 
0.1%
31 45
 
3.6%
30 15
 
1.2%
13 566
45.7%
3 601
48.5%
2 5
 
0.4%

상세영업상태명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
폐업
601 
영업중
566 
등록취소
 
45
허가취소
 
15
휴업
 
5
Other values (2)
 
6

Length

Max length4
Median length3
Mean length2.5638126
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row휴업
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 601
48.5%
영업중 566
45.7%
등록취소 45
 
3.6%
허가취소 15
 
1.2%
휴업 5
 
0.4%
직권말소 5
 
0.4%
지정취소 1
 
0.1%

Length

2024-04-16T15:50:06.008921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:06.154919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 601
48.5%
영업중 566
45.7%
등록취소 45
 
3.6%
허가취소 15
 
1.2%
휴업 5
 
0.4%
직권말소 5
 
0.4%
지정취소 1
 
0.1%

폐업일자
Real number (ℝ)

MISSING 

Distinct544
Distinct (%)89.9%
Missing633
Missing (%)51.1%
Infinite0
Infinite (%)0.0%
Mean20116332
Minimum19971211
Maximum20210604
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:06.338033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19971211
5-th percentile20010564
Q120070307
median20120807
Q320170719
95-th percentile20200789
Maximum20210604
Range239393
Interquartile range (IQR)100412

Descriptive statistics

Standard deviation60827.07
Coefficient of variation (CV)0.0030237654
Kurtosis-1.0417693
Mean20116332
Median Absolute Deviation (MAD)50209
Skewness-0.26009618
Sum1.2170381 × 1010
Variance3.6999325 × 109
MonotonicityNot monotonic
2024-04-16T15:50:06.483371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000111 9
 
0.7%
20001129 5
 
0.4%
20150723 3
 
0.2%
20190630 3
 
0.2%
20190709 3
 
0.2%
20200825 2
 
0.2%
20140526 2
 
0.2%
20060119 2
 
0.2%
20131231 2
 
0.2%
20181126 2
 
0.2%
Other values (534) 572
46.2%
(Missing) 633
51.1%
ValueCountFrequency (%)
19971211 1
 
0.1%
19990403 1
 
0.1%
19990408 1
 
0.1%
19990524 1
 
0.1%
19990622 1
 
0.1%
19990909 1
 
0.1%
19991104 1
 
0.1%
20000111 9
0.7%
20000128 1
 
0.1%
20000229 1
 
0.1%
ValueCountFrequency (%)
20210604 1
0.1%
20210524 1
0.1%
20210405 1
0.1%
20210331 1
0.1%
20210305 1
0.1%
20210216 1
0.1%
20210203 1
0.1%
20210201 1
0.1%
20210127 1
0.1%
20210112 1
0.1%

휴업시작일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
1233 
20210101
 
1
20201201
 
1
20200401
 
1
20130510
 
1

Length

Max length8
Median length4
Mean length4.0161551
Min length4

Unique

Unique5 ?
Unique (%)0.4%

Sample

1st row20210101
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1233
99.6%
20210101 1
 
0.1%
20201201 1
 
0.1%
20200401 1
 
0.1%
20130510 1
 
0.1%
20130902 1
 
0.1%

Length

2024-04-16T15:50:06.625396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:06.714413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1233
99.6%
20210101 1
 
0.1%
20201201 1
 
0.1%
20200401 1
 
0.1%
20130510 1
 
0.1%
20130902 1
 
0.1%

휴업종료일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
1233 
20211231
 
1
20211130
 
1
20210930
 
1
20140509
 
1

Length

Max length8
Median length4
Mean length4.0161551
Min length4

Unique

Unique5 ?
Unique (%)0.4%

Sample

1st row20211231
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1233
99.6%
20211231 1
 
0.1%
20211130 1
 
0.1%
20210930 1
 
0.1%
20140509 1
 
0.1%
20140904 1
 
0.1%

Length

2024-04-16T15:50:06.812843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:06.901641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1233
99.6%
20211231 1
 
0.1%
20211130 1
 
0.1%
20210930 1
 
0.1%
20140509 1
 
0.1%
20140904 1
 
0.1%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1238
Missing (%)100.0%
Memory size11.0 KiB

소재지전화
Text

MISSING 

Distinct906
Distinct (%)96.6%
Missing300
Missing (%)24.2%
Memory size9.8 KiB
2024-04-16T15:50:07.084271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length10.646055
Min length1

Characters and Unicode

Total characters9986
Distinct characters16
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique878 ?
Unique (%)93.6%

Sample

1st row469-7731
2nd row051241 0909
3rd row051-464-6464
4th row254-4061
5th row246-1003
ValueCountFrequency (%)
051 31
 
3.1%
5
 
0.5%
740-6353 3
 
0.3%
051-467-5111 2
 
0.2%
809 2
 
0.2%
261 2
 
0.2%
051-311-2133 2
 
0.2%
808-2211 2
 
0.2%
702-8260 2
 
0.2%
051-266-5600 2
 
0.2%
Other values (922) 943
94.7%
2024-04-16T15:50:07.383239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1577
15.8%
- 1435
14.4%
1 1339
13.4%
5 1309
13.1%
6 738
7.4%
8 717
7.2%
4 673
6.7%
2 630
 
6.3%
7 612
 
6.1%
3 489
 
4.9%
Other values (6) 467
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8464
84.8%
Dash Punctuation 1435
 
14.4%
Space Separator 58
 
0.6%
Close Punctuation 16
 
0.2%
Other Punctuation 9
 
0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1577
18.6%
1 1339
15.8%
5 1309
15.5%
6 738
8.7%
8 717
8.5%
4 673
8.0%
2 630
 
7.4%
7 612
 
7.2%
3 489
 
5.8%
9 380
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 7
77.8%
, 2
 
22.2%
Dash Punctuation
ValueCountFrequency (%)
- 1435
100.0%
Space Separator
ValueCountFrequency (%)
58
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9986
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1577
15.8%
- 1435
14.4%
1 1339
13.4%
5 1309
13.1%
6 738
7.4%
8 717
7.2%
4 673
6.7%
2 630
 
6.3%
7 612
 
6.1%
3 489
 
4.9%
Other values (6) 467
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9986
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1577
15.8%
- 1435
14.4%
1 1339
13.4%
5 1309
13.1%
6 738
7.4%
8 717
7.2%
4 673
6.7%
2 630
 
6.3%
7 612
 
6.1%
3 489
 
4.9%
Other values (6) 467
 
4.7%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1238
Missing (%)100.0%
Memory size11.0 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct309
Distinct (%)46.3%
Missing570
Missing (%)46.0%
Infinite0
Infinite (%)0.0%
Mean609794.03
Minimum600011
Maximum701814
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:07.505790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile600100
Q1602828
median611802
Q3614822.25
95-th percentile616852
Maximum701814
Range101803
Interquartile range (IQR)11994.25

Descriptive statistics

Standard deviation7784.5688
Coefficient of variation (CV)0.012765899
Kurtosis49.280707
Mean609794.03
Median Absolute Deviation (MAD)3058.5
Skewness4.6281746
Sum4.0734241 × 108
Variance60599511
MonotonicityNot monotonic
2024-04-16T15:50:07.629843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
600815 17
 
1.4%
614854 16
 
1.3%
614844 11
 
0.9%
614849 11
 
0.9%
601839 10
 
0.8%
612824 10
 
0.8%
607827 10
 
0.8%
614828 9
 
0.7%
601715 9
 
0.7%
600100 8
 
0.6%
Other values (299) 557
45.0%
(Missing) 570
46.0%
ValueCountFrequency (%)
600011 1
 
0.1%
600012 2
 
0.2%
600013 4
0.3%
600014 6
0.5%
600015 2
 
0.2%
600016 3
0.2%
600022 3
0.2%
600023 1
 
0.1%
600031 1
 
0.1%
600032 1
 
0.1%
ValueCountFrequency (%)
701814 1
0.1%
682818 1
0.1%
680828 1
0.1%
619952 1
0.1%
619906 1
0.1%
619905 1
0.1%
619903 1
0.1%
618814 1
0.1%
618708 1
0.1%
618200 1
0.1%
Distinct1162
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
2024-04-16T15:50:07.889386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length39
Mean length25.920032
Min length12

Characters and Unicode

Total characters32089
Distinct characters384
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1109 ?
Unique (%)89.6%

Sample

1st row부산광역시 중구 중앙동4가 53-30
2nd row부산광역시 중구 남포동4가 44-3번지
3rd row부산광역시 중구 중앙동4가 15-3번지
4th row부산광역시 중구 남포동5가 39-6번지
5th row부산광역시 중구 남포동6가 113-1번지
ValueCountFrequency (%)
부산광역시 1235
 
20.0%
부산진구 266
 
4.3%
중구 143
 
2.3%
해운대구 138
 
2.2%
동구 132
 
2.1%
동래구 101
 
1.6%
연제구 97
 
1.6%
초량동 92
 
1.5%
부전동 92
 
1.5%
남구 70
 
1.1%
Other values (1781) 3804
61.7%
2024-04-16T15:50:08.267648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4932
 
15.4%
1671
 
5.2%
1625
 
5.1%
1 1613
 
5.0%
1582
 
4.9%
1278
 
4.0%
1270
 
4.0%
1251
 
3.9%
1244
 
3.9%
- 1091
 
3.4%
Other values (374) 14532
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18824
58.7%
Decimal Number 6892
 
21.5%
Space Separator 4932
 
15.4%
Dash Punctuation 1091
 
3.4%
Lowercase Letter 154
 
0.5%
Uppercase Letter 152
 
0.5%
Open Punctuation 16
 
< 0.1%
Close Punctuation 16
 
< 0.1%
Other Punctuation 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1671
 
8.9%
1625
 
8.6%
1582
 
8.4%
1278
 
6.8%
1270
 
6.7%
1251
 
6.6%
1244
 
6.6%
735
 
3.9%
696
 
3.7%
374
 
2.0%
Other values (320) 7098
37.7%
Uppercase Letter
ValueCountFrequency (%)
S 34
22.4%
T 20
13.2%
C 14
9.2%
K 13
 
8.6%
A 11
 
7.2%
B 11
 
7.2%
E 7
 
4.6%
I 6
 
3.9%
O 6
 
3.9%
H 5
 
3.3%
Other values (10) 25
16.4%
Lowercase Letter
ValueCountFrequency (%)
e 33
21.4%
o 21
13.6%
l 12
 
7.8%
i 11
 
7.1%
p 11
 
7.1%
d 10
 
6.5%
m 10
 
6.5%
a 10
 
6.5%
x 10
 
6.5%
w 10
 
6.5%
Other values (7) 16
10.4%
Decimal Number
ValueCountFrequency (%)
1 1613
23.4%
2 958
13.9%
3 754
10.9%
4 681
9.9%
0 645
 
9.4%
5 509
 
7.4%
7 480
 
7.0%
8 469
 
6.8%
6 452
 
6.6%
9 331
 
4.8%
Other Punctuation
ValueCountFrequency (%)
/ 7
58.3%
, 4
33.3%
@ 1
 
8.3%
Space Separator
ValueCountFrequency (%)
4932
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1091
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18824
58.7%
Common 12959
40.4%
Latin 306
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1671
 
8.9%
1625
 
8.6%
1582
 
8.4%
1278
 
6.8%
1270
 
6.7%
1251
 
6.6%
1244
 
6.6%
735
 
3.9%
696
 
3.7%
374
 
2.0%
Other values (320) 7098
37.7%
Latin
ValueCountFrequency (%)
S 34
 
11.1%
e 33
 
10.8%
o 21
 
6.9%
T 20
 
6.5%
C 14
 
4.6%
K 13
 
4.2%
l 12
 
3.9%
A 11
 
3.6%
i 11
 
3.6%
B 11
 
3.6%
Other values (27) 126
41.2%
Common
ValueCountFrequency (%)
4932
38.1%
1 1613
 
12.4%
- 1091
 
8.4%
2 958
 
7.4%
3 754
 
5.8%
4 681
 
5.3%
0 645
 
5.0%
5 509
 
3.9%
7 480
 
3.7%
8 469
 
3.6%
Other values (7) 827
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18824
58.7%
ASCII 13265
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4932
37.2%
1 1613
 
12.2%
- 1091
 
8.2%
2 958
 
7.2%
3 754
 
5.7%
4 681
 
5.1%
0 645
 
4.9%
5 509
 
3.8%
7 480
 
3.6%
8 469
 
3.5%
Other values (44) 1133
 
8.5%
Hangul
ValueCountFrequency (%)
1671
 
8.9%
1625
 
8.6%
1582
 
8.4%
1278
 
6.8%
1270
 
6.7%
1251
 
6.6%
1244
 
6.6%
735
 
3.9%
696
 
3.7%
374
 
2.0%
Other values (320) 7098
37.7%

도로명전체주소
Text

MISSING 

Distinct1142
Distinct (%)96.6%
Missing56
Missing (%)4.5%
Memory size9.8 KiB
2024-04-16T15:50:08.566251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length48
Mean length33.465313
Min length21

Characters and Unicode

Total characters39556
Distinct characters419
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

Unique1109 ?
Unique (%)93.8%

Sample

1st row부산광역시 중구 중앙대로81번길 2 (중앙동4가)
2nd row부산광역시 중구 자갈치해안로 60 (남포동4가)
3rd row부산광역시 중구 충장대로 24, 부산항연안여객터미널 1층 (중앙동4가)
4th row부산광역시 중구 중구로 2 (남포동5가)
5th row부산광역시 중구 구덕로 87-1 (남포동6가)
ValueCountFrequency (%)
부산광역시 1180
 
15.9%
부산진구 249
 
3.3%
중앙대로 172
 
2.3%
중구 141
 
1.9%
해운대구 136
 
1.8%
2층 124
 
1.7%
동구 117
 
1.6%
동래구 98
 
1.3%
연제구 97
 
1.3%
부전동 68
 
0.9%
Other values (1837) 5061
68.0%
2024-04-16T15:50:08.987093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6533
 
16.5%
1639
 
4.1%
1626
 
4.1%
1566
 
4.0%
1 1411
 
3.6%
1272
 
3.2%
1241
 
3.1%
, 1229
 
3.1%
1212
 
3.1%
1188
 
3.0%
Other values (409) 20639
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22734
57.5%
Space Separator 6533
 
16.5%
Decimal Number 6207
 
15.7%
Other Punctuation 1235
 
3.1%
Open Punctuation 1179
 
3.0%
Close Punctuation 1179
 
3.0%
Dash Punctuation 174
 
0.4%
Uppercase Letter 158
 
0.4%
Lowercase Letter 155
 
0.4%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1639
 
7.2%
1626
 
7.2%
1566
 
6.9%
1272
 
5.6%
1241
 
5.5%
1212
 
5.3%
1188
 
5.2%
1186
 
5.2%
803
 
3.5%
547
 
2.4%
Other values (355) 10454
46.0%
Uppercase Letter
ValueCountFrequency (%)
S 34
21.5%
T 18
11.4%
C 16
10.1%
K 14
8.9%
A 13
 
8.2%
B 13
 
8.2%
E 8
 
5.1%
I 6
 
3.8%
H 6
 
3.8%
O 5
 
3.2%
Other values (10) 25
15.8%
Lowercase Letter
ValueCountFrequency (%)
e 34
21.9%
o 21
13.5%
l 12
 
7.7%
p 11
 
7.1%
i 11
 
7.1%
m 10
 
6.5%
n 10
 
6.5%
x 10
 
6.5%
d 10
 
6.5%
a 10
 
6.5%
Other values (7) 16
10.3%
Decimal Number
ValueCountFrequency (%)
1 1411
22.7%
2 976
15.7%
3 767
12.4%
0 684
11.0%
4 513
 
8.3%
5 456
 
7.3%
6 406
 
6.5%
7 359
 
5.8%
8 328
 
5.3%
9 307
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 1229
99.5%
/ 6
 
0.5%
Space Separator
ValueCountFrequency (%)
6533
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1179
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1179
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 174
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22734
57.5%
Common 16509
41.7%
Latin 313
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1639
 
7.2%
1626
 
7.2%
1566
 
6.9%
1272
 
5.6%
1241
 
5.5%
1212
 
5.3%
1188
 
5.2%
1186
 
5.2%
803
 
3.5%
547
 
2.4%
Other values (355) 10454
46.0%
Latin
ValueCountFrequency (%)
S 34
 
10.9%
e 34
 
10.9%
o 21
 
6.7%
T 18
 
5.8%
C 16
 
5.1%
K 14
 
4.5%
A 13
 
4.2%
B 13
 
4.2%
l 12
 
3.8%
p 11
 
3.5%
Other values (27) 127
40.6%
Common
ValueCountFrequency (%)
6533
39.6%
1 1411
 
8.5%
, 1229
 
7.4%
( 1179
 
7.1%
) 1179
 
7.1%
2 976
 
5.9%
3 767
 
4.6%
0 684
 
4.1%
4 513
 
3.1%
5 456
 
2.8%
Other values (7) 1582
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22734
57.5%
ASCII 16822
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6533
38.8%
1 1411
 
8.4%
, 1229
 
7.3%
( 1179
 
7.0%
) 1179
 
7.0%
2 976
 
5.8%
3 767
 
4.6%
0 684
 
4.1%
4 513
 
3.0%
5 456
 
2.7%
Other values (44) 1895
 
11.3%
Hangul
ValueCountFrequency (%)
1639
 
7.2%
1626
 
7.2%
1566
 
6.9%
1272
 
5.6%
1241
 
5.5%
1212
 
5.3%
1188
 
5.2%
1186
 
5.2%
803
 
3.5%
547
 
2.4%
Other values (355) 10454
46.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct471
Distinct (%)56.2%
Missing400
Missing (%)32.3%
Infinite0
Infinite (%)0.0%
Mean103014.86
Minimum46015
Maximum618142
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:09.099102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46015
5-th percentile46297.1
Q147257
median48087
Q348821
95-th percentile612052.5
Maximum618142
Range572127
Interquartile range (IQR)1564

Descriptive statistics

Standard deviation167502.6
Coefficient of variation (CV)1.6260043
Kurtosis5.3698831
Mean103014.86
Median Absolute Deviation (MAD)829
Skewness2.712173
Sum86326450
Variance2.8057122 × 1010
MonotonicityNot monotonic
2024-04-16T15:50:09.201606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47216 19
 
1.5%
48924 10
 
0.8%
49037 10
 
0.8%
47246 10
 
0.8%
47257 9
 
0.7%
48059 9
 
0.7%
48092 9
 
0.7%
48741 8
 
0.6%
48095 8
 
0.6%
48733 8
 
0.6%
Other values (461) 738
59.6%
(Missing) 400
32.3%
ValueCountFrequency (%)
46015 3
0.2%
46022 1
 
0.1%
46024 2
0.2%
46056 1
 
0.1%
46063 1
 
0.1%
46070 1
 
0.1%
46072 1
 
0.1%
46073 1
 
0.1%
46080 1
 
0.1%
46213 1
 
0.1%
ValueCountFrequency (%)
618142 1
0.1%
617825 1
0.1%
617816 1
0.1%
617814 1
0.1%
617809 2
0.2%
617807 1
0.1%
617802 1
0.1%
617723 1
0.1%
616852 1
0.1%
616829 1
0.1%
Distinct1192
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
2024-04-16T15:50:09.411679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length8.1268174
Min length2

Characters and Unicode

Total characters10061
Distinct characters482
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1150 ?
Unique (%)92.9%

Sample

1st row(주)팔성국제관광
2nd row부산남항유람선 자갈치크루즈
3rd row(주)마린크루즈
4th row(주)초이스관광여행사
5th row(주)미래투어
ValueCountFrequency (%)
주식회사 88
 
5.9%
여행사 29
 
2.0%
투어 16
 
1.1%
15
 
1.0%
tour 6
 
0.4%
여행 6
 
0.4%
부산투어 5
 
0.3%
협동조합 5
 
0.3%
부산 3
 
0.2%
주)환태평양고속관광 3
 
0.2%
Other values (1247) 1306
88.1%
2024-04-16T15:50:09.758412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
863
 
8.6%
( 766
 
7.6%
) 766
 
7.6%
507
 
5.0%
505
 
5.0%
500
 
5.0%
408
 
4.1%
401
 
4.0%
244
 
2.4%
179
 
1.8%
Other values (472) 4922
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8095
80.5%
Open Punctuation 766
 
7.6%
Close Punctuation 766
 
7.6%
Space Separator 244
 
2.4%
Uppercase Letter 115
 
1.1%
Lowercase Letter 34
 
0.3%
Other Punctuation 18
 
0.2%
Decimal Number 15
 
0.1%
Dash Punctuation 5
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
863
 
10.7%
507
 
6.3%
505
 
6.2%
500
 
6.2%
408
 
5.0%
401
 
5.0%
179
 
2.2%
175
 
2.2%
170
 
2.1%
168
 
2.1%
Other values (419) 4219
52.1%
Uppercase Letter
ValueCountFrequency (%)
T 23
20.0%
O 13
11.3%
B 7
 
6.1%
R 6
 
5.2%
U 6
 
5.2%
L 6
 
5.2%
H 6
 
5.2%
W 6
 
5.2%
G 5
 
4.3%
E 5
 
4.3%
Other values (11) 32
27.8%
Lowercase Letter
ValueCountFrequency (%)
r 6
17.6%
o 5
14.7%
t 3
8.8%
u 3
8.8%
i 2
 
5.9%
s 2
 
5.9%
e 2
 
5.9%
a 2
 
5.9%
b 1
 
2.9%
v 1
 
2.9%
Other values (7) 7
20.6%
Other Punctuation
ValueCountFrequency (%)
. 10
55.6%
& 5
27.8%
, 2
 
11.1%
: 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 7
46.7%
2 5
33.3%
8 2
 
13.3%
0 1
 
6.7%
Math Symbol
ValueCountFrequency (%)
1
50.0%
> 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 766
100.0%
Close Punctuation
ValueCountFrequency (%)
) 766
100.0%
Space Separator
ValueCountFrequency (%)
244
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8096
80.5%
Common 1816
 
18.0%
Latin 149
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
863
 
10.7%
507
 
6.3%
505
 
6.2%
500
 
6.2%
408
 
5.0%
401
 
5.0%
179
 
2.2%
175
 
2.2%
170
 
2.1%
168
 
2.1%
Other values (420) 4220
52.1%
Latin
ValueCountFrequency (%)
T 23
 
15.4%
O 13
 
8.7%
B 7
 
4.7%
R 6
 
4.0%
U 6
 
4.0%
L 6
 
4.0%
H 6
 
4.0%
W 6
 
4.0%
r 6
 
4.0%
G 5
 
3.4%
Other values (28) 65
43.6%
Common
ValueCountFrequency (%)
( 766
42.2%
) 766
42.2%
244
 
13.4%
. 10
 
0.6%
1 7
 
0.4%
2 5
 
0.3%
- 5
 
0.3%
& 5
 
0.3%
, 2
 
0.1%
8 2
 
0.1%
Other values (4) 4
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8095
80.5%
ASCII 1964
 
19.5%
Arrows 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
863
 
10.7%
507
 
6.3%
505
 
6.2%
500
 
6.2%
408
 
5.0%
401
 
5.0%
179
 
2.2%
175
 
2.2%
170
 
2.1%
168
 
2.1%
Other values (419) 4219
52.1%
ASCII
ValueCountFrequency (%)
( 766
39.0%
) 766
39.0%
244
 
12.4%
T 23
 
1.2%
O 13
 
0.7%
. 10
 
0.5%
1 7
 
0.4%
B 7
 
0.4%
R 6
 
0.3%
U 6
 
0.3%
Other values (41) 116
 
5.9%
Arrows
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct1208
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0160387 × 1013
Minimum2.0021018 × 1013
Maximum2.0210728 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:09.874371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0021018 × 1013
5-th percentile2.0040614 × 1013
Q12.012065 × 1013
median2.0190713 × 1013
Q32.0210126 × 1013
95-th percentile2.0210611 × 1013
Maximum2.0210728 × 1013
Range1.8971001 × 1011
Interquartile range (IQR)8.9475793 × 1010

Descriptive statistics

Standard deviation5.7830992 × 1010
Coefficient of variation (CV)0.0028685458
Kurtosis-0.44908788
Mean2.0160387 × 1013
Median Absolute Deviation (MAD)1.9811008 × 1010
Skewness-0.96707589
Sum2.4958559 × 1016
Variance3.3444236 × 1021
MonotonicityNot monotonic
2024-04-16T15:50:09.989603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030127161421 17
 
1.4%
20030127161348 15
 
1.2%
20210311140247 1
 
0.1%
20210310173305 1
 
0.1%
20210224174814 1
 
0.1%
20210324093655 1
 
0.1%
20201209105913 1
 
0.1%
20210224125616 1
 
0.1%
20210218170340 1
 
0.1%
20210224125818 1
 
0.1%
Other values (1198) 1198
96.8%
ValueCountFrequency (%)
20021018131515 1
 
0.1%
20021217165012 1
 
0.1%
20030127161348 15
1.2%
20030127161421 17
1.4%
20030203150601 1
 
0.1%
20030312172512 1
 
0.1%
20030410112657 1
 
0.1%
20030422140401 1
 
0.1%
20030423092346 1
 
0.1%
20030516111251 1
 
0.1%
ValueCountFrequency (%)
20210728141519 1
0.1%
20210727173633 1
0.1%
20210727135226 1
0.1%
20210726150537 1
0.1%
20210726142243 1
0.1%
20210726121206 1
0.1%
20210726121138 1
0.1%
20210726121044 1
0.1%
20210723085623 1
0.1%
20210722105549 1
0.1%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
U
638 
I
600 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowU
2nd rowU
3rd rowU
4th rowI
5th rowU

Common Values

ValueCountFrequency (%)
U 638
51.5%
I 600
48.5%

Length

2024-04-16T15:50:10.091416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:10.161731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 638
51.5%
i 600
48.5%
Distinct345
Distinct (%)27.9%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
Minimum2018-08-31 23:59:59
Maximum2021-07-30 02:40:00
2024-04-16T15:50:10.282365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T15:50:10.683640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1238
Missing (%)100.0%
Memory size11.0 KiB

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct880
Distinct (%)73.3%
Missing37
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean388409.06
Minimum345960.71
Maximum419502.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:10.807503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum345960.71
5-th percentile380482.77
Q1385754.48
median388076
Q3390403.02
95-th percentile396962.54
Maximum419502.8
Range73542.098
Interquartile range (IQR)4648.5382

Descriptive statistics

Standard deviation4699.3416
Coefficient of variation (CV)0.01209895
Kurtosis7.6468201
Mean388409.06
Median Absolute Deviation (MAD)2321.5215
Skewness-0.2611811
Sum4.6647928 × 108
Variance22083812
MonotonicityNot monotonic
2024-04-16T15:50:10.920112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
391411.212179843 16
 
1.3%
387225.613588405 13
 
1.1%
385507.640529964 11
 
0.9%
385754.477258744 10
 
0.8%
386093.674147239 10
 
0.8%
388922.806889486 8
 
0.6%
396180.621244719 7
 
0.6%
385502.492319657 7
 
0.6%
396962.538162221 6
 
0.5%
387052.317362645 6
 
0.5%
Other values (870) 1107
89.4%
(Missing) 37
 
3.0%
ValueCountFrequency (%)
345960.705739 1
0.1%
371478.346756395 1
0.1%
373016.981172454 1
0.1%
373099.680011291 1
0.1%
373506.567424228 1
0.1%
374028.336209222 1
0.1%
374032.128682044 1
0.1%
374333.199064 1
0.1%
374846.363500608 2
0.2%
374874.044714515 1
0.1%
ValueCountFrequency (%)
419502.803661768 1
0.1%
407681.822826568 1
0.1%
402013.567273627 1
0.1%
401991.877826951 1
0.1%
401723.13090266 1
0.1%
401654.448837686 1
0.1%
401510.613962736 1
0.1%
401502.415893064 1
0.1%
401448.811664877 1
0.1%
400815.753437419 1
0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct880
Distinct (%)73.3%
Missing37
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean186472.41
Minimum174307.15
Maximum265785.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:11.031521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174307.15
5-th percentile179658.84
Q1182474.91
median186442.19
Q3189180.05
95-th percentile194714.02
Maximum265785.6
Range91478.456
Interquartile range (IQR)6705.1471

Descriptive statistics

Standard deviation5328.1005
Coefficient of variation (CV)0.028573131
Kurtosis42.877054
Mean186472.41
Median Absolute Deviation (MAD)3159.7726
Skewness3.3594201
Sum2.2395336 × 108
Variance28388655
MonotonicityNot monotonic
2024-04-16T15:50:11.165522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
184052.409245407 16
 
1.3%
186408.726533861 13
 
1.1%
180548.792611588 11
 
0.9%
179113.980448494 10
 
0.8%
182068.358104572 10
 
0.8%
188106.837170815 8
 
0.6%
186522.35047527 7
 
0.6%
180297.579330876 7
 
0.6%
186759.94170898 6
 
0.5%
186253.143814124 6
 
0.5%
Other values (870) 1107
89.4%
(Missing) 37
 
3.0%
ValueCountFrequency (%)
174307.148168245 1
0.1%
174856.056137804 1
0.1%
175087.296427656 2
0.2%
176115.246760367 1
0.1%
176897.907425952 1
0.1%
177354.376036871 1
0.1%
177441.748341131 1
0.1%
177442.817428718 1
0.1%
177527.376138393 1
0.1%
177532.283470077 2
0.2%
ValueCountFrequency (%)
265785.603884 1
0.1%
226490.138380339 1
0.1%
205732.231316224 1
0.1%
204739.778227028 1
0.1%
204665.784677421 1
0.1%
204621.655738547 1
0.1%
204592.491613115 1
0.1%
204214.040987968 1
0.1%
204186.113952008 1
0.1%
199051.512822937 1
0.1%

문화체육업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
국내여행업
1238 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내여행업 1238
100.0%

Length

2024-04-16T15:50:11.290359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:11.382854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내여행업 1238
100.0%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
705 
관광사업
533 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 705
56.9%
관광사업 533
43.1%

Length

2024-04-16T15:50:11.480592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:11.577450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 705
56.9%
관광사업 533
43.1%

지역구분명
Categorical

IMBALANCE 

Distinct14
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
1012 
일반주거지역
 
62
일반상업지역
 
41
상업지역
 
34
근린상업지역
 
31
Other values (9)
 
58

Length

Max length6
Median length4
Mean length4.2560582
Min length4

Unique

Unique5 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1012
81.7%
일반주거지역 62
 
5.0%
일반상업지역 41
 
3.3%
상업지역 34
 
2.7%
근린상업지역 31
 
2.5%
준주거지역 28
 
2.3%
주거지역 14
 
1.1%
준공업지역 7
 
0.6%
자연녹지지역 4
 
0.3%
녹지지역 1
 
0.1%
Other values (4) 4
 
0.3%

Length

2024-04-16T15:50:11.673328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1012
81.7%
일반주거지역 62
 
5.0%
일반상업지역 41
 
3.3%
상업지역 34
 
2.7%
근린상업지역 31
 
2.5%
준주거지역 28
 
2.3%
주거지역 14
 
1.1%
준공업지역 7
 
0.6%
자연녹지지역 4
 
0.3%
녹지지역 1
 
0.1%
Other values (4) 4
 
0.3%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct25
Distinct (%)10.4%
Missing998
Missing (%)80.6%
Infinite0
Infinite (%)0.0%
Mean5.0166667
Minimum0
Maximum54
Zeros43
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:11.768945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q36
95-th percentile14.05
Maximum54
Range54
Interquartile range (IQR)4

Descriptive statistics

Standard deviation7.1111714
Coefficient of variation (CV)1.4175092
Kurtosis19.34384
Mean5.0166667
Median Absolute Deviation (MAD)2
Skewness3.9257056
Sum1204
Variance50.568759
MonotonicityNot monotonic
2024-04-16T15:50:11.860334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 43
 
3.5%
2 36
 
2.9%
4 34
 
2.7%
3 29
 
2.3%
5 21
 
1.7%
6 15
 
1.2%
1 14
 
1.1%
7 10
 
0.8%
8 7
 
0.6%
10 7
 
0.6%
Other values (15) 24
 
1.9%
(Missing) 998
80.6%
ValueCountFrequency (%)
0 43
3.5%
1 14
 
1.1%
2 36
2.9%
3 29
2.3%
4 34
2.7%
5 21
1.7%
6 15
 
1.2%
7 10
 
0.8%
8 7
 
0.6%
9 3
 
0.2%
ValueCountFrequency (%)
54 1
 
0.1%
50 1
 
0.1%
37 1
 
0.1%
33 1
 
0.1%
31 3
0.2%
27 1
 
0.1%
21 1
 
0.1%
20 1
 
0.1%
19 1
 
0.1%
15 1
 
0.1%

주변환경명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
1080 
기타
 
85
학교정화(상대)
 
22
주택가주변
 
21
아파트지역
 
19
Other values (3)
 
11

Length

Max length8
Median length4
Mean length3.9983845
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1080
87.2%
기타 85
 
6.9%
학교정화(상대) 22
 
1.8%
주택가주변 21
 
1.7%
아파트지역 19
 
1.5%
유흥업소밀집지역 5
 
0.4%
결혼예식장주변 4
 
0.3%
학교정화(절대) 2
 
0.2%

Length

2024-04-16T15:50:11.958215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:12.050106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1080
87.2%
기타 85
 
6.9%
학교정화(상대 22
 
1.8%
주택가주변 21
 
1.7%
아파트지역 19
 
1.5%
유흥업소밀집지역 5
 
0.4%
결혼예식장주변 4
 
0.3%
학교정화(절대 2
 
0.2%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1238
Missing (%)100.0%
Memory size11.0 KiB

보험기관명
Categorical

Distinct30
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
451 
서울보증보험주식회사
262 
서울보증보험
224 
한국관광협회중앙회 여행공제회
83 
한국관광협회중앙회
63 
Other values (25)
155 

Length

Max length19
Median length16
Mean length7.1688207
Min length4

Unique

Unique14 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 451
36.4%
서울보증보험주식회사 262
21.2%
서울보증보험 224
18.1%
한국관광협회중앙회 여행공제회 83
 
6.7%
한국관광협회중앙회 63
 
5.1%
한국관광협회 58
 
4.7%
서울보증보험(주) 20
 
1.6%
부산광역시관광협회 15
 
1.2%
한국관광협회중앙회여행공제회 12
 
1.0%
한국관광협회중앙회 관광공제회 8
 
0.6%
Other values (20) 42
 
3.4%

Length

2024-04-16T15:50:12.176219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 451
33.6%
서울보증보험주식회사 262
19.5%
서울보증보험 224
16.7%
한국관광협회중앙회 156
 
11.6%
여행공제회 84
 
6.3%
한국관광협회 59
 
4.4%
서울보증보험(주 20
 
1.5%
관광공제회 16
 
1.2%
부산광역시관광협회 15
 
1.1%
한국관광협회중앙회여행공제회 12
 
0.9%
Other values (19) 42
 
3.1%

건물용도명
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
995 
근린생활시설
169 
사무실
 
54
교육연구시설
 
6
기타
 
5
Other values (6)
 
9

Length

Max length15
Median length4
Mean length4.2390953
Min length2

Unique

Unique4 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 995
80.4%
근린생활시설 169
 
13.7%
사무실 54
 
4.4%
교육연구시설 6
 
0.5%
기타 5
 
0.4%
아파트 3
 
0.2%
유통시설 2
 
0.2%
복지시설 1
 
0.1%
다세대주택 1
 
0.1%
다가구용 주택(공동주택적용) 1
 
0.1%

Length

2024-04-16T15:50:12.304567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 995
80.3%
근린생활시설 169
 
13.6%
사무실 54
 
4.4%
교육연구시설 6
 
0.5%
기타 5
 
0.4%
아파트 3
 
0.2%
유통시설 2
 
0.2%
복지시설 1
 
0.1%
다세대주택 1
 
0.1%
다가구용 1
 
0.1%
Other values (2) 2
 
0.2%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)10.0%
Missing978
Missing (%)79.0%
Infinite0
Infinite (%)0.0%
Mean4.6307692
Minimum0
Maximum49
Zeros39
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:12.410338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q35
95-th percentile16
Maximum49
Range49
Interquartile range (IQR)3

Descriptive statistics

Standard deviation6.3192278
Coefficient of variation (CV)1.3646173
Kurtosis17.082041
Mean4.6307692
Median Absolute Deviation (MAD)2
Skewness3.6369183
Sum1204
Variance39.93264
MonotonicityNot monotonic
2024-04-16T15:50:12.503762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2 60
 
4.8%
0 39
 
3.2%
3 39
 
3.2%
4 26
 
2.1%
5 23
 
1.9%
1 17
 
1.4%
6 10
 
0.8%
7 8
 
0.6%
9 8
 
0.6%
10 5
 
0.4%
Other values (16) 25
 
2.0%
(Missing) 978
79.0%
ValueCountFrequency (%)
0 39
3.2%
1 17
 
1.4%
2 60
4.8%
3 39
3.2%
4 26
2.1%
5 23
 
1.9%
6 10
 
0.8%
7 8
 
0.6%
8 4
 
0.3%
9 8
 
0.6%
ValueCountFrequency (%)
49 1
 
0.1%
43 1
 
0.1%
32 1
 
0.1%
29 1
 
0.1%
26 3
0.2%
24 1
 
0.1%
23 1
 
0.1%
22 1
 
0.1%
20 1
 
0.1%
17 1
 
0.1%

지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)5.3%
Missing1087
Missing (%)87.8%
Infinite0
Infinite (%)0.0%
Mean1.0463576
Minimum0
Maximum7
Zeros55
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:12.595600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile4.5
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3132035
Coefficient of variation (CV)1.2550236
Kurtosis5.3659928
Mean1.0463576
Median Absolute Deviation (MAD)1
Skewness2.1868218
Sum158
Variance1.7245033
MonotonicityNot monotonic
2024-04-16T15:50:12.681302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 69
 
5.6%
0 55
 
4.4%
2 13
 
1.1%
5 6
 
0.5%
3 4
 
0.3%
4 2
 
0.2%
7 1
 
0.1%
6 1
 
0.1%
(Missing) 1087
87.8%
ValueCountFrequency (%)
0 55
4.4%
1 69
5.6%
2 13
 
1.1%
3 4
 
0.3%
4 2
 
0.2%
5 6
 
0.5%
6 1
 
0.1%
7 1
 
0.1%
ValueCountFrequency (%)
7 1
 
0.1%
6 1
 
0.1%
5 6
 
0.5%
4 2
 
0.2%
3 4
 
0.3%
2 13
 
1.1%
1 69
5.6%
0 55
4.4%

객실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
1206 
0
 
32

Length

Max length4
Median length4
Mean length3.9224556
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1206
97.4%
0 32
 
2.6%

Length

2024-04-16T15:50:12.783285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:12.860724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1206
97.4%
0 32
 
2.6%

건축연면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
1206 
0
 
32

Length

Max length4
Median length4
Mean length3.9224556
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1206
97.4%
0 32
 
2.6%

Length

2024-04-16T15:50:12.939237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:13.034590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1206
97.4%
0 32
 
2.6%

영문상호명
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing1209
Missing (%)97.7%
Memory size9.8 KiB
2024-04-16T15:50:13.207764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length25
Mean length20.172414
Min length7

Characters and Unicode

Total characters585
Distinct characters52
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st rowLeaders Tour
2nd rowSEOKWANG Travel
3rd rowEMTCO Limited
4th rowNadri Tour Co.,Ltd.
5th rowS&G.CO.,Ltd
ValueCountFrequency (%)
tour 13
 
13.0%
travel 9
 
9.0%
ltd 7
 
7.0%
co 7
 
7.0%
co.,ltd 5
 
5.0%
inc 4
 
4.0%
service 3
 
3.0%
agency 3
 
3.0%
air 2
 
2.0%
express 2
 
2.0%
Other values (43) 45
45.0%
2024-04-16T15:50:13.484380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
71
 
12.1%
T 35
 
6.0%
O 29
 
5.0%
R 29
 
5.0%
L 28
 
4.8%
E 28
 
4.8%
. 23
 
3.9%
A 23
 
3.9%
C 22
 
3.8%
S 19
 
3.2%
Other values (42) 278
47.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 327
55.9%
Lowercase Letter 149
25.5%
Space Separator 71
 
12.1%
Other Punctuation 36
 
6.2%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 35
10.7%
O 29
 
8.9%
R 29
 
8.9%
L 28
 
8.6%
E 28
 
8.6%
A 23
 
7.0%
C 22
 
6.7%
S 19
 
5.8%
U 19
 
5.8%
I 15
 
4.6%
Other values (14) 80
24.5%
Lowercase Letter
ValueCountFrequency (%)
a 18
12.1%
n 16
10.7%
o 15
10.1%
e 15
10.1%
r 14
9.4%
t 11
 
7.4%
d 10
 
6.7%
c 9
 
6.0%
u 7
 
4.7%
l 6
 
4.0%
Other values (12) 28
18.8%
Other Punctuation
ValueCountFrequency (%)
. 23
63.9%
, 11
30.6%
& 2
 
5.6%
Space Separator
ValueCountFrequency (%)
71
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 476
81.4%
Common 109
 
18.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 35
 
7.4%
O 29
 
6.1%
R 29
 
6.1%
L 28
 
5.9%
E 28
 
5.9%
A 23
 
4.8%
C 22
 
4.6%
S 19
 
4.0%
U 19
 
4.0%
a 18
 
3.8%
Other values (36) 226
47.5%
Common
ValueCountFrequency (%)
71
65.1%
. 23
 
21.1%
, 11
 
10.1%
& 2
 
1.8%
( 1
 
0.9%
) 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 585
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
71
 
12.1%
T 35
 
6.0%
O 29
 
5.0%
R 29
 
5.0%
L 28
 
4.8%
E 28
 
4.8%
. 23
 
3.9%
A 23
 
3.9%
C 22
 
3.8%
S 19
 
3.2%
Other values (42) 278
47.5%

영문상호주소
Categorical

IMBALANCE 

Distinct13
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
1209 
Domestic travel business
 
6
DOMESTIC TRAVEL BUSINESS
 
4
Inland Travel Business
 
3
Domestic Traval Agency
 
3
Other values (8)
 
13

Length

Max length30
Median length4
Mean length4.453958
Min length4

Unique

Unique5 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1209
97.7%
Domestic travel business 6
 
0.5%
DOMESTIC TRAVEL BUSINESS 4
 
0.3%
Inland Travel Business 3
 
0.2%
Domestic Traval Agency 3
 
0.2%
Domestic Travel Agency 3
 
0.2%
DOMESTIC TRAVEL AGENCY 3
 
0.2%
WITHIN A COUNTRY TRAVEL AGENCY 2
 
0.2%
Domestic Travel Industry 1
 
0.1%
Domestic Travel Business 1
 
0.1%
Other values (3) 3
 
0.2%

Length

2024-04-16T15:50:13.588965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1209
93.1%
travel 26
 
2.0%
domestic 22
 
1.7%
business 15
 
1.2%
agency 12
 
0.9%
inland 3
 
0.2%
traval 3
 
0.2%
within 2
 
0.2%
a 2
 
0.2%
country 2
 
0.2%
Other values (3) 3
 
0.2%

선박총톤수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
1206 
0
 
32

Length

Max length4
Median length4
Mean length3.9224556
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1206
97.4%
0 32
 
2.6%

Length

2024-04-16T15:50:13.684071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:13.767426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1206
97.4%
0 32
 
2.6%

선박척수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
1206 
0
 
32

Length

Max length4
Median length4
Mean length3.9224556
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1206
97.4%
0 32
 
2.6%

Length

2024-04-16T15:50:13.852010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:13.930194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1206
97.4%
0 32
 
2.6%

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1238
Missing (%)100.0%
Memory size11.0 KiB

무대면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
1206 
0
 
32

Length

Max length4
Median length4
Mean length3.9224556
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1206
97.4%
0 32
 
2.6%

Length

2024-04-16T15:50:14.013535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:14.090801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1206
97.4%
0 32
 
2.6%

좌석수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
1206 
0
 
32

Length

Max length4
Median length4
Mean length3.9224556
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1206
97.4%
0 32
 
2.6%

Length

2024-04-16T15:50:14.172253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:14.249518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1206
97.4%
0 32
 
2.6%

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1238
Missing (%)100.0%
Memory size11.0 KiB

회의실별동시수용인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
1206 
0
 
32

Length

Max length4
Median length4
Mean length3.9224556
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1206
97.4%
0 32
 
2.6%

Length

2024-04-16T15:50:14.330240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:14.412827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1206
97.4%
0 32
 
2.6%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct223
Distinct (%)69.3%
Missing916
Missing (%)74.0%
Infinite0
Infinite (%)0.0%
Mean288.14441
Minimum0
Maximum43511
Zeros40
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:14.501230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q122.0125
median44.715
Q383.2275
95-th percentile201.857
Maximum43511
Range43511
Interquartile range (IQR)61.215

Descriptive statistics

Standard deviation2649.0212
Coefficient of variation (CV)9.1933806
Kurtosis229.19834
Mean288.14441
Median Absolute Deviation (MAD)28.13
Skewness14.667514
Sum92782.5
Variance7017313.5
MonotonicityNot monotonic
2024-04-16T15:50:14.620746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 40
 
3.2%
33.0 12
 
1.0%
30.0 7
 
0.6%
50.0 6
 
0.5%
66.0 6
 
0.5%
20.0 5
 
0.4%
198.0 3
 
0.2%
15.0 3
 
0.2%
25.0 3
 
0.2%
12.0 3
 
0.2%
Other values (213) 234
 
18.9%
(Missing) 916
74.0%
ValueCountFrequency (%)
0.0 40
3.2%
2.58 1
 
0.1%
4.05 1
 
0.1%
6.0 1
 
0.1%
6.6 1
 
0.1%
6.71 1
 
0.1%
8.0 1
 
0.1%
8.4 1
 
0.1%
10.0 1
 
0.1%
12.0 3
 
0.2%
ValueCountFrequency (%)
43511.0 1
0.1%
18592.0 1
0.1%
3920.67 1
0.1%
3480.76 1
0.1%
2988.0 1
0.1%
1022.9 1
0.1%
1013.0 1
0.1%
268.5 1
0.1%
258.15 1
0.1%
243.34 1
0.1%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1238
Missing (%)100.0%
Memory size11.0 KiB

놀이시설수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
1206 
0
 
32

Length

Max length4
Median length4
Mean length3.9224556
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1206
97.4%
0 32
 
2.6%

Length

2024-04-16T15:50:14.724918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:14.804602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1206
97.4%
0 32
 
2.6%

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1238
Missing (%)100.0%
Memory size11.0 KiB

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1238
Missing (%)100.0%
Memory size11.0 KiB

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1238
Missing (%)100.0%
Memory size11.0 KiB

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1238
Missing (%)100.0%
Memory size11.0 KiB

기획여행보험시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
1237 
20200205
 
1

Length

Max length8
Median length4
Mean length4.003231
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1237
99.9%
20200205 1
 
0.1%

Length

2024-04-16T15:50:14.889867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:14.973831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1237
99.9%
20200205 1
 
0.1%

기획여행보험종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
1237 
20210204
 
1

Length

Max length8
Median length4
Mean length4.003231
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1237
99.9%
20210204 1
 
0.1%

Length

2024-04-16T15:50:15.058927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:50:15.140638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1237
99.9%
20210204 1
 
0.1%

자본금
Real number (ℝ)

MISSING 

Distinct140
Distinct (%)17.2%
Missing426
Missing (%)34.4%
Infinite0
Infinite (%)0.0%
Mean86703118
Minimum0
Maximum6.5122084 × 109
Zeros7
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:15.231777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15000000
Q130000000
median50000000
Q31 × 108
95-th percentile1.5 × 108
Maximum6.5122084 × 109
Range6.5122084 × 109
Interquartile range (IQR)70000000

Descriptive statistics

Standard deviation2.6751984 × 108
Coefficient of variation (CV)3.0854697
Kurtosis443.69358
Mean86703118
Median Absolute Deviation (MAD)20000000
Skewness19.820109
Sum7.0402932 × 1010
Variance7.1566867 × 1016
MonotonicityNot monotonic
2024-04-16T15:50:15.342839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000000 192
15.5%
30000000 108
 
8.7%
150000000 103
 
8.3%
100000000 72
 
5.8%
15000000 56
 
4.5%
90000000 53
 
4.3%
45000000 21
 
1.7%
60000000 16
 
1.3%
20000000 16
 
1.3%
0 7
 
0.6%
Other values (130) 168
 
13.6%
(Missing) 426
34.4%
ValueCountFrequency (%)
0 7
 
0.6%
5000 1
 
0.1%
5300 1
 
0.1%
30000 1
 
0.1%
1500000 1
 
0.1%
1750000 1
 
0.1%
3000000 4
 
0.3%
5000000 1
 
0.1%
10000000 2
 
0.2%
15000000 56
4.5%
ValueCountFrequency (%)
6512208375 1
 
0.1%
3500000000 1
 
0.1%
1000000000 1
 
0.1%
950000000 1
 
0.1%
505000000 1
 
0.1%
500000000 5
0.4%
490000000 1
 
0.1%
375256000 1
 
0.1%
300000000 3
0.2%
281323639 1
 
0.1%

보험시작일자
Real number (ℝ)

MISSING 

Distinct638
Distinct (%)78.0%
Missing420
Missing (%)33.9%
Infinite0
Infinite (%)0.0%
Mean20184747
Minimum20021021
Maximum20210901
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:15.457023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20021021
5-th percentile20110816
Q120171111
median20200366
Q320201124
95-th percentile20210518
Maximum20210901
Range189880
Interquartile range (IQR)30013.25

Descriptive statistics

Standard deviation31500.09
Coefficient of variation (CV)0.0015605888
Kurtosis4.2215369
Mean20184747
Median Absolute Deviation (MAD)9861
Skewness-1.9597298
Sum1.6511123 × 1010
Variance9.9225565 × 108
MonotonicityNot monotonic
2024-04-16T15:50:15.838409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210401 8
 
0.6%
20210201 6
 
0.5%
20200718 5
 
0.4%
20200826 5
 
0.4%
20200625 5
 
0.4%
20200701 5
 
0.4%
20210101 5
 
0.4%
20201201 4
 
0.3%
20190705 4
 
0.3%
20200810 4
 
0.3%
Other values (628) 767
62.0%
(Missing) 420
33.9%
ValueCountFrequency (%)
20021021 1
0.1%
20030812 1
0.1%
20030925 1
0.1%
20040420 1
0.1%
20051201 1
0.1%
20070111 1
0.1%
20070601 1
0.1%
20070802 1
0.1%
20071116 1
0.1%
20080303 1
0.1%
ValueCountFrequency (%)
20210901 1
0.1%
20210828 1
0.1%
20210731 1
0.1%
20210725 1
0.1%
20210721 1
0.1%
20210715 1
0.1%
20210709 1
0.1%
20210707 1
0.1%
20210706 1
0.1%
20210705 2
0.2%

보험종료일자
Real number (ℝ)

MISSING 

Distinct633
Distinct (%)77.3%
Missing419
Missing (%)33.8%
Infinite0
Infinite (%)0.0%
Mean20197347
Minimum20031021
Maximum21210810
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:15.962251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20031021
5-th percentile20121006
Q120181210
median20210408
Q320211166
95-th percentile20220525
Maximum21210810
Range1179789
Interquartile range (IQR)29955.5

Descriptive statistics

Standard deviation59173.274
Coefficient of variation (CV)0.0029297548
Kurtosis209.5009
Mean20197347
Median Absolute Deviation (MAD)9897
Skewness11.986118
Sum1.6541627 × 1010
Variance3.5014764 × 109
MonotonicityNot monotonic
2024-04-16T15:50:16.075998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20220331 7
 
0.6%
20211231 6
 
0.5%
20220131 5
 
0.4%
20210630 5
 
0.4%
20210825 5
 
0.4%
20220325 4
 
0.3%
20220322 4
 
0.3%
20200704 4
 
0.3%
20211130 4
 
0.3%
20210722 4
 
0.3%
Other values (623) 771
62.3%
(Missing) 419
33.8%
ValueCountFrequency (%)
20031021 1
0.1%
20040812 1
0.1%
20040925 1
0.1%
20050420 1
0.1%
20061201 1
0.1%
20080111 1
0.1%
20080601 1
0.1%
20080802 1
0.1%
20081115 1
0.1%
20090704 1
0.1%
ValueCountFrequency (%)
21210810 1
0.1%
21210714 1
0.1%
20240301 1
0.1%
20221110 1
0.1%
20221027 1
0.1%
20220831 1
0.1%
20220828 1
0.1%
20220806 1
0.1%
20220730 1
0.1%
20220724 1
0.1%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1238
Missing (%)100.0%
Memory size11.0 KiB

시설규모
Real number (ℝ)

MISSING  ZEROS 

Distinct130
Distinct (%)40.4%
Missing916
Missing (%)74.0%
Infinite0
Infinite (%)0.0%
Mean288.1646
Minimum0
Maximum43511
Zeros40
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-16T15:50:16.182673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q122
median44.5
Q383
95-th percentile201.8
Maximum43511
Range43511
Interquartile range (IQR)61

Descriptive statistics

Standard deviation2649.0219
Coefficient of variation (CV)9.192739
Kurtosis229.19765
Mean288.1646
Median Absolute Deviation (MAD)27.5
Skewness14.667483
Sum92789
Variance7017317.1
MonotonicityNot monotonic
2024-04-16T15:50:16.283561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 40
 
3.2%
33 16
 
1.3%
50 11
 
0.9%
30 9
 
0.7%
20 9
 
0.7%
66 8
 
0.6%
40 7
 
0.6%
15 6
 
0.5%
32 5
 
0.4%
26 5
 
0.4%
Other values (120) 206
 
16.6%
(Missing) 916
74.0%
ValueCountFrequency (%)
0 40
3.2%
3 1
 
0.1%
4 1
 
0.1%
6 1
 
0.1%
7 2
 
0.2%
8 2
 
0.2%
10 1
 
0.1%
12 3
 
0.2%
13 2
 
0.2%
15 6
 
0.5%
ValueCountFrequency (%)
43511 1
0.1%
18592 1
0.1%
3921 1
0.1%
3481 1
0.1%
2988 1
0.1%
1023 1
0.1%
1013 1
0.1%
269 1
0.1%
258 1
0.1%
243 1
0.1%

Unnamed: 63
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1238
Missing (%)100.0%
Memory size11.0 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모Unnamed: 63
01국내여행업03_12_01_P3250000CDFI226001200700001320071109<NA>2휴업2휴업<NA>2021010120211231<NA>469-7731<NA>600815부산광역시 중구 중앙동4가 53-30부산광역시 중구 중앙대로81번길 2 (중앙동4가)<NA>(주)팔성국제관광20210311140247U2021-03-13 02:40:00.0<NA>385556.341486180343.213568국내여행업관광사업<NA><NA><NA><NA>서울보증보험<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1500000002018110920191108<NA><NA><NA>
12국내여행업03_12_01_P3250000CDFI226001201900000220190110<NA>3폐업3폐업20200106<NA><NA><NA>051241 0909<NA><NA>부산광역시 중구 남포동4가 44-3번지부산광역시 중구 자갈치해안로 60 (남포동4가)48984부산남항유람선 자갈치크루즈20200106150326U2020-01-08 02:40:00.0<NA>385191.013393179401.283402국내여행업<NA><NA><NA><NA><NA>서울보증보험주식회사<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>162433582019011420200113<NA><NA><NA>
23국내여행업03_12_01_P3250000CDFI226001201900000620190829<NA>3폐업3폐업20190924<NA><NA><NA>051-464-6464<NA><NA>부산광역시 중구 중앙동4가 15-3번지부산광역시 중구 충장대로 24, 부산항연안여객터미널 1층 (중앙동4가)48940(주)마린크루즈20190924165841U2019-09-26 02:40:00.0<NA>386032.236799180263.270671국내여행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>15000000<NA><NA><NA><NA><NA>
34국내여행업03_12_01_P3250000CDFI226001199700000619970421<NA>3폐업3폐업20060704<NA><NA><NA>254-4061<NA>600045부산광역시 중구 남포동5가 39-6번지부산광역시 중구 중구로 2 (남포동5가)<NA>(주)초이스관광여행사20060704162946I2018-08-31 23:59:59.0<NA>384877.272224179536.794609국내여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45국내여행업03_12_01_P3250000CDFI226001199400000119940929<NA>3폐업3폐업20200317<NA><NA><NA>246-1003<NA>600046부산광역시 중구 남포동6가 113-1번지부산광역시 중구 구덕로 87-1 (남포동6가)<NA>(주)미래투어20200317173318U2020-03-19 02:40:00.0<NA>384708.848958179404.943227국내여행업관광사업<NA><NA><NA><NA>서울보증보험<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2018100820191017<NA><NA><NA>
56국내여행업03_12_01_P3250000CDFI226001199700000719970801<NA>3폐업3폐업20060517<NA><NA><NA>442-5020<NA>600815부산광역시 중구 중앙동4가 37-16번지 동아제일빌딩 903호부산광역시 중구 중앙대로81번길 9, 903호 (중앙동4가,동아제일빌딩)<NA>(주)세진여행사20060517165132I2018-08-31 23:59:59.0<NA>385473.57641180297.978229국내여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
67국내여행업03_12_01_P3250000CDFI226001199800000119980202<NA>3폐업3폐업20090129<NA><NA><NA>462-6661<NA>600814부산광역시 중구 중앙동4가 89-1번지부산광역시 중구 중앙대로 94 (중앙동4가)<NA>(주)아주좋은여행사20090129180902I2018-08-31 23:59:59.0<NA>385624.46871180447.914514국내여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
78국내여행업03_12_01_P3250000CDFI226001200000000820001024<NA>3폐업3폐업20200318<NA><NA><NA>247-1122<NA><NA>부산광역시 중구 부평동2가 68-4번지부산광역시 중구 흑교로 18 (부평동2가)48977(주)뉴태평양여행사20200318155253U2020-03-20 02:40:00.0<NA>384598.903965179879.997495국내여행업관광사업<NA><NA><NA><NA>한국관광협회<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2019062520200625<NA><NA><NA>
89국내여행업03_12_01_P3250000CDFI226001200700001120071018<NA>3폐업3폐업20071101<NA><NA><NA>463-5585<NA>600811부산광역시 중구 영주동 31-13번지부산광역시 중구 대영로 245 (영주동)<NA>해정여행사20071101133817I2018-08-31 23:59:59.0<NA>385692.204059181148.902569국내여행업관광사업<NA><NA><NA><NA><NA><NA>2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>50000000<NA><NA><NA><NA><NA>
910국내여행업03_12_01_P3250000CDFI226001200700001220071030<NA>3폐업3폐업20110422<NA><NA><NA>051-465-7111<NA>600013부산광역시 중구 중앙동3가 1번지 부산우체국보험회관 9층부산광역시 중구 중앙대로 63 (중앙동3가,부산우체국보험회관 9층)<NA>(주)조이로드20110425134240I2018-08-31 23:59:59.0<NA>385561.650139180152.738082국내여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2009102920101028<NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모Unnamed: 63
12281229국내여행업03_12_01_P3330000CDFI226001202100000419990513<NA>1영업/정상13영업중<NA><NA><NA><NA>051-808-6788<NA><NA>부산광역시 해운대구 중동 1829 엘시티부산광역시 해운대구 달맞이길 30, 제포디움동 2층 2023호 (중동, 엘시티)48099(주)구주20210722090252U2021-07-24 02:40:00.0<NA><NA><NA>국내여행업관광사업<NA>0<NA><NA>한국관광협회중앙회 여행공제회<NA>0000<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>02021060520220605<NA>0<NA>
12291230국내여행업03_12_01_P3330000CDFI226001202100000120180409<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>부산광역시 해운대구 우동 1407 해운대두산위브더제니스 104동 214호부산광역시 해운대구 마린시티2로 33, 104동 214호 (우동, 해운대두산위브더제니스)48119(주)아리아투어20210222181139I2021-02-24 00:23:01.0<NA>395388.71507186268.853283국내여행업<NA><NA><NA><NA><NA>서울보증보험주식회사<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>150000002020040120210331<NA><NA><NA>
12301231국내여행업03_12_01_P3330000CDFI226001202100000320210414<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>부산광역시 해운대구 중동 1394-286 크리스탈비치오피스텔 620호부산광역시 해운대구 해운대해변로 291, 크리스탈비치오피스텔 620호 (중동)48095부산여성트레킹20210416105129U2021-04-18 02:40:00.0<NA>396962.538162186759.941709국내여행업<NA><NA><NA><NA><NA>서울보증보험<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021041420220413<NA><NA><NA>
12311232국내여행업03_12_01_P3330000CDFI226001202100000220210318<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>부산광역시 해운대구 재송동 1108-6 303호부산광역시 해운대구 해운대로143번길 38, 303호 (재송동)48055모아디자인20210323124804U2021-03-25 02:40:00.0<NA>393326.171272189353.108229국내여행업<NA><NA><NA><NA><NA>서울보증보험<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021032220220321<NA><NA><NA>
12321233국내여행업03_12_01_P3330000CDFI226001202000000920201127<NA>1영업/정상13영업중<NA><NA><NA><NA>051-633-1161<NA><NA>부산광역시 해운대구 재송동 939-2 센텀이편한세상아파트 101동 2001호부산광역시 해운대구 해운대로76번길 55, 101동 2001호 (재송동, 센텀이편한세상아파트)48048(주)콜럼버스코리아20201221160950U2020-12-23 02:40:00.0<NA>392799.149932189781.150493국내여행업<NA><NA><NA><NA><NA>서울보증보험<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020120120211130<NA><NA><NA>
12331234국내여행업03_12_01_P3330000CDFI226001200100000120010330<NA>4취소/말소/만료/정지/중지30허가취소<NA><NA><NA><NA>051-747-4446<NA>612824부산광역시 해운대구 우동 1434번지 선프라자 201부산광역시 해운대구 마린시티3로 1, 201호 (우동, 선프라자)612725(주)뉴그린여행사20111115163559I2018-08-31 23:59:59.0<NA>395615.201854186406.750871국내여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12341235국내여행업03_12_01_P3330000CDFI226001201300000320130308201501284취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA><NA><NA>612862부산광역시 해운대구 좌동 1432-4번지 르네상스오피스텔 304호부산광역시 해운대구 좌동순환로249번길 11, 304호 (좌동, 르네상스오피스텔)612862(주) 밀크투어20150325162610I2018-08-31 23:59:59.0<NA>398665.261088188263.875653국내여행업<NA><NA><NA><NA><NA>서울보증보험<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>30000002013031520140314<NA><NA><NA>
12351236국내여행업03_12_01_P3330000CDFI226001201000000620100916201410074취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA>740-6033<NA>612726부산광역시 해운대구 우동 오션타워 718호부산광역시 해운대구 해운대해변로 203, 718호 (우동, 오션타워)612726(주)비케이트래블20141226115313I2018-08-31 23:59:59.0<NA>396180.621245186522.350475국내여행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>81517681<NA><NA><NA><NA><NA>
12361237국내여행업03_12_01_P3330000CDFI226001200400000120040107201410074취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA><NA><NA>612836부산광역시 해운대구 좌동 1460-4번지 쌍용플래티넘트윈102-201호부산광역시 해운대구 양운로 82, 102동 201호 (좌동, 쌍용플래티넘트윈)612836(주) 신나라 투어20141226115517I2018-08-31 23:59:59.0<NA>398133.960402187864.096706국내여행업관광사업일반상업지역7아파트지역<NA><NA>사무실71<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>150000000<NA><NA><NA><NA><NA>
12371238국내여행업03_12_01_P3330000CDFI226001200400000520040310201409124취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA>051-731-7191<NA>612821부산광역시 해운대구 우동 640-24번지부산광역시 해운대구 해운대로 575 (우동)612821(주)W.T.우리여행사20141226115732I2018-08-31 23:59:59.0<NA>396225.196088186827.050656국내여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>