Overview

Dataset statistics

Number of variables39
Number of observations900
Missing cells7624
Missing cells (%)21.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory290.2 KiB
Average record size in memory330.1 B

Variable types

Numeric13
Unsupported1
Categorical13
Text10
Boolean1
DateTime1

Dataset

Description경기도_BMS 업체/차고지 부대시설 이력 정보
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=1P8UMW2W2IV46ZRQND0K33225473&infSeq=1

Alerts

1차승인자아이디 has constant value ""Constant
신고인가구분 is highly imbalanced (75.0%)Imbalance
처리진행코드 is highly imbalanced (80.3%)Imbalance
1차승인일자 is highly imbalanced (98.7%)Imbalance
최종승인자아이디 is highly imbalanced (80.4%)Imbalance
비고 is highly imbalanced (83.4%)Imbalance
신고인가구분명 is highly imbalanced (80.3%)Imbalance
업무코드명 is highly imbalanced (72.8%)Imbalance
영업소아이디 has 900 (100.0%) missing valuesMissing
전체규모 has 282 (31.3%) missing valuesMissing
기관코드 has 42 (4.7%) missing valuesMissing
수용가능수 has 512 (56.9%) missing valuesMissing
사용구분 has 106 (11.8%) missing valuesMissing
부대시설상세명 has 655 (72.8%) missing valuesMissing
계약시작일 has 435 (48.3%) missing valuesMissing
계약종료일 has 441 (49.0%) missing valuesMissing
사용면적 has 343 (38.1%) missing valuesMissing
차량대수 has 499 (55.4%) missing valuesMissing
1차승인자아이디 has 899 (99.9%) missing valuesMissing
최종승인일자 has 54 (6.0%) missing valuesMissing
2차주소 has 15 (1.7%) missing valuesMissing
수정아이디 has 624 (69.3%) missing valuesMissing
갱신일자 has 624 (69.3%) missing valuesMissing
전화번호 has 556 (61.8%) missing valuesMissing
팩스번호 has 625 (69.4%) missing valuesMissing
영업소아이디 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전체규모 has 11 (1.2%) zerosZeros
수용가능수 has 77 (8.6%) zerosZeros
사용면적 has 67 (7.4%) zerosZeros
차량대수 has 146 (16.2%) zerosZeros

Reproduction

Analysis started2024-04-19 05:44:56.174378
Analysis finished2024-04-19 05:44:57.116749
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설아이디
Real number (ℝ)

Distinct860
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10836.061
Minimum10001
Maximum20960
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-04-19T14:44:57.183808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10001
5-th percentile10048.95
Q110226.5
median10451.5
Q310670
95-th percentile10997.05
Maximum20960
Range10959
Interquartile range (IQR)443.5

Descriptive statistics

Standard deviation1968.6018
Coefficient of variation (CV)0.18167135
Kurtosis20.755766
Mean10836.061
Median Absolute Deviation (MAD)221
Skewness4.7132127
Sum9752455
Variance3875393
MonotonicityNot monotonic
2024-04-19T14:44:57.310667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10670 3
 
0.3%
10669 3
 
0.3%
10035 3
 
0.3%
10682 2
 
0.2%
10545 2
 
0.2%
20440 2
 
0.2%
10025 2
 
0.2%
10695 2
 
0.2%
10694 2
 
0.2%
10690 2
 
0.2%
Other values (850) 877
97.4%
ValueCountFrequency (%)
10001 1
0.1%
10002 1
0.1%
10010 1
0.1%
10012 1
0.1%
10013 1
0.1%
10014 1
0.1%
10015 1
0.1%
10016 1
0.1%
10017 1
0.1%
10018 1
0.1%
ValueCountFrequency (%)
20960 1
0.1%
20940 1
0.1%
20920 1
0.1%
20880 1
0.1%
20861 1
0.1%
20860 1
0.1%
20840 1
0.1%
20820 1
0.1%
20800 1
0.1%
20780 1
0.1%

이력아이디
Real number (ℝ)

Distinct100
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0711244 × 109
Minimum1 × 109
Maximum2.0001571 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-04-19T14:44:57.443192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1 × 109
5-th percentile1 × 109
Q11 × 109
median1 × 109
Q31 × 109
95-th percentile2.0000615 × 109
Maximum2.0001571 × 109
Range1.0001571 × 109
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.5716921 × 108
Coefficient of variation (CV)0.24009277
Kurtosis9.196727
Mean1.0711244 × 109
Median Absolute Deviation (MAD)0
Skewness3.3430965
Sum9.6401192 × 1011
Variance6.6136005 × 1016
MonotonicityNot monotonic
2024-04-19T14:44:57.594675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1000000000 794
88.2%
1000046172 8
 
0.9%
1000351749 1
 
0.1%
2000120182 1
 
0.1%
2000080392 1
 
0.1%
2000080391 1
 
0.1%
2000080389 1
 
0.1%
2000070910 1
 
0.1%
2000070909 1
 
0.1%
2000070436 1
 
0.1%
Other values (90) 90
 
10.0%
ValueCountFrequency (%)
1000000000 794
88.2%
1000002411 1
 
0.1%
1000008634 1
 
0.1%
1000009135 1
 
0.1%
1000037370 1
 
0.1%
1000046045 1
 
0.1%
1000046172 8
 
0.9%
1000046236 1
 
0.1%
1000046237 1
 
0.1%
1000046245 1
 
0.1%
ValueCountFrequency (%)
2000157090 1
0.1%
2000157040 1
0.1%
2000157038 1
0.1%
2000151070 1
0.1%
2000151068 1
0.1%
2000144095 1
0.1%
2000120182 1
0.1%
2000119973 1
0.1%
2000119956 1
0.1%
2000118956 1
0.1%

업체아이디
Real number (ℝ)

Distinct148
Distinct (%)16.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4124420.4
Minimum4100100
Maximum4160300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-04-19T14:44:57.750859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4100100
5-th percentile4100795
Q14103000
median4110650
Q34150500
95-th percentile4153900
Maximum4160300
Range60200
Interquartile range (IQR)47500

Descriptive statistics

Standard deviation22654.948
Coefficient of variation (CV)0.0054928804
Kurtosis-1.7797174
Mean4124420.4
Median Absolute Deviation (MAD)10300
Skewness0.25007655
Sum3.7119784 × 109
Variance5.1324668 × 108
MonotonicityNot monotonic
2024-04-19T14:44:57.901124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4150200 49
 
5.4%
4104000 43
 
4.8%
4101600 40
 
4.4%
4151400 35
 
3.9%
4102600 32
 
3.6%
4150300 32
 
3.6%
4150600 24
 
2.7%
4153600 21
 
2.3%
4102000 19
 
2.1%
4154000 16
 
1.8%
Other values (138) 589
65.4%
ValueCountFrequency (%)
4100100 2
 
0.2%
4100200 11
1.2%
4100300 5
0.6%
4100400 8
0.9%
4100500 8
0.9%
4100600 5
0.6%
4100700 6
0.7%
4100800 2
 
0.2%
4100900 2
 
0.2%
4101100 9
1.0%
ValueCountFrequency (%)
4160300 1
 
0.1%
4160000 1
 
0.1%
4159700 1
 
0.1%
4159600 1
 
0.1%
4159500 1
 
0.1%
4159400 1
 
0.1%
4159300 1
 
0.1%
4159200 5
0.6%
4159100 1
 
0.1%
4158900 1
 
0.1%

영업소아이디
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing900
Missing (%)100.0%
Memory size8.0 KiB

시설코드
Real number (ℝ)

Distinct10
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3244444
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-04-19T14:44:58.026845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q38
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.3493748
Coefficient of variation (CV)0.77452141
Kurtosis-1.1824551
Mean4.3244444
Median Absolute Deviation (MAD)2
Skewness0.68101012
Sum3892
Variance11.218312
MonotonicityNot monotonic
2024-04-19T14:44:58.132805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 253
28.1%
1 186
20.7%
10 130
14.4%
3 94
 
10.4%
9 62
 
6.9%
4 49
 
5.4%
8 49
 
5.4%
6 39
 
4.3%
7 24
 
2.7%
5 14
 
1.6%
ValueCountFrequency (%)
1 186
20.7%
2 253
28.1%
3 94
 
10.4%
4 49
 
5.4%
5 14
 
1.6%
6 39
 
4.3%
7 24
 
2.7%
8 49
 
5.4%
9 62
 
6.9%
10 130
14.4%
ValueCountFrequency (%)
10 130
14.4%
9 62
 
6.9%
8 49
 
5.4%
7 24
 
2.7%
6 39
 
4.3%
5 14
 
1.6%
4 49
 
5.4%
3 94
 
10.4%
2 253
28.1%
1 186
20.7%

전체규모
Real number (ℝ)

MISSING  ZEROS 

Distinct457
Distinct (%)73.9%
Missing282
Missing (%)31.3%
Infinite0
Infinite (%)0.0%
Mean1671.9109
Minimum0
Maximum25312
Zeros11
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-04-19T14:44:58.248011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.068
Q150.55
median323
Q31832.97
95-th percentile7733.8815
Maximum25312
Range25312
Interquartile range (IQR)1782.42

Descriptive statistics

Standard deviation3056.0994
Coefficient of variation (CV)1.827908
Kurtosis17.83457
Mean1671.9109
Median Absolute Deviation (MAD)309.55
Skewness3.5829513
Sum1033240.9
Variance9339743.6
MonotonicityNot monotonic
2024-04-19T14:44:58.377378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 11
 
1.2%
100.0 8
 
0.9%
20.0 8
 
0.9%
80.0 6
 
0.7%
50.0 6
 
0.7%
1000.0 6
 
0.7%
18.0 5
 
0.6%
323.0 5
 
0.6%
24.0 4
 
0.4%
1800.0 4
 
0.4%
Other values (447) 555
61.7%
(Missing) 282
31.3%
ValueCountFrequency (%)
0.0 11
1.2%
3.5 1
 
0.1%
4.06 1
 
0.1%
4.95 1
 
0.1%
5.76 1
 
0.1%
6.0 1
 
0.1%
6.24 1
 
0.1%
7.4 1
 
0.1%
7.5 1
 
0.1%
7.68 1
 
0.1%
ValueCountFrequency (%)
25312.0 1
0.1%
24200.21 1
0.1%
23111.0 1
0.1%
18443.7 1
0.1%
18216.0 1
0.1%
14578.0 1
0.1%
14365.83 1
0.1%
12071.4 1
0.1%
11571.0 1
0.1%
10178.0 1
0.1%
Distinct8
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
<NA>
410 
6
145 
5
101 
3
62 
61 
Other values (3)
121 

Length

Max length4
Median length1
Mean length2.3666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 410
45.6%
6 145
 
16.1%
5 101
 
11.2%
3 62
 
6.9%
61
 
6.8%
4 58
 
6.4%
2 41
 
4.6%
1 22
 
2.4%

Length

2024-04-19T14:44:58.499982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:44:58.617072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 410
48.9%
6 145
 
17.3%
5 101
 
12.0%
3 62
 
7.4%
4 58
 
6.9%
2 41
 
4.9%
1 22
 
2.6%

우편번호
Real number (ℝ)

Distinct292
Distinct (%)32.7%
Missing6
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean350996.43
Minimum8507
Maximum760110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-04-19T14:44:58.745403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8507
5-th percentile12009.4
Q1336040
median441350
Q3463870
95-th percentile483110
Maximum760110
Range751603
Interquartile range (IQR)127830

Descriptive statistics

Standard deviation183170.13
Coefficient of variation (CV)0.52185755
Kurtosis-0.28895876
Mean350996.43
Median Absolute Deviation (MAD)29940
Skewness-1.0684106
Sum3.137908 × 108
Variance3.3551298 × 1010
MonotonicityNot monotonic
2024-04-19T14:44:58.883900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441350 45
 
5.0%
486802 16
 
1.8%
14083 16
 
1.8%
480100 15
 
1.7%
421180 14
 
1.6%
483100 13
 
1.4%
482832 13
 
1.4%
16230 12
 
1.3%
336040 12
 
1.3%
464050 12
 
1.3%
Other values (282) 726
80.7%
ValueCountFrequency (%)
8507 1
 
0.1%
10220 6
0.7%
10251 3
0.3%
10258 1
 
0.1%
10264 1
 
0.1%
10266 1
 
0.1%
10267 1
 
0.1%
10283 1
 
0.1%
10315 2
 
0.2%
10316 1
 
0.1%
ValueCountFrequency (%)
760110 2
 
0.2%
750010 1
 
0.1%
745804 1
 
0.1%
745120 1
 
0.1%
745050 2
 
0.2%
742933 1
 
0.1%
742090 1
 
0.1%
701020 1
 
0.1%
487873 2
 
0.2%
487862 8
0.9%

기관코드
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)3.7%
Missing42
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean4.1206189 × 109
Minimum4.1 × 109
Maximum4.199 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-04-19T14:44:59.040273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.1 × 109
5-th percentile4.1 × 109
Q14.1 × 109
median4.113 × 109
Q34.128 × 109
95-th percentile4.163 × 109
Maximum4.199 × 109
Range99000000
Interquartile range (IQR)28000000

Descriptive statistics

Standard deviation22067267
Coefficient of variation (CV)0.0053553283
Kurtosis0.41381714
Mean4.1206189 × 109
Median Absolute Deviation (MAD)13000000
Skewness1.0791164
Sum3.535491 × 1012
Variance4.8696426 × 1014
MonotonicityNot monotonic
2024-04-19T14:44:59.182955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
4100000000 299
33.2%
4113000000 67
 
7.4%
4128000000 67
 
7.4%
4111000000 64
 
7.1%
4119000000 34
 
3.8%
4122000000 32
 
3.6%
4163000000 29
 
3.2%
4117000000 23
 
2.6%
4136000000 23
 
2.6%
4115000000 22
 
2.4%
Other values (22) 198
22.0%
(Missing) 42
 
4.7%
ValueCountFrequency (%)
4100000000 299
33.2%
4111000000 64
 
7.1%
4113000000 67
 
7.4%
4115000000 22
 
2.4%
4117000000 23
 
2.6%
4119000000 34
 
3.8%
4121000000 8
 
0.9%
4122000000 32
 
3.6%
4125000000 22
 
2.4%
4127000000 11
 
1.2%
ValueCountFrequency (%)
4199000000 2
 
0.2%
4183000000 2
 
0.2%
4182000000 11
 
1.2%
4180000000 10
 
1.1%
4173000000 1
 
0.1%
4165000000 4
 
0.4%
4163000000 29
3.2%
4161000000 17
1.9%
4159000000 15
1.7%
4157000000 13
1.4%

수용가능수
Real number (ℝ)

MISSING  ZEROS 

Distinct131
Distinct (%)33.8%
Missing512
Missing (%)56.9%
Infinite0
Infinite (%)0.0%
Mean60.92268
Minimum0
Maximum1631
Zeros77
Zeros (%)8.6%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-04-19T14:44:59.323777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16.75
median30
Q377.5
95-th percentile190.65
Maximum1631
Range1631
Interquartile range (IQR)70.75

Descriptive statistics

Standard deviation114.86142
Coefficient of variation (CV)1.8853639
Kurtosis93.788614
Mean60.92268
Median Absolute Deviation (MAD)30
Skewness7.869094
Sum23638
Variance13193.146
MonotonicityNot monotonic
2024-04-19T14:44:59.457911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 77
 
8.6%
25 13
 
1.4%
20 9
 
1.0%
10 9
 
1.0%
17 7
 
0.8%
14 7
 
0.8%
30 6
 
0.7%
23 6
 
0.7%
118 6
 
0.7%
4 6
 
0.7%
Other values (121) 242
26.9%
(Missing) 512
56.9%
ValueCountFrequency (%)
0 77
8.6%
1 1
 
0.1%
2 2
 
0.2%
3 2
 
0.2%
4 6
 
0.7%
5 5
 
0.6%
6 4
 
0.4%
7 1
 
0.1%
8 3
 
0.3%
9 1
 
0.1%
ValueCountFrequency (%)
1631 1
0.1%
633 1
0.1%
605 1
0.1%
578 1
0.1%
461 1
0.1%
455 1
0.1%
340 1
0.1%
302 1
0.1%
300 1
0.1%
289 1
0.1%
Distinct146
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2024-04-19T14:44:59.757379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length7.8588889
Min length5

Characters and Unicode

Total characters7073
Distinct characters49
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)6.2%

Sample

1st rowycbusi05
2nd rowycbusi05
3rd rowycbusi05
4th rowycbusi05
5th rowbus01971
ValueCountFrequency (%)
suilkhs1 284
31.6%
pyungan1 42
 
4.7%
msws7031 40
 
4.4%
sncb2000 20
 
2.2%
stbm1443 19
 
2.1%
uj35381 18
 
2.0%
hogyebus 15
 
1.7%
swws3483 15
 
1.7%
yong6624 13
 
1.4%
han20084 11
 
1.2%
Other values (136) 423
47.0%
2024-04-19T14:45:00.276157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 988
 
14.0%
1 664
 
9.4%
u 505
 
7.1%
h 405
 
5.7%
i 384
 
5.4%
k 381
 
5.4%
l 342
 
4.8%
0 307
 
4.3%
n 290
 
4.1%
3 226
 
3.2%
Other values (39) 2581
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4963
70.2%
Decimal Number 2093
29.6%
Uppercase Letter 13
 
0.2%
Other Punctuation 3
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 988
19.9%
u 505
10.2%
h 405
 
8.2%
i 384
 
7.7%
k 381
 
7.7%
l 342
 
6.9%
n 290
 
5.8%
b 201
 
4.0%
g 187
 
3.8%
y 181
 
3.6%
Other values (15) 1099
22.1%
Uppercase Letter
ValueCountFrequency (%)
H 2
15.4%
A 2
15.4%
O 1
7.7%
N 1
7.7%
D 1
7.7%
T 1
7.7%
C 1
7.7%
L 1
7.7%
S 1
7.7%
G 1
7.7%
Decimal Number
ValueCountFrequency (%)
1 664
31.7%
0 307
14.7%
3 226
 
10.8%
2 204
 
9.7%
7 138
 
6.6%
4 138
 
6.6%
8 133
 
6.4%
5 126
 
6.0%
6 84
 
4.0%
9 73
 
3.5%
Other Punctuation
ValueCountFrequency (%)
* 2
66.7%
. 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4976
70.4%
Common 2097
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 988
19.9%
u 505
10.1%
h 405
 
8.1%
i 384
 
7.7%
k 381
 
7.7%
l 342
 
6.9%
n 290
 
5.8%
b 201
 
4.0%
g 187
 
3.8%
y 181
 
3.6%
Other values (26) 1112
22.3%
Common
ValueCountFrequency (%)
1 664
31.7%
0 307
14.6%
3 226
 
10.8%
2 204
 
9.7%
7 138
 
6.6%
4 138
 
6.6%
8 133
 
6.3%
5 126
 
6.0%
6 84
 
4.0%
9 73
 
3.5%
Other values (3) 4
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7073
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 988
 
14.0%
1 664
 
9.4%
u 505
 
7.1%
h 405
 
5.7%
i 384
 
5.4%
k 381
 
5.4%
l 342
 
4.8%
0 307
 
4.3%
n 290
 
4.1%
3 226
 
3.2%
Other values (39) 2581
36.5%

등록일자
Real number (ℝ)

Distinct899
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0100087 × 1013
Minimum2.0070903 × 1013
Maximum2.0230813 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-04-19T14:45:00.433968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0070903 × 1013
5-th percentile2.0070903 × 1013
Q12.0070906 × 1013
median2.0071019 × 1013
Q32.0160317 × 1013
95-th percentile2.0210323 × 1013
Maximum2.0230813 × 1013
Range1.5991003 × 1011
Interquartile range (IQR)8.9410956 × 1010

Descriptive statistics

Standard deviation4.6911638 × 1010
Coefficient of variation (CV)0.0023339023
Kurtosis-0.013645383
Mean2.0100087 × 1013
Median Absolute Deviation (MAD)1.1300126 × 108
Skewness1.2299125
Sum1.8090078 × 1016
Variance2.2007018 × 1021
MonotonicityNot monotonic
2024-04-19T14:45:00.582663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20070907143047 2
 
0.2%
20070903162428 1
 
0.1%
20080801140155 1
 
0.1%
20110711162508 1
 
0.1%
20111124131914 1
 
0.1%
20111116114012 1
 
0.1%
20111124132347 1
 
0.1%
20111129184923 1
 
0.1%
20111130113152 1
 
0.1%
20111130142823 1
 
0.1%
Other values (889) 889
98.8%
ValueCountFrequency (%)
20070903102802 1
0.1%
20070903102849 1
0.1%
20070903132930 1
0.1%
20070903141344 1
0.1%
20070903142810 1
0.1%
20070903144804 1
0.1%
20070903144808 1
0.1%
20070903145010 1
0.1%
20070903145101 1
0.1%
20070903145115 1
0.1%
ValueCountFrequency (%)
20230813130217 1
0.1%
20230813125827 1
0.1%
20230811133249 1
0.1%
20230601110514 1
0.1%
20230601110344 1
0.1%
20230310152202 1
0.1%
20221012150002 1
0.1%
20220614082429 1
0.1%
20220614082208 1
0.1%
20220609103629 1
0.1%
Distinct425
Distinct (%)47.2%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2024-04-19T14:45:00.779127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length5.2344444
Min length1

Characters and Unicode

Total characters4711
Distinct characters223
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique345 ?
Unique (%)38.3%

Sample

1st row기사식당
2nd row전곡영업소사무실
3rd row전곡영업소기사휴게실
4th row전곡영업소식당
5th row불광동시외버스 터미널
ValueCountFrequency (%)
차고지 181
 
16.5%
사무실 56
 
5.1%
휴게실 42
 
3.8%
숙소 33
 
3.0%
30
 
2.7%
식당 18
 
1.6%
공영차고지 15
 
1.4%
화장실 14
 
1.3%
가능동 13
 
1.2%
세차시설 13
 
1.2%
Other values (409) 682
62.2%
2024-04-19T14:45:01.112107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
451
 
9.6%
411
 
8.7%
369
 
7.8%
220
 
4.7%
202
 
4.3%
159
 
3.4%
144
 
3.1%
( 102
 
2.2%
) 102
 
2.2%
99
 
2.1%
Other values (213) 2452
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4173
88.6%
Space Separator 202
 
4.3%
Open Punctuation 102
 
2.2%
Close Punctuation 102
 
2.2%
Decimal Number 86
 
1.8%
Other Punctuation 32
 
0.7%
Dash Punctuation 8
 
0.2%
Uppercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
451
 
10.8%
411
 
9.8%
369
 
8.8%
220
 
5.3%
159
 
3.8%
144
 
3.5%
99
 
2.4%
98
 
2.3%
91
 
2.2%
89
 
2.1%
Other values (191) 2042
48.9%
Decimal Number
ValueCountFrequency (%)
1 18
20.9%
3 16
18.6%
2 15
17.4%
7 11
12.8%
6 9
10.5%
9 6
 
7.0%
4 4
 
4.7%
5 4
 
4.7%
8 2
 
2.3%
0 1
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
T 2
33.3%
E 1
16.7%
S 1
16.7%
H 1
16.7%
L 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 26
81.2%
/ 4
 
12.5%
. 2
 
6.2%
Space Separator
ValueCountFrequency (%)
202
100.0%
Open Punctuation
ValueCountFrequency (%)
( 102
100.0%
Close Punctuation
ValueCountFrequency (%)
) 102
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4173
88.6%
Common 532
 
11.3%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
451
 
10.8%
411
 
9.8%
369
 
8.8%
220
 
5.3%
159
 
3.8%
144
 
3.5%
99
 
2.4%
98
 
2.3%
91
 
2.2%
89
 
2.1%
Other values (191) 2042
48.9%
Common
ValueCountFrequency (%)
202
38.0%
( 102
19.2%
) 102
19.2%
, 26
 
4.9%
1 18
 
3.4%
3 16
 
3.0%
2 15
 
2.8%
7 11
 
2.1%
6 9
 
1.7%
- 8
 
1.5%
Other values (7) 23
 
4.3%
Latin
ValueCountFrequency (%)
T 2
33.3%
E 1
16.7%
S 1
16.7%
H 1
16.7%
L 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4161
88.3%
ASCII 538
 
11.4%
Compat Jamo 12
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
451
 
10.8%
411
 
9.9%
369
 
8.9%
220
 
5.3%
159
 
3.8%
144
 
3.5%
99
 
2.4%
98
 
2.4%
91
 
2.2%
89
 
2.1%
Other values (184) 2030
48.8%
ASCII
ValueCountFrequency (%)
202
37.5%
( 102
19.0%
) 102
19.0%
, 26
 
4.8%
1 18
 
3.3%
3 16
 
3.0%
2 15
 
2.8%
7 11
 
2.0%
6 9
 
1.7%
- 8
 
1.5%
Other values (12) 29
 
5.4%
Compat Jamo
ValueCountFrequency (%)
3
25.0%
3
25.0%
2
16.7%
1
 
8.3%
1
 
8.3%
1
 
8.3%
1
 
8.3%
Distinct310
Distinct (%)34.7%
Missing6
Missing (%)0.7%
Memory size7.2 KiB
2024-04-19T14:45:01.433747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length30
Mean length15.844519
Min length10

Characters and Unicode

Total characters14165
Distinct characters236
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

Unique163 ?
Unique (%)18.2%

Sample

1st row경기 동두천시 하봉암동
2nd row경기 연천군 전곡읍
3rd row경기 연천군 전곡읍
4th row경기 연천군 전곡읍
5th row서울 은평구 대조동
ValueCountFrequency (%)
경기 731
 
20.2%
수원시 108
 
3.0%
성남시 86
 
2.4%
권선구 76
 
2.1%
고양시 67
 
1.9%
오목천동 47
 
1.3%
경기도 45
 
1.2%
분당구 45
 
1.2%
부천시 44
 
1.2%
인천 44
 
1.2%
Other values (532) 2325
64.3%
2024-04-19T14:45:01.855064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3204
22.6%
801
 
5.7%
801
 
5.7%
774
 
5.5%
736
 
5.2%
469
 
3.3%
253
 
1.8%
239
 
1.7%
237
 
1.7%
200
 
1.4%
Other values (226) 6451
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9945
70.2%
Space Separator 3204
 
22.6%
Decimal Number 729
 
5.1%
Open Punctuation 122
 
0.9%
Close Punctuation 122
 
0.9%
Dash Punctuation 39
 
0.3%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
801
 
8.1%
801
 
8.1%
774
 
7.8%
736
 
7.4%
469
 
4.7%
253
 
2.5%
239
 
2.4%
237
 
2.4%
200
 
2.0%
169
 
1.7%
Other values (211) 5266
53.0%
Decimal Number
ValueCountFrequency (%)
1 186
25.5%
4 106
14.5%
2 82
11.2%
7 68
 
9.3%
3 66
 
9.1%
9 62
 
8.5%
6 57
 
7.8%
0 46
 
6.3%
5 29
 
4.0%
8 27
 
3.7%
Space Separator
ValueCountFrequency (%)
3204
100.0%
Open Punctuation
ValueCountFrequency (%)
( 122
100.0%
Close Punctuation
ValueCountFrequency (%)
) 122
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9945
70.2%
Common 4220
29.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
801
 
8.1%
801
 
8.1%
774
 
7.8%
736
 
7.4%
469
 
4.7%
253
 
2.5%
239
 
2.4%
237
 
2.4%
200
 
2.0%
169
 
1.7%
Other values (211) 5266
53.0%
Common
ValueCountFrequency (%)
3204
75.9%
1 186
 
4.4%
( 122
 
2.9%
) 122
 
2.9%
4 106
 
2.5%
2 82
 
1.9%
7 68
 
1.6%
3 66
 
1.6%
9 62
 
1.5%
6 57
 
1.4%
Other values (5) 145
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9945
70.2%
ASCII 4220
29.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3204
75.9%
1 186
 
4.4%
( 122
 
2.9%
) 122
 
2.9%
4 106
 
2.5%
2 82
 
1.9%
7 68
 
1.6%
3 66
 
1.6%
9 62
 
1.5%
6 57
 
1.4%
Other values (5) 145
 
3.4%
Hangul
ValueCountFrequency (%)
801
 
8.1%
801
 
8.1%
774
 
7.8%
736
 
7.4%
469
 
4.7%
253
 
2.5%
239
 
2.4%
237
 
2.4%
200
 
2.0%
169
 
1.7%
Other values (211) 5266
53.0%

사용구분
Boolean

MISSING 

Distinct2
Distinct (%)0.3%
Missing106
Missing (%)11.8%
Memory size1.9 KiB
True
703 
False
91 
(Missing)
106 
ValueCountFrequency (%)
True 703
78.1%
False 91
 
10.1%
(Missing) 106
 
11.8%
2024-04-19T14:45:01.975122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

신고인가구분
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
<NA>
799 
1
 
63
2
 
33
10
 
3
9
 
1

Length

Max length4
Median length4
Mean length3.6666667
Min length1

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 799
88.8%
1 63
 
7.0%
2 33
 
3.7%
10 3
 
0.3%
9 1
 
0.1%
8 1
 
0.1%

Length

2024-04-19T14:45:02.398126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:45:02.508262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 799
88.8%
1 63
 
7.0%
2 33
 
3.7%
10 3
 
0.3%
9 1
 
0.1%
8 1
 
0.1%

소유구분
Categorical

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
L
458 
J
222 
C
188 
M
 
32

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
L 458
50.9%
J 222
24.7%
C 188
20.9%
M 32
 
3.6%

Length

2024-04-19T14:45:02.619644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:45:02.718180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
l 458
50.9%
j 222
24.7%
c 188
20.9%
m 32
 
3.6%

부대시설상세명
Text

MISSING 

Distinct211
Distinct (%)86.1%
Missing655
Missing (%)72.8%
Memory size7.2 KiB
2024-04-19T14:45:02.967023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length112
Median length77
Mean length20.318367
Min length1

Characters and Unicode

Total characters4978
Distinct characters257
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique192 ?
Unique (%)78.4%

Sample

1st row서울 유출입 차량을 위하여 임대
2nd row적성영업소 차고지
3rd row신일여객 본사 주차장 무상임대, 정비실, 세차장
4th row1층(사무실82, 중역실15, 기타:67(샤워장,화장실) 2층(휴게실21.33, 교양실40.56, 기타 79.46) 정비실:201.3
5th row주유시설,세차시설,차고지
ValueCountFrequency (%)
사무실 33
 
4.3%
차고지 31
 
4.0%
휴게실 29
 
3.7%
25
 
3.2%
21
 
2.7%
식당 14
 
1.8%
10
 
1.3%
교육실 10
 
1.3%
세차장 9
 
1.2%
기타 8
 
1.0%
Other values (447) 586
75.5%
2024-04-19T14:45:03.378913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
560
 
11.2%
, 294
 
5.9%
224
 
4.5%
1 159
 
3.2%
150
 
3.0%
2 142
 
2.9%
122
 
2.5%
. 116
 
2.3%
( 105
 
2.1%
) 103
 
2.1%
Other values (247) 3003
60.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2727
54.8%
Decimal Number 836
 
16.8%
Space Separator 560
 
11.2%
Other Punctuation 455
 
9.1%
Open Punctuation 105
 
2.1%
Close Punctuation 103
 
2.1%
Dash Punctuation 77
 
1.5%
Other Symbol 48
 
1.0%
Lowercase Letter 29
 
0.6%
Uppercase Letter 18
 
0.4%
Other values (3) 20
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
224
 
8.2%
150
 
5.5%
122
 
4.5%
103
 
3.8%
97
 
3.6%
86
 
3.2%
84
 
3.1%
78
 
2.9%
76
 
2.8%
71
 
2.6%
Other values (214) 1636
60.0%
Decimal Number
ValueCountFrequency (%)
1 159
19.0%
2 142
17.0%
0 101
12.1%
4 76
9.1%
3 75
9.0%
6 67
8.0%
5 62
 
7.4%
8 57
 
6.8%
7 55
 
6.6%
9 42
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
T 3
16.7%
S 3
16.7%
G 2
11.1%
N 2
11.1%
C 2
11.1%
M 2
11.1%
B 2
11.1%
E 1
 
5.6%
V 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 294
64.6%
. 116
 
25.5%
: 35
 
7.7%
/ 8
 
1.8%
* 2
 
0.4%
Space Separator
ValueCountFrequency (%)
560
100.0%
Open Punctuation
ValueCountFrequency (%)
( 105
100.0%
Close Punctuation
ValueCountFrequency (%)
) 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%
Other Symbol
ValueCountFrequency (%)
48
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 29
100.0%
Other Number
ValueCountFrequency (%)
² 15
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2727
54.8%
Common 2204
44.3%
Latin 47
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
224
 
8.2%
150
 
5.5%
122
 
4.5%
103
 
3.8%
97
 
3.6%
86
 
3.2%
84
 
3.1%
78
 
2.9%
76
 
2.8%
71
 
2.6%
Other values (214) 1636
60.0%
Common
ValueCountFrequency (%)
560
25.4%
, 294
13.3%
1 159
 
7.2%
2 142
 
6.4%
. 116
 
5.3%
( 105
 
4.8%
) 103
 
4.7%
0 101
 
4.6%
- 77
 
3.5%
4 76
 
3.4%
Other values (13) 471
21.4%
Latin
ValueCountFrequency (%)
m 29
61.7%
T 3
 
6.4%
S 3
 
6.4%
G 2
 
4.3%
N 2
 
4.3%
C 2
 
4.3%
M 2
 
4.3%
B 2
 
4.3%
E 1
 
2.1%
V 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2727
54.8%
ASCII 2188
44.0%
CJK Compat 48
 
1.0%
None 15
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
560
25.6%
, 294
13.4%
1 159
 
7.3%
2 142
 
6.5%
. 116
 
5.3%
( 105
 
4.8%
) 103
 
4.7%
0 101
 
4.6%
- 77
 
3.5%
4 76
 
3.5%
Other values (21) 455
20.8%
Hangul
ValueCountFrequency (%)
224
 
8.2%
150
 
5.5%
122
 
4.5%
103
 
3.8%
97
 
3.6%
86
 
3.2%
84
 
3.1%
78
 
2.9%
76
 
2.8%
71
 
2.6%
Other values (214) 1636
60.0%
CJK Compat
ValueCountFrequency (%)
48
100.0%
None
ValueCountFrequency (%)
² 15
100.0%

계약시작일
Date

MISSING 

Distinct156
Distinct (%)33.5%
Missing435
Missing (%)48.3%
Memory size7.2 KiB
Minimum1988-07-30 00:00:00
Maximum2031-12-15 00:00:00
2024-04-19T14:45:03.511629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:45:03.636148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

계약종료일
Text

MISSING 

Distinct149
Distinct (%)32.5%
Missing441
Missing (%)49.0%
Memory size7.2 KiB
2024-04-19T14:45:03.970115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters3672
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

Unique97 ?
Unique (%)21.1%

Sample

1st row08/06/01
2nd row08/03/01
3rd row08/03/01
4th row08/03/01
5th row08/07/31
ValueCountFrequency (%)
07/10/01 125
27.2%
07/12/31 21
 
4.6%
20/12/31 14
 
3.1%
08/01/13 10
 
2.2%
08/02/18 10
 
2.2%
09/01/31 10
 
2.2%
17/02/28 9
 
2.0%
08/01/14 9
 
2.0%
13/12/31 9
 
2.0%
16/12/31 8
 
1.7%
Other values (139) 234
51.0%
2024-04-19T14:45:04.381418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 923
25.1%
1 851
23.2%
/ 788
21.5%
2 310
 
8.4%
3 234
 
6.4%
7 221
 
6.0%
8 137
 
3.7%
6 57
 
1.6%
9 55
 
1.5%
4 49
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2884
78.5%
Other Punctuation 788
 
21.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 923
32.0%
1 851
29.5%
2 310
 
10.7%
3 234
 
8.1%
7 221
 
7.7%
8 137
 
4.8%
6 57
 
2.0%
9 55
 
1.9%
4 49
 
1.7%
5 47
 
1.6%
Other Punctuation
ValueCountFrequency (%)
/ 788
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3672
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 923
25.1%
1 851
23.2%
/ 788
21.5%
2 310
 
8.4%
3 234
 
6.4%
7 221
 
6.0%
8 137
 
3.7%
6 57
 
1.6%
9 55
 
1.5%
4 49
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3672
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 923
25.1%
1 851
23.2%
/ 788
21.5%
2 310
 
8.4%
3 234
 
6.4%
7 221
 
6.0%
8 137
 
3.7%
6 57
 
1.6%
9 55
 
1.5%
4 49
 
1.3%

사용면적
Real number (ℝ)

MISSING  ZEROS 

Distinct375
Distinct (%)67.3%
Missing343
Missing (%)38.1%
Infinite0
Infinite (%)0.0%
Mean1359.4455
Minimum0
Maximum37890
Zeros67
Zeros (%)7.4%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-04-19T14:45:04.547450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q129
median215
Q31375
95-th percentile5687.04
Maximum37890
Range37890
Interquartile range (IQR)1346

Descriptive statistics

Standard deviation3057.7838
Coefficient of variation (CV)2.2492875
Kurtosis52.01692
Mean1359.4455
Median Absolute Deviation (MAD)215
Skewness5.9971674
Sum757211.15
Variance9350041.7
MonotonicityNot monotonic
2024-04-19T14:45:04.689086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 67
 
7.4%
1000.0 10
 
1.1%
20.0 6
 
0.7%
500.0 5
 
0.6%
50.0 5
 
0.6%
70.0 5
 
0.6%
18.0 5
 
0.6%
158.0 4
 
0.4%
250.0 4
 
0.4%
60.0 4
 
0.4%
Other values (365) 442
49.1%
(Missing) 343
38.1%
ValueCountFrequency (%)
0.0 67
7.4%
3.0 1
 
0.1%
4.5 1
 
0.1%
5.0 1
 
0.1%
6.6 1
 
0.1%
7.0 3
 
0.3%
7.3 1
 
0.1%
7.98 1
 
0.1%
8.0 1
 
0.1%
8.6 1
 
0.1%
ValueCountFrequency (%)
37890.0 1
0.1%
25312.0 1
0.1%
24200.21 1
0.1%
18443.7 1
0.1%
18216.0 1
0.1%
13606.51 1
0.1%
12071.4 1
0.1%
11900.0 1
0.1%
11571.0 1
0.1%
10000.0 1
0.1%

차량대수
Real number (ℝ)

MISSING  ZEROS 

Distinct94
Distinct (%)23.4%
Missing499
Missing (%)55.4%
Infinite0
Infinite (%)0.0%
Mean29.024938
Minimum0
Maximum633
Zeros146
Zeros (%)16.2%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-04-19T14:45:04.831500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median11
Q340
95-th percentile111
Maximum633
Range633
Interquartile range (IQR)40

Descriptive statistics

Standard deviation48.617172
Coefficient of variation (CV)1.6750138
Kurtosis60.05135
Mean29.024938
Median Absolute Deviation (MAD)11
Skewness5.6942821
Sum11639
Variance2363.6294
MonotonicityNot monotonic
2024-04-19T14:45:04.963147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 146
 
16.2%
6 10
 
1.1%
10 10
 
1.1%
13 7
 
0.8%
2 7
 
0.8%
27 7
 
0.8%
80 7
 
0.8%
36 7
 
0.8%
7 6
 
0.7%
35 6
 
0.7%
Other values (84) 188
 
20.9%
(Missing) 499
55.4%
ValueCountFrequency (%)
0 146
16.2%
1 1
 
0.1%
2 7
 
0.8%
4 3
 
0.3%
5 5
 
0.6%
6 10
 
1.1%
7 6
 
0.7%
8 4
 
0.4%
9 5
 
0.6%
10 10
 
1.1%
ValueCountFrequency (%)
633 1
0.1%
209 1
0.1%
206 1
0.1%
191 1
0.1%
183 1
0.1%
181 1
0.1%
149 1
0.1%
139 1
0.1%
138 2
0.2%
129 1
0.1%

처리진행코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
31
846 
1
 
30
11
 
23
32
 
1

Length

Max length2
Median length2
Mean length1.9666667
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row31
2nd row31
3rd row31
4th row31
5th row31

Common Values

ValueCountFrequency (%)
31 846
94.0%
1 30
 
3.3%
11 23
 
2.6%
32 1
 
0.1%

Length

2024-04-19T14:45:05.106012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:45:05.218976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
31 846
94.0%
1 30
 
3.3%
11 23
 
2.6%
32 1
 
0.1%

1차승인자아이디
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing899
Missing (%)99.9%
Memory size7.2 KiB
2024-04-19T14:45:05.345747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
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

Unique1 ?
Unique (%)100.0%

Sample

1st rowcupidwings
ValueCountFrequency (%)
cupidwings 1
100.0%
2024-04-19T14:45:05.596804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 2
20.0%
c 1
10.0%
u 1
10.0%
p 1
10.0%
d 1
10.0%
w 1
10.0%
n 1
10.0%
g 1
10.0%
s 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 2
20.0%
c 1
10.0%
u 1
10.0%
p 1
10.0%
d 1
10.0%
w 1
10.0%
n 1
10.0%
g 1
10.0%
s 1
10.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 2
20.0%
c 1
10.0%
u 1
10.0%
p 1
10.0%
d 1
10.0%
w 1
10.0%
n 1
10.0%
g 1
10.0%
s 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 2
20.0%
c 1
10.0%
u 1
10.0%
p 1
10.0%
d 1
10.0%
w 1
10.0%
n 1
10.0%
g 1
10.0%
s 1
10.0%

1차승인일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
<NA>
899 
20210415135618
 
1

Length

Max length14
Median length4
Mean length4.0111111
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> 899
99.9%
20210415135618 1
 
0.1%

Length

2024-04-19T14:45:05.737806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:45:05.836346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 899
99.9%
20210415135618 1
 
0.1%

최종승인자아이디
Categorical

IMBALANCE 

Distinct21
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
BASIC_INFO
794 
<NA>
 
54
00000000
 
12
eunji1103
 
6
KTS80090
 
4
Other values (16)
 
30

Length

Max length10
Median length10
Mean length9.5366667
Min length4

Unique

Unique8 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
BASIC_INFO 794
88.2%
<NA> 54
 
6.0%
00000000 12
 
1.3%
eunji1103 6
 
0.7%
KTS80090 4
 
0.4%
b1474212 4
 
0.4%
cupidwings 4
 
0.4%
anseong5 3
 
0.3%
jintopia 3
 
0.3%
drlim21-m 2
 
0.2%
Other values (11) 14
 
1.6%

Length

2024-04-19T14:45:05.947745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
basic_info 794
88.2%
na 54
 
6.0%
00000000 12
 
1.3%
eunji1103 6
 
0.7%
kts80090 4
 
0.4%
b1474212 4
 
0.4%
cupidwings 4
 
0.4%
anseong5 3
 
0.3%
jintopia 3
 
0.3%
khs4619 2
 
0.2%
Other values (11) 14
 
1.6%

최종승인일자
Real number (ℝ)

MISSING 

Distinct845
Distinct (%)99.9%
Missing54
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean2.009485 × 1013
Minimum2.0070903 × 1013
Maximum2.023031 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-04-19T14:45:06.064023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0070903 × 1013
5-th percentile2.0070903 × 1013
Q12.0070906 × 1013
median2.0071019 × 1013
Q32.0110711 × 1013
95-th percentile2.0170123 × 1013
Maximum2.023031 × 1013
Range1.5940705 × 1011
Interquartile range (IQR)3.9805034 × 1010

Descriptive statistics

Standard deviation4.2143474 × 1010
Coefficient of variation (CV)0.0020972276
Kurtosis0.51325518
Mean2.009485 × 1013
Median Absolute Deviation (MAD)1.1298556 × 108
Skewness1.4177804
Sum1.7000243 × 1016
Variance1.7760724 × 1021
MonotonicityNot monotonic
2024-04-19T14:45:06.197297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20070907143047 2
 
0.2%
20071024172441 1
 
0.1%
20071024164100 1
 
0.1%
20071024164133 1
 
0.1%
20071024164150 1
 
0.1%
20071024170335 1
 
0.1%
20071024170355 1
 
0.1%
20071024170431 1
 
0.1%
20071024170602 1
 
0.1%
20071024170637 1
 
0.1%
Other values (835) 835
92.8%
(Missing) 54
 
6.0%
ValueCountFrequency (%)
20070903102802 1
0.1%
20070903102849 1
0.1%
20070903132930 1
0.1%
20070903141344 1
0.1%
20070903142810 1
0.1%
20070903144804 1
0.1%
20070903144808 1
0.1%
20070903145010 1
0.1%
20070903145101 1
0.1%
20070903145115 1
0.1%
ValueCountFrequency (%)
20230310155457 1
0.1%
20221017102324 1
0.1%
20220818092127 1
0.1%
20220818092100 1
0.1%
20211125175648 1
0.1%
20211111113846 1
0.1%
20211111113834 1
0.1%
20211021150652 1
0.1%
20211021150615 1
0.1%
20211021150552 1
0.1%

업무코드
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
0
794 
30
106 

Length

Max length2
Median length1
Mean length1.1177778
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 794
88.2%
30 106
 
11.8%

Length

2024-04-19T14:45:06.340279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:45:06.476680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 794
88.2%
30 106
 
11.8%

비고
Categorical

IMBALANCE 

Distinct17
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
기초정보입력
794 
<NA>
88 
성남시내버스(주) 임대
 
2
 
2
차고지(유개): 건물사용료(전기세,수도세 등) 별도 납부
 
2
Other values (12)
 
12

Length

Max length41
Median length6
Mean length5.9777778
Min length1

Unique

Unique12 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
기초정보입력 794
88.2%
<NA> 88
 
9.8%
성남시내버스(주) 임대 2
 
0.2%
2
 
0.2%
차고지(유개): 건물사용료(전기세,수도세 등) 별도 납부 2
 
0.2%
성남동대형주차장 차고지 1
 
0.1%
세차장, 자가주유소 신설예정 1
 
0.1%
차고지이전 1
 
0.1%
면허대수 차량대수 안맞아서 수정합니다 빠른시일에 처리부탁합니다 감사합니다 1
 
0.1%
차고지 면적변경 1
 
0.1%
Other values (7) 7
 
0.8%

Length

2024-04-19T14:45:06.592999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기초정보입력 794
85.3%
na 88
 
9.5%
차고지 3
 
0.3%
별도 2
 
0.2%
차량대수 2
 
0.2%
납부 2
 
0.2%
사용종료 2
 
0.2%
2
 
0.2%
건물사용료(전기세,수도세 2
 
0.2%
성남시내버스(주 2
 
0.2%
Other values (30) 32
 
3.4%

2차주소
Text

MISSING 

Distinct382
Distinct (%)43.2%
Missing15
Missing (%)1.7%
Memory size7.2 KiB
2024-04-19T14:45:06.887624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length29
Mean length6.280226
Min length1

Characters and Unicode

Total characters5558
Distinct characters177
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique241 ?
Unique (%)27.2%

Sample

1st row62번지(주)연천교통
2nd row474-2
3rd row474-2
4th row474-2
5th row2-9
ValueCountFrequency (%)
합자 16
 
1.4%
경남여객 16
 
1.4%
91-3 15
 
1.3%
224-1 15
 
1.3%
호계운수 15
 
1.3%
주식회사 15
 
1.3%
공영차고지 15
 
1.3%
20-6 13
 
1.2%
668-1 13
 
1.2%
170-1 13
 
1.2%
Other values (441) 968
86.9%
2024-04-19T14:45:07.317286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 573
 
10.3%
1 538
 
9.7%
2 422
 
7.6%
3 352
 
6.3%
6 285
 
5.1%
4 282
 
5.1%
5 265
 
4.8%
255
 
4.6%
8 228
 
4.1%
7 216
 
3.9%
Other values (167) 2142
38.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2905
52.3%
Other Letter 1609
28.9%
Dash Punctuation 573
 
10.3%
Space Separator 255
 
4.6%
Other Punctuation 76
 
1.4%
Close Punctuation 66
 
1.2%
Open Punctuation 66
 
1.2%
Uppercase Letter 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
168
 
10.4%
91
 
5.7%
65
 
4.0%
59
 
3.7%
54
 
3.4%
44
 
2.7%
41
 
2.5%
38
 
2.4%
38
 
2.4%
36
 
2.2%
Other values (147) 975
60.6%
Decimal Number
ValueCountFrequency (%)
1 538
18.5%
2 422
14.5%
3 352
12.1%
6 285
9.8%
4 282
9.7%
5 265
9.1%
8 228
7.8%
7 216
7.4%
0 169
 
5.8%
9 148
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
A 2
25.0%
S 2
25.0%
M 2
25.0%
B 2
25.0%
Other Punctuation
ValueCountFrequency (%)
, 63
82.9%
. 13
 
17.1%
Dash Punctuation
ValueCountFrequency (%)
- 573
100.0%
Space Separator
ValueCountFrequency (%)
255
100.0%
Close Punctuation
ValueCountFrequency (%)
) 66
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3941
70.9%
Hangul 1609
28.9%
Latin 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
168
 
10.4%
91
 
5.7%
65
 
4.0%
59
 
3.7%
54
 
3.4%
44
 
2.7%
41
 
2.5%
38
 
2.4%
38
 
2.4%
36
 
2.2%
Other values (147) 975
60.6%
Common
ValueCountFrequency (%)
- 573
14.5%
1 538
13.7%
2 422
10.7%
3 352
8.9%
6 285
7.2%
4 282
7.2%
5 265
6.7%
255
6.5%
8 228
 
5.8%
7 216
 
5.5%
Other values (6) 525
13.3%
Latin
ValueCountFrequency (%)
A 2
25.0%
S 2
25.0%
M 2
25.0%
B 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3949
71.1%
Hangul 1605
28.9%
Compat Jamo 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 573
14.5%
1 538
13.6%
2 422
10.7%
3 352
8.9%
6 285
7.2%
4 282
7.1%
5 265
6.7%
255
6.5%
8 228
 
5.8%
7 216
 
5.5%
Other values (10) 533
13.5%
Hangul
ValueCountFrequency (%)
168
 
10.5%
91
 
5.7%
65
 
4.0%
59
 
3.7%
54
 
3.4%
44
 
2.7%
41
 
2.6%
38
 
2.4%
38
 
2.4%
36
 
2.2%
Other values (146) 971
60.5%
Compat Jamo
ValueCountFrequency (%)
4
100.0%

수정아이디
Text

MISSING 

Distinct104
Distinct (%)37.7%
Missing624
Missing (%)69.3%
Memory size7.2 KiB
2024-04-19T14:45:07.593057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length7.8188406
Min length5

Characters and Unicode

Total characters2158
Distinct characters44
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)17.4%

Sample

1st rowbus01971
2nd rowchh72018
3rd rowchh72018
4th rowpyungan2
5th rowchh72018
ValueCountFrequency (%)
pyungan2 21
 
7.6%
sncb2000 19
 
6.9%
msws7031 9
 
3.3%
daewon03 8
 
2.9%
c4ksmjss 8
 
2.9%
chh72018 7
 
2.5%
sncb03 7
 
2.5%
pyungan1 6
 
2.2%
sncbbgy 6
 
2.2%
daewon22 5
 
1.8%
Other values (94) 180
65.2%
2024-04-19T14:45:08.017761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 198
 
9.2%
n 165
 
7.6%
0 150
 
7.0%
1 139
 
6.4%
2 117
 
5.4%
u 94
 
4.4%
b 93
 
4.3%
a 91
 
4.2%
g 88
 
4.1%
y 83
 
3.8%
Other values (34) 940
43.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1407
65.2%
Decimal Number 741
34.3%
Uppercase Letter 6
 
0.3%
Other Punctuation 3
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 198
14.1%
n 165
 
11.7%
u 94
 
6.7%
b 93
 
6.6%
a 91
 
6.5%
g 88
 
6.3%
y 83
 
5.9%
c 65
 
4.6%
h 55
 
3.9%
o 53
 
3.8%
Other values (15) 422
30.0%
Decimal Number
ValueCountFrequency (%)
0 150
20.2%
1 139
18.8%
2 117
15.8%
3 80
10.8%
7 58
 
7.8%
4 49
 
6.6%
8 47
 
6.3%
5 39
 
5.3%
9 31
 
4.2%
6 31
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
D 1
16.7%
T 1
16.7%
C 1
16.7%
L 1
16.7%
S 1
16.7%
H 1
16.7%
Other Punctuation
ValueCountFrequency (%)
* 2
66.7%
. 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1413
65.5%
Common 745
34.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 198
14.0%
n 165
 
11.7%
u 94
 
6.7%
b 93
 
6.6%
a 91
 
6.4%
g 88
 
6.2%
y 83
 
5.9%
c 65
 
4.6%
h 55
 
3.9%
o 53
 
3.8%
Other values (21) 428
30.3%
Common
ValueCountFrequency (%)
0 150
20.1%
1 139
18.7%
2 117
15.7%
3 80
10.7%
7 58
 
7.8%
4 49
 
6.6%
8 47
 
6.3%
5 39
 
5.2%
9 31
 
4.2%
6 31
 
4.2%
Other values (3) 4
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2158
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 198
 
9.2%
n 165
 
7.6%
0 150
 
7.0%
1 139
 
6.4%
2 117
 
5.4%
u 94
 
4.4%
b 93
 
4.3%
a 91
 
4.2%
g 88
 
4.1%
y 83
 
3.8%
Other values (34) 940
43.6%

갱신일자
Real number (ℝ)

MISSING 

Distinct276
Distinct (%)100.0%
Missing624
Missing (%)69.3%
Infinite0
Infinite (%)0.0%
Mean2.0124988 × 1013
Minimum2.0070903 × 1013
Maximum2.023031 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-04-19T14:45:08.155105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0070903 × 1013
5-th percentile2.0070904 × 1013
Q12.0071005 × 1013
median2.0111124 × 1013
Q32.0160848 × 1013
95-th percentile2.0210648 × 1013
Maximum2.023031 × 1013
Range1.5940705 × 1011
Interquartile range (IQR)8.9842757 × 1010

Descriptive statistics

Standard deviation5.4302175 × 1010
Coefficient of variation (CV)0.0026982463
Kurtosis-1.4562501
Mean2.0124988 × 1013
Median Absolute Deviation (MAD)4.0220026 × 1010
Skewness0.33101485
Sum5.5544967 × 1015
Variance2.9487262 × 1021
MonotonicityNot monotonic
2024-04-19T14:45:08.292052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160830115340 1
 
0.1%
20171214133740 1
 
0.1%
20170306165410 1
 
0.1%
20160902142644 1
 
0.1%
20160830105315 1
 
0.1%
20160830105238 1
 
0.1%
20160829162539 1
 
0.1%
20170306165429 1
 
0.1%
20160512095628 1
 
0.1%
20170306165422 1
 
0.1%
Other values (266) 266
29.6%
(Missing) 624
69.3%
ValueCountFrequency (%)
20070903102903 1
0.1%
20070903141218 1
0.1%
20070903141354 1
0.1%
20070903144848 1
0.1%
20070903150519 1
0.1%
20070903152705 1
0.1%
20070903152732 1
0.1%
20070903153729 1
0.1%
20070903160947 1
0.1%
20070903162444 1
0.1%
ValueCountFrequency (%)
20230310155430 1
0.1%
20221014164603 1
0.1%
20220623095205 1
0.1%
20220623095142 1
0.1%
20220524191836 1
0.1%
20211111095012 1
0.1%
20211111094104 1
0.1%
20211020091048 1
0.1%
20211020091040 1
0.1%
20211020091031 1
0.1%

전화번호
Text

MISSING 

Distinct149
Distinct (%)43.3%
Missing556
Missing (%)61.8%
Memory size7.2 KiB
2024-04-19T14:45:08.521516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.369186
Min length8

Characters and Unicode

Total characters3911
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

Unique86 ?
Unique (%)25.0%

Sample

1st row031-867-3326
2nd row031-832-2256
3rd row031-832-2256
4th row031-832-2256
5th row02-387-2442
ValueCountFrequency (%)
031-747-3200 12
 
3.5%
0312933483 9
 
2.6%
031-295-7105 9
 
2.6%
0316563385 9
 
2.6%
031-668-1441 9
 
2.6%
0332543676 7
 
2.0%
032-677-0320 7
 
2.0%
673-3456 7
 
2.0%
031-912-7031 7
 
2.0%
031-964-2256 6
 
1.7%
Other values (139) 262
76.2%
2024-04-19T14:45:08.956268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 622
15.9%
0 531
13.6%
- 520
13.3%
1 492
12.6%
2 323
8.3%
7 282
7.2%
5 275
7.0%
6 265
6.8%
8 214
 
5.5%
9 195
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3391
86.7%
Dash Punctuation 520
 
13.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 622
18.3%
0 531
15.7%
1 492
14.5%
2 323
9.5%
7 282
8.3%
5 275
8.1%
6 265
7.8%
8 214
 
6.3%
9 195
 
5.8%
4 192
 
5.7%
Dash Punctuation
ValueCountFrequency (%)
- 520
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3911
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 622
15.9%
0 531
13.6%
- 520
13.3%
1 492
12.6%
2 323
8.3%
7 282
7.2%
5 275
7.0%
6 265
6.8%
8 214
 
5.5%
9 195
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3911
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 622
15.9%
0 531
13.6%
- 520
13.3%
1 492
12.6%
2 323
8.3%
7 282
7.2%
5 275
7.0%
6 265
6.8%
8 214
 
5.5%
9 195
 
5.0%

팩스번호
Text

MISSING 

Distinct118
Distinct (%)42.9%
Missing625
Missing (%)69.4%
Memory size7.2 KiB
2024-04-19T14:45:09.173287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.254545
Min length1

Characters and Unicode

Total characters3095
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

Unique68 ?
Unique (%)24.7%

Sample

1st row031-867-3329
2nd row031-867-3329
3rd row031-867-3329
4th row031-867-3329
5th row02-382-5103
ValueCountFrequency (%)
031-747-5758 12
 
4.4%
031-668-0183 11
 
4.0%
031-295-7104 10
 
3.6%
0316563381 9
 
3.3%
676-1554 9
 
3.3%
0312933486 9
 
3.3%
031-867-3329 8
 
2.9%
031-912-7592 7
 
2.5%
032-677-0266 7
 
2.5%
031-958-6712 7
 
2.5%
Other values (108) 186
67.6%
2024-04-19T14:45:09.505129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 461
14.9%
- 404
13.1%
1 382
12.3%
0 373
12.1%
7 253
8.2%
6 241
7.8%
5 229
7.4%
2 226
7.3%
8 213
6.9%
4 158
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2691
86.9%
Dash Punctuation 404
 
13.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 461
17.1%
1 382
14.2%
0 373
13.9%
7 253
9.4%
6 241
9.0%
5 229
8.5%
2 226
8.4%
8 213
7.9%
4 158
 
5.9%
9 155
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 404
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3095
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 461
14.9%
- 404
13.1%
1 382
12.3%
0 373
12.1%
7 253
8.2%
6 241
7.8%
5 229
7.4%
2 226
7.3%
8 213
6.9%
4 158
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3095
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 461
14.9%
- 404
13.1%
1 382
12.3%
0 373
12.1%
7 253
8.2%
6 241
7.8%
5 229
7.4%
2 226
7.3%
8 213
6.9%
4 158
 
5.1%

시설코드명
Categorical

Distinct10
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
차고지(무개)
253 
차고지(유개)
186 
기타
130 
사무실
94 
휴게실
62 
Other values (5)
175 

Length

Max length7
Median length4
Mean length4.7911111
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row사무실
3rd row휴게실
4th row기타
5th row차고지(무개)

Common Values

ValueCountFrequency (%)
차고지(무개) 253
28.1%
차고지(유개) 186
20.7%
기타 130
14.4%
사무실 94
 
10.4%
휴게실 62
 
6.9%
숙소 49
 
5.4%
교육시설 49
 
5.4%
세차장 39
 
4.3%
검사장 24
 
2.7%
욕실 14
 
1.6%

Length

2024-04-19T14:45:09.645517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:45:09.763510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
차고지(무개 253
28.1%
차고지(유개 186
20.7%
기타 130
14.4%
사무실 94
 
10.4%
휴게실 62
 
6.9%
숙소 49
 
5.4%
교육시설 49
 
5.4%
세차장 39
 
4.3%
검사장 24
 
2.7%
욕실 14
 
1.6%

신고인가구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
승인
846 
작성중
 
30
신청완료
 
23
불허
 
1

Length

Max length4
Median length2
Mean length2.0844444
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
승인 846
94.0%
작성중 30
 
3.3%
신청완료 23
 
2.6%
불허 1
 
0.1%

Length

2024-04-19T14:45:09.910210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:45:10.023540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
승인 846
94.0%
작성중 30
 
3.3%
신청완료 23
 
2.6%
불허 1
 
0.1%
Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
임대
458 
법인소유
222 
대표자(개인)소유
188 
기타(공영)
 
32

Length

Max length9
Median length2
Mean length4.0977778
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
임대 458
50.9%
법인소유 222
24.7%
대표자(개인)소유 188
20.9%
기타(공영) 32
 
3.6%

Length

2024-04-19T14:45:10.132173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:45:10.236875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임대 458
50.9%
법인소유 222
24.7%
대표자(개인)소유 188
20.9%
기타(공영 32
 
3.6%

업무코드명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
기초정보입력
793 
차고지 및 부대시설 변경
105 
 
1
차고지 및 부대시설
 
1

Length

Max length13
Median length6
Mean length6.8155556
Min length1

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
기초정보입력 793
88.1%
차고지 및 부대시설 변경 105
 
11.7%
1
 
0.1%
차고지 및 부대시설 1
 
0.1%

Length

2024-04-19T14:45:10.353041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:45:10.450261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기초정보입력 793
65.2%
차고지 106
 
8.7%
106
 
8.7%
부대시설 106
 
8.7%
변경 105
 
8.6%
1
 
0.1%
Distinct7
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
<NA>
471 
기타
145 
부설주차장
101 
노외주차장
62 
거주지주차장
58 
Other values (2)
63 

Length

Max length6
Median length4
Mean length4.0577778
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 471
52.3%
기타 145
 
16.1%
부설주차장 101
 
11.2%
노외주차장 62
 
6.9%
거주지주차장 58
 
6.4%
공영차고지 41
 
4.6%
여객터미널 22
 
2.4%

Length

2024-04-19T14:45:10.894499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:45:11.014038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 471
52.3%
기타 145
 
16.1%
부설주차장 101
 
11.2%
노외주차장 62
 
6.9%
거주지주차장 58
 
6.4%
공영차고지 41
 
4.6%
여객터미널 22
 
2.4%

Sample

시설아이디이력아이디업체아이디영업소아이디시설코드전체규모차고지시설유형우편번호기관코드수용가능수등록아이디등록일자시설명1차주소사용구분신고인가구분소유구분부대시설상세명계약시작일계약종료일사용면적차량대수처리진행코드1차승인자아이디1차승인일자최종승인자아이디최종승인일자업무코드비고2차주소수정아이디갱신일자전화번호팩스번호시설코드명신고인가구분명처리진행코드명업무코드명부대시설상세내역
01006310000000004103500<NA>10<NA><NA>4831104125000000<NA>ycbusi0520070903162428기사식당경기 동두천시 하봉암동N<NA>L<NA>05/06/0108/06/0167.0<NA>31<NA><NA>BASIC_INFO200709031624280기초정보입력62번지(주)연천교통<NA><NA>031-867-3326031-867-3329기타승인임대기초정보입력<NA>
11006410000000004103500<NA>3<NA><NA>4869004180000000<NA>ycbusi0520070903162648전곡영업소사무실경기 연천군 전곡읍N<NA>L<NA>05/03/0108/03/0143.0<NA>31<NA><NA>BASIC_INFO200709031626480기초정보입력474-2<NA><NA>031-832-2256031-867-3329사무실승인임대기초정보입력<NA>
21006510000000004103500<NA>9<NA><NA>4869004180000000<NA>ycbusi0520070903162915전곡영업소기사휴게실경기 연천군 전곡읍N<NA>L<NA>05/03/0108/03/0177.0<NA>31<NA><NA>BASIC_INFO200709031629150기초정보입력474-2<NA><NA>031-832-2256031-867-3329휴게실승인임대기초정보입력<NA>
31006610000000004103500<NA>10<NA><NA>4869004180000000<NA>ycbusi0520070903163035전곡영업소식당경기 연천군 전곡읍N<NA>L<NA>05/03/0108/03/0125.0<NA>31<NA><NA>BASIC_INFO200709031630350기초정보입력474-2<NA><NA>031-832-2256031-867-3329기타승인임대기초정보입력<NA>
41006710000000004103400<NA>2<NA>11228374148000000<NA>bus0197120070903163915불광동시외버스 터미널서울 은평구 대조동Y<NA>L서울 유출입 차량을 위하여 임대07/08/0108/07/31991.02331<NA><NA>BASIC_INFO200709031639150기초정보입력2-9<NA><NA>02-387-244202-382-5103차고지(무개)승인임대기초정보입력여객터미널
51006810000000004103400<NA>1<NA>14139134148000000<NA>bus0197120070903164503적성영업소경기 파주시 적성면 마지리Y<NA>L적성영업소 차고지07/03/0108/02/292842.02431<NA><NA>BASIC_INFO200709031645030기초정보입력352-2<NA><NA>031-959-1713031-959-1135차고지(유개)승인임대기초정보입력여객터미널
61006910000000004103400<NA>2<NA>44138724148000000<NA>bus0197120070903165355본사 주차장경기 파주시 법원읍 갈곡리Y<NA>L신일여객 본사 주차장 무상임대, 정비실, 세차장05/05/0110/04/301337.02331<NA><NA>BASIC_INFO200709031653550기초정보입력352-2bus0197120070904102838031-958-0713031-958-6712차고지(무개)승인임대기초정보입력거주지주차장
71020210000000004104000<NA>420.0<NA>4831004125000000<NA>pyungan120070906115044동두천 기숙사경기 동두천시 상봉암동N<NA>J<NA><NA><NA><NA><NA>31<NA><NA>BASIC_INFO200709061150440기초정보입력69-7<NA><NA><NA><NA>숙소승인법인소유기초정보입력<NA>
81020310000000004104000<NA>912.0<NA>4831004125000000<NA>pyungan120070906115140동두천 휴식/대기실경기 동두천시 상봉암동N<NA>J<NA><NA><NA><NA><NA>31<NA><NA>BASIC_INFO200709061151400기초정보입력69-7<NA><NA><NA><NA>휴게실승인법인소유기초정보입력<NA>
91020410000000004104000<NA>10120.0<NA>4831004125000000<NA>pyungan120070906115230동두천 기타시설경기 동두천시 상봉암동N<NA>J<NA><NA><NA><NA><NA>31<NA><NA>BASIC_INFO200709061152300기초정보입력69-7<NA><NA><NA><NA>기타승인법인소유기초정보입력<NA>
시설아이디이력아이디업체아이디영업소아이디시설코드전체규모차고지시설유형우편번호기관코드수용가능수등록아이디등록일자시설명1차주소사용구분신고인가구분소유구분부대시설상세명계약시작일계약종료일사용면적차량대수처리진행코드1차승인자아이디1차승인일자최종승인자아이디최종승인일자업무코드비고2차주소수정아이디갱신일자전화번호팩스번호시설코드명신고인가구분명처리진행코드명업무코드명부대시설상세내역
8902066120000702644110400<NA>13158.06109444128000000794110400020210608145717서울여객 앞골차고지경기 파주시 아동동 168-54<NA>1L사무실2021011220220111<NA>911<NA><NA><NA><NA>30차고지(유개): 건물사용료(전기세,수도세 등) 별도 납부(앞골) 서울여객 앞골차고지411040002021060815301902-357-049002-761-0495차고지(유개)신청완료임대차고지 및 부대시설 변경기타
8912072120000709344149400<NA>110000.0185074100000000100daezi2120210614191443TEST 차고지서울 금천구 가산동 371-28<NA>1CTEST202106012021063010000.0201<NA><NA><NA><NA>30<NA>ㄱㄱㄱㄱ<NA><NA>0001111000000111000차고지(유개)작성중대표자(개인)소유차고지 및 부대시설 변경여객터미널
8922076020000711104145500<NA>11800.0311426416300000017yoyokg2120210616210628주차장경기 양주시 은현면 은현로 401-15<NA>1L사무실,휴계실,교육실2020120120201130400.0601<NA><NA><NA><NA>30<NA>0<NA><NA>0318642374031-858-9828차고지(유개)작성중임대차고지 및 부대시설 변경노외주차장
8931068520000803814102600<NA>27314.024613604113000000191sncbbgy20211019093628사송동 공영차고지 (사송로 41)경기도 성남시 수정구 사송동<NA>2L대형:182대중형:9대20190115202401140.019131<NA><NA>eunji11032021102115065230<NA>279번지 사송동공영차고지sncbbgy20211020091048031-747-3200031-747-5758차고지(무개)승인임대차고지 및 부대시설 변경공영차고지
8941029820000803824102600<NA>22816.03462120411300000083sncbbgy20211019094140상대원(하) 차고지 (순환로 233)경기 성남시 중원구 상대원동<NA>2L대형:60대중형:23대20201201203012310.08331<NA><NA>eunji11032021102115061530<NA>135-1번지sncbbgy20211020091040031-747-3200031-747-5758차고지(무개)승인임대차고지 및 부대시설 변경노외주차장
8951068120000803904102600<NA>2764.03461802411300000020sncbbgy20211019100908산성동 차고지 (산성동 7)경기도 성남시 수정구 산성동<NA>2L대형:20대20210611202406100.02031<NA><NA>eunji11032021102115045130<NA>7번지sncbbgy20211020091023031-747-3200031-747-5758차고지(무개)승인임대차고지 및 부대시설 변경노외주차장
8962084020001199564155500<NA>22234.0311954410000000030daehwa20220609103629주차 및 정비경기 구리시 아차산로 387-13<NA>1J차고지 및 정비소19880929198809292234.0291<NA><NA><NA><NA>30<NA>(교문동)<NA><NA>031-562-2131031-562-0071차고지(무개)작성중법인소유차고지 및 부대시설 변경노외주차장
8972088020001199734155500<NA>22234.0611954410000000032daehwa20221012150002(주)대화관광 자동차관련시설경기 구리시 아차산로 387-13<NA>2J차고지, 정비, 식당, 휴게실, 회의실 등19911016199110162234.02731<NA><NA>mjhi02172022101710232430<NA>(교문동)daehwa20221014164603031-562-1237031-563-0071차고지(무개)승인법인소유차고지 및 부대시설 변경기타
8982096020001510704102700<NA>23709.0617704411100000027swws348320230601110514차고지경기 평택시 서탄면 수월암리 960-1<NA>1L배차실, 기사휴게실, 식당, 자가용주차장20230601202806013709.0271<NA><NA><NA><NA>30<NA>삼경.성우운수<NA><NA>031-293-3483031-668-0183차고지(무개)작성중임대차고지 및 부대시설 변경기타
8991020520000147124101800<NA>23611.94456360415500000090chh7201820200219154654자동차관련시설경기 안성시 당왕동<NA>1J1층(사무실82, 중역실15, 기타:67(샤워장,화장실) 2층(휴게실21.33, 교양실40.56, 기타 79.46) 자동차관련시설:201.30계:506.6519880730000000000.01011<NA><NA><NA><NA>30<NA>357-1,357-4<NA><NA>673-3456676-1554차고지(무개)작성중법인소유차고지 및 부대시설 변경거주지주차장