Overview

Dataset statistics

Number of variables25
Number of observations8291
Missing cells40589
Missing cells (%)19.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 MiB
Average record size in memory221.0 B

Variable types

Numeric11
Unsupported4
Text3
Categorical6
Boolean1

Dataset

Description교차로코드,입력일자,교차로명칭,유형코드,연동교차로코드,구코드 (공통);,지번,구경찰서 (공통);,신경찰서 (공통);,작업구분 (공통);,표출구분 (공통);,고객번호,계약종별,계량기번호,도로구분 (공통);,관할사업소 (공통);,교차로관리번호,공간데이터,신규정규화ID,이력ID,동코드 (공통);,공사형태 (공통);,지도표출구분,X좌표,Y좌표
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15534/S/1/datasetView.do

Alerts

작업구분 (공통); has constant value ""Constant
표출구분 (공통); is highly imbalanced (80.3%)Imbalance
계약종별 is highly imbalanced (99.8%)Imbalance
계량기번호 is highly imbalanced (99.8%)Imbalance
지도표출구분 is highly imbalanced (93.6%)Imbalance
입력일자 has 8291 (100.0%) missing valuesMissing
연동교차로코드 has 1911 (23.0%) missing valuesMissing
지번 has 840 (10.1%) missing valuesMissing
구경찰서 (공통); has 246 (3.0%) missing valuesMissing
고객번호 has 8291 (100.0%) missing valuesMissing
공간데이터 has 8291 (100.0%) missing valuesMissing
신규정규화ID has 2813 (33.9%) missing valuesMissing
공사형태 (공통); has 8291 (100.0%) missing valuesMissing
지도표출구분 has 1152 (13.9%) missing valuesMissing
X좌표 has 188 (2.3%) missing valuesMissing
Y좌표 has 188 (2.3%) missing valuesMissing
교차로코드 has unique valuesUnique
교차로관리번호 has unique valuesUnique
이력ID has unique valuesUnique
입력일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
고객번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공간데이터 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공사형태 (공통); is an unsupported type, check if it needs cleaning or further analysisUnsupported
연동교차로코드 has 4473 (54.0%) zerosZeros

Reproduction

Analysis started2024-05-04 05:07:49.057082
Analysis finished2024-05-04 05:07:51.592473
Duration2.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

교차로코드
Real number (ℝ)

UNIQUE 

Distinct8291
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4517.6392
Minimum4
Maximum8905
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size73.0 KiB
2024-05-04T05:07:51.849336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile499.5
Q12275.5
median4519
Q36799.5
95-th percentile8490.5
Maximum8905
Range8901
Interquartile range (IQR)4524

Descriptive statistics

Standard deviation2580.0238
Coefficient of variation (CV)0.57110001
Kurtosis-1.2219763
Mean4517.6392
Median Absolute Deviation (MAD)2261
Skewness-0.0085058806
Sum37455747
Variance6656522.8
MonotonicityNot monotonic
2024-05-04T05:07:52.347966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1302 1
 
< 0.1%
6290 1
 
< 0.1%
6319 1
 
< 0.1%
6318 1
 
< 0.1%
6317 1
 
< 0.1%
6315 1
 
< 0.1%
6314 1
 
< 0.1%
6313 1
 
< 0.1%
6312 1
 
< 0.1%
6311 1
 
< 0.1%
Other values (8281) 8281
99.9%
ValueCountFrequency (%)
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
32 1
< 0.1%
33 1
< 0.1%
34 1
< 0.1%
35 1
< 0.1%
36 1
< 0.1%
37 1
< 0.1%
38 1
< 0.1%
ValueCountFrequency (%)
8905 1
< 0.1%
8904 1
< 0.1%
8903 1
< 0.1%
8902 1
< 0.1%
8901 1
< 0.1%
8900 1
< 0.1%
8899 1
< 0.1%
8898 1
< 0.1%
8897 1
< 0.1%
8896 1
< 0.1%

입력일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8291
Missing (%)100.0%
Memory size73.0 KiB

교차로명칭
Text

Distinct8243
Distinct (%)99.5%
Missing3
Missing (%)< 0.1%
Memory size64.9 KiB
2024-05-04T05:07:52.981713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length7.6167954
Min length2

Characters and Unicode

Total characters63128
Distinct characters647
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8198 ?
Unique (%)98.9%

Sample

1st row삼성산성지
2nd row난향삼거리(연등)
3rd row대우당약국
4th row수동물병원(연등)2
5th row삼성동자치회관
ValueCountFrequency (%)
송파상운종점 4
 
< 0.1%
교차로 3
 
< 0.1%
가락시장 3
 
< 0.1%
올림픽공원r(경보 2
 
< 0.1%
등촌역(연등)1 2
 
< 0.1%
srt수서역 2
 
< 0.1%
마곡센트럴타워 2
 
< 0.1%
전파연구소 2
 
< 0.1%
구룡사거리 2
 
< 0.1%
삼각산초교 2
 
< 0.1%
Other values (8250) 8290
99.7%
2024-05-04T05:07:54.268396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 3228
 
5.1%
) 3228
 
5.1%
등 2195
 
3.5%
연 2175
 
3.4%
교 1714
 
2.7%
동 1473
 
2.3%
경 1325
 
2.1%
보 1258
 
2.0%
1 1159
 
1.8%
파 1016
 
1.6%
Other values (637) 44357
70.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52784
83.6%
Open Punctuation 3228
 
5.1%
Close Punctuation 3228
 
5.1%
Decimal Number 3146
 
5.0%
Uppercase Letter 586
 
0.9%
Other Punctuation 70
 
0.1%
Lowercase Letter 39
 
0.1%
Space Separator 26
 
< 0.1%
Dash Punctuation 19
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
등 2195
 
4.2%
연 2175
 
4.1%
교 1714
 
3.2%
동 1473
 
2.8%
경 1325
 
2.5%
보 1258
 
2.4%
파 1016
 
1.9%
아 950
 
1.8%
트 939
 
1.8%
초 859
 
1.6%
Other values (588) 38880
73.7%
Uppercase Letter
ValueCountFrequency (%)
C 84
14.3%
S 74
12.6%
K 71
12.1%
I 52
8.9%
T 40
 
6.8%
G 37
 
6.3%
D 31
 
5.3%
M 31
 
5.3%
B 25
 
4.3%
L 24
 
4.1%
Other values (13) 117
20.0%
Decimal Number
ValueCountFrequency (%)
1 1159
36.8%
2 728
23.1%
3 315
 
10.0%
0 310
 
9.9%
4 159
 
5.1%
9 116
 
3.7%
5 114
 
3.6%
6 101
 
3.2%
7 84
 
2.7%
8 60
 
1.9%
Lowercase Letter
ValueCountFrequency (%)
e 19
48.7%
t 8
20.5%
s 6
 
15.4%
l 2
 
5.1%
o 2
 
5.1%
i 2
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 50
71.4%
& 8
 
11.4%
# 7
 
10.0%
? 4
 
5.7%
？ 1
 
1.4%
Open Punctuation
ValueCountFrequency (%)
( 3228
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3228
100.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52784
83.6%
Common 9719
 
15.4%
Latin 625
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
등 2195
 
4.2%
연 2175
 
4.1%
교 1714
 
3.2%
동 1473
 
2.8%
경 1325
 
2.5%
보 1258
 
2.4%
파 1016
 
1.9%
아 950
 
1.8%
트 939
 
1.8%
초 859
 
1.6%
Other values (588) 38880
73.7%
Latin
ValueCountFrequency (%)
C 84
13.4%
S 74
11.8%
K 71
11.4%
I 52
 
8.3%
T 40
 
6.4%
G 37
 
5.9%
D 31
 
5.0%
M 31
 
5.0%
B 25
 
4.0%
L 24
 
3.8%
Other values (19) 156
25.0%
Common
ValueCountFrequency (%)
( 3228
33.2%
) 3228
33.2%
1 1159
 
11.9%
2 728
 
7.5%
3 315
 
3.2%
0 310
 
3.2%
4 159
 
1.6%
9 116
 
1.2%
5 114
 
1.2%
6 101
 
1.0%
Other values (10) 261
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52784
83.6%
ASCII 10343
 
16.4%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 3228
31.2%
) 3228
31.2%
1 1159
 
11.2%
2 728
 
7.0%
3 315
 
3.0%
0 310
 
3.0%
4 159
 
1.5%
9 116
 
1.1%
5 114
 
1.1%
6 101
 
1.0%
Other values (38) 885
 
8.6%
Hangul
ValueCountFrequency (%)
등 2195
 
4.2%
연 2175
 
4.1%
교 1714
 
3.2%
동 1473
 
2.8%
경 1325
 
2.5%
보 1258
 
2.4%
파 1016
 
1.9%
아 950
 
1.8%
트 939
 
1.8%
초 859
 
1.6%
Other values (588) 38880
73.7%
None
ValueCountFrequency (%)
？ 1
100.0%

유형코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size64.9 KiB
1
4697 
3
1812 
2
1759 
4
 
22
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row2
3rd row3
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 4697
56.7%
3 1812
 
21.9%
2 1759
 
21.2%
4 22
 
0.3%
5 1
 
< 0.1%

Length

2024-05-04T05:07:54.862632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T05:07:55.266723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4697
56.7%
3 1812
 
21.9%
2 1759
 
21.2%
4 22
 
0.3%
5 1
 
< 0.1%

연동교차로코드
Real number (ℝ)

MISSING  ZEROS 

Distinct1501
Distinct (%)23.5%
Missing1911
Missing (%)23.0%
Infinite0
Infinite (%)0.0%
Mean761.37194
Minimum0
Maximum8337
Zeros4473
Zeros (%)54.0%
Negative0
Negative (%)0.0%
Memory size73.0 KiB
2024-05-04T05:07:55.964540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3565.25
95-th percentile4226
Maximum8337
Range8337
Interquartile range (IQR)565.25

Descriptive statistics

Standard deviation1549.0328
Coefficient of variation (CV)2.0345284
Kurtosis4.5352092
Mean761.37194
Median Absolute Deviation (MAD)0
Skewness2.2442402
Sum4857553
Variance2399502.8
MonotonicityNot monotonic
2024-05-04T05:07:56.411647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4473
54.0%
367 5
 
0.1%
5 4
 
< 0.1%
2258 4
 
< 0.1%
2380 3
 
< 0.1%
2359 3
 
< 0.1%
1109 3
 
< 0.1%
3547 3
 
< 0.1%
563 3
 
< 0.1%
3979 3
 
< 0.1%
Other values (1491) 1876
22.6%
(Missing) 1911
23.0%
ValueCountFrequency (%)
0 4473
54.0%
5 4
 
< 0.1%
28 1
 
< 0.1%
32 1
 
< 0.1%
33 1
 
< 0.1%
35 1
 
< 0.1%
36 1
 
< 0.1%
37 1
 
< 0.1%
39 1
 
< 0.1%
40 2
 
< 0.1%
ValueCountFrequency (%)
8337 1
< 0.1%
8220 1
< 0.1%
8151 1
< 0.1%
8137 1
< 0.1%
8132 1
< 0.1%
8128 1
< 0.1%
8124 1
< 0.1%
8118 1
< 0.1%
8081 1
< 0.1%
8076 1
< 0.1%

구코드 (공통);
Real number (ℝ)

Distinct25
Distinct (%)0.3%
Missing16
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean452.43142
Minimum110
Maximum740
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size73.0 KiB
2024-05-04T05:07:56.984043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110
5-th percentile140
Q1290
median470
Q3620
95-th percentile710
Maximum740
Range630
Interquartile range (IQR)330

Descriptive statistics

Standard deviation186.27744
Coefficient of variation (CV)0.41172525
Kurtosis-1.1828271
Mean452.43142
Median Absolute Deviation (MAD)170
Skewness-0.12703025
Sum3743870
Variance34699.284
MonotonicityNot monotonic
2024-05-04T05:07:57.416532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
710 541
 
6.5%
680 502
 
6.1%
560 471
 
5.7%
650 462
 
5.6%
500 462
 
5.6%
740 413
 
5.0%
350 397
 
4.8%
470 390
 
4.7%
530 355
 
4.3%
440 351
 
4.2%
Other values (15) 3931
47.4%
ValueCountFrequency (%)
110 245
3.0%
140 210
2.5%
170 258
3.1%
200 231
2.8%
210 245
3.0%
230 301
3.6%
260 312
3.8%
290 347
4.2%
300 229
2.8%
320 234
2.8%
ValueCountFrequency (%)
740 413
5.0%
710 541
6.5%
680 502
6.1%
650 462
5.6%
620 277
3.3%
590 237
2.9%
560 471
5.7%
540 219
2.6%
530 355
4.3%
500 462
5.6%

지번
Text

MISSING 

Distinct6030
Distinct (%)80.9%
Missing840
Missing (%)10.1%
Memory size64.9 KiB
2024-05-04T05:07:58.412327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.923366
Min length2

Characters and Unicode

Total characters44135
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5102 ?
Unique (%)68.5%

Sample

1st row321-12 천
2nd row산87-11도
3rd row1000-118도
4th row442-185도
5th row310-5도
ValueCountFrequency (%)
도 654
 
7.2%
대 561
 
6.2%
공 82
 
0.9%
학 75
 
0.8%
임 74
 
0.8%
천 41
 
0.4%
전 26
 
0.3%
철 25
 
0.3%
잡 22
 
0.2%
산 18
 
0.2%
Other values (5986) 7537
82.7%
2024-05-04T05:08:00.284719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5852
13.3%
- 5601
12.7%
2 3775
 
8.6%
3 3273
 
7.4%
도 3237
 
7.3%
4 2795
 
6.3%
6 2499
 
5.7%
5 2410
 
5.5%
대 2384
 
5.4%
7 2200
 
5.0%
Other values (26) 10109
22.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29026
65.8%
Other Letter 7844
 
17.8%
Dash Punctuation 5601
 
12.7%
Space Separator 1664
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 3237
41.3%
대 2384
30.4%
산 398
 
5.1%
임 384
 
4.9%
천 382
 
4.9%
학 215
 
2.7%
공 146
 
1.9%
답 135
 
1.7%
구 111
 
1.4%
전 109
 
1.4%
Other values (14) 343
 
4.4%
Decimal Number
ValueCountFrequency (%)
1 5852
20.2%
2 3775
13.0%
3 3273
11.3%
4 2795
9.6%
6 2499
8.6%
5 2410
8.3%
7 2200
 
7.6%
0 2109
 
7.3%
8 2061
 
7.1%
9 2052
 
7.1%
Dash Punctuation
ValueCountFrequency (%)
- 5601
100.0%
Space Separator
ValueCountFrequency (%)
1664
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36291
82.2%
Hangul 7844
 
17.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 3237
41.3%
대 2384
30.4%
산 398
 
5.1%
임 384
 
4.9%
천 382
 
4.9%
학 215
 
2.7%
공 146
 
1.9%
답 135
 
1.7%
구 111
 
1.4%
전 109
 
1.4%
Other values (14) 343
 
4.4%
Common
ValueCountFrequency (%)
1 5852
16.1%
- 5601
15.4%
2 3775
10.4%
3 3273
9.0%
4 2795
7.7%
6 2499
6.9%
5 2410
6.6%
7 2200
 
6.1%
0 2109
 
5.8%
8 2061
 
5.7%
Other values (2) 3716
10.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36291
82.2%
Hangul 7844
 
17.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5852
16.1%
- 5601
15.4%
2 3775
10.4%
3 3273
9.0%
4 2795
7.7%
6 2499
6.9%
5 2410
6.6%
7 2200
 
6.1%
0 2109
 
5.8%
8 2061
 
5.7%
Other values (2) 3716
10.2%
Hangul
ValueCountFrequency (%)
도 3237
41.3%
대 2384
30.4%
산 398
 
5.1%
임 384
 
4.9%
천 382
 
4.9%
학 215
 
2.7%
공 146
 
1.9%
답 135
 
1.7%
구 111
 
1.4%
전 109
 
1.4%
Other values (14) 343
 
4.4%

구경찰서 (공통);
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)0.4%
Missing246
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean272.20758
Minimum110
Maximum410
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size73.0 KiB
2024-05-04T05:08:00.828876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110
5-th percentile130
Q1200
median290
Q3350
95-th percentile400
Maximum410
Range300
Interquartile range (IQR)150

Descriptive statistics

Standard deviation86.601961
Coefficient of variation (CV)0.31814676
Kurtosis-1.1663282
Mean272.20758
Median Absolute Deviation (MAD)70
Skewness-0.20796542
Sum2189910
Variance7499.8997
MonotonicityNot monotonic
2024-05-04T05:08:01.229227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
360 519
 
6.3%
300 455
 
5.5%
170 449
 
5.4%
310 409
 
4.9%
350 393
 
4.7%
370 386
 
4.7%
210 356
 
4.3%
330 351
 
4.2%
340 325
 
3.9%
410 315
 
3.8%
Other values (21) 4087
49.3%
ValueCountFrequency (%)
110 224
2.7%
120 154
 
1.9%
130 76
 
0.9%
140 266
3.2%
150 146
 
1.8%
160 253
3.1%
170 449
5.4%
180 229
2.8%
190 202
2.4%
200 226
2.7%
ValueCountFrequency (%)
410 315
3.8%
400 241
2.9%
390 161
 
1.9%
380 122
 
1.5%
370 386
4.7%
360 519
6.3%
350 393
4.7%
340 325
3.9%
330 351
4.2%
320 143
 
1.7%

신경찰서 (공통);
Real number (ℝ)

Distinct31
Distinct (%)0.4%
Missing17
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean271.25937
Minimum110
Maximum410
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size73.0 KiB
2024-05-04T05:08:01.608476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110
5-th percentile130
Q1200
median280
Q3350
95-th percentile400
Maximum410
Range300
Interquartile range (IQR)150

Descriptive statistics

Standard deviation85.608916
Coefficient of variation (CV)0.31559801
Kurtosis-1.1381443
Mean271.25937
Median Absolute Deviation (MAD)70
Skewness-0.17996847
Sum2244400
Variance7328.8864
MonotonicityNot monotonic
2024-05-04T05:08:02.146466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
360 530
 
6.4%
170 461
 
5.6%
300 456
 
5.5%
310 408
 
4.9%
370 400
 
4.8%
350 392
 
4.7%
210 356
 
4.3%
330 349
 
4.2%
340 322
 
3.9%
410 315
 
3.8%
Other values (21) 4285
51.7%
ValueCountFrequency (%)
110 237
2.9%
120 159
 
1.9%
130 79
 
1.0%
140 264
3.2%
150 86
 
1.0%
160 253
3.1%
170 461
5.6%
180 226
2.7%
190 203
2.4%
200 294
3.5%
ValueCountFrequency (%)
410 315
3.8%
400 234
2.8%
390 160
 
1.9%
380 117
 
1.4%
370 400
4.8%
360 530
6.4%
350 392
4.7%
340 322
3.9%
330 349
4.2%
320 141
 
1.7%

작업구분 (공통);
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size64.9 KiB
1
8291 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 8291
100.0%

Length

2024-05-04T05:08:02.563077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T05:08:02.973793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 8291
100.0%

표출구분 (공통);
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size64.9 KiB
2
8038 
1
 
253

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 8038
96.9%
1 253
 
3.1%

Length

2024-05-04T05:08:03.328534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T05:08:03.687365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8038
96.9%
1 253
 
3.1%

고객번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8291
Missing (%)100.0%
Memory size73.0 KiB

계약종별
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size64.9 KiB
<NA>
8289 
2
 
1
1
 
1

Length

Max length4
Median length4
Mean length3.9992763
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8289
> 99.9%
2 1
 
< 0.1%
1 1
 
< 0.1%

Length

2024-05-04T05:08:04.050523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T05:08:04.511386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8289
> 99.9%
2 1
 
< 0.1%
1 1
 
< 0.1%

계량기번호
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size64.9 KiB
<NA>
8289 
3
 
1
1
 
1

Length

Max length4
Median length4
Mean length3.9992763
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8289
> 99.9%
3 1
 
< 0.1%
1 1
 
< 0.1%

Length

2024-05-04T05:08:04.906844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T05:08:05.283899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8289
> 99.9%
3 1
 
< 0.1%
1 1
 
< 0.1%

도로구분 (공통);
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size64.9 KiB
1
5216 
2
3000 
<NA>
 
75

Length

Max length4
Median length1
Mean length1.0271379
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 5216
62.9%
2 3000
36.2%
<NA> 75
 
0.9%

Length

2024-05-04T05:08:05.623365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T05:08:06.111494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 5216
62.9%
2 3000
36.2%
na 75
 
0.9%

관할사업소 (공통);
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing46
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean106.38617
Minimum104
Maximum109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size73.0 KiB
2024-05-04T05:08:06.563954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum104
5-th percentile104
Q1105
median106
Q3108
95-th percentile109
Maximum109
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.6691548
Coefficient of variation (CV)0.015689584
Kurtosis-1.2103411
Mean106.38617
Median Absolute Deviation (MAD)1
Skewness0.037512106
Sum877154
Variance2.7860776
MonotonicityNot monotonic
2024-05-04T05:08:07.065617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
104 1522
18.4%
106 1504
18.1%
107 1450
17.5%
108 1401
16.9%
105 1282
15.5%
109 1086
13.1%
(Missing) 46
 
0.6%
ValueCountFrequency (%)
104 1522
18.4%
105 1282
15.5%
106 1504
18.1%
107 1450
17.5%
108 1401
16.9%
109 1086
13.1%
ValueCountFrequency (%)
109 1086
13.1%
108 1401
16.9%
107 1450
17.5%
106 1504
18.1%
105 1282
15.5%
104 1522
18.4%

교차로관리번호
Text

UNIQUE 

Distinct8291
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size64.9 KiB
2024-05-04T05:08:07.680868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters107783
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

Unique8291 ?
Unique (%)100.0%

Sample

1st row82-0000000976
2nd row82-0000000201
3rd row82-0000001561
4th row82-0000003649
5th row82-0000004279
ValueCountFrequency (%)
82-0000000976 1
 
< 0.1%
82-0000005803 1
 
< 0.1%
82-0000005829 1
 
< 0.1%
82-0000005827 1
 
< 0.1%
82-0000005826 1
 
< 0.1%
82-0000005825 1
 
< 0.1%
82-0000005824 1
 
< 0.1%
82-0000005823 1
 
< 0.1%
82-0000005822 1
 
< 0.1%
82-0000005821 1
 
< 0.1%
Other values (8281) 8281
99.9%
2024-05-04T05:08:08.648808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 53232
49.4%
2 11805
 
11.0%
8 11288
 
10.5%
- 8291
 
7.7%
1 3515
 
3.3%
5 3496
 
3.2%
4 3482
 
3.2%
3 3473
 
3.2%
7 3406
 
3.2%
6 3362
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 99492
92.3%
Dash Punctuation 8291
 
7.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 53232
53.5%
2 11805
 
11.9%
8 11288
 
11.3%
1 3515
 
3.5%
5 3496
 
3.5%
4 3482
 
3.5%
3 3473
 
3.5%
7 3406
 
3.4%
6 3362
 
3.4%
9 2433
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 8291
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 107783
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 53232
49.4%
2 11805
 
11.0%
8 11288
 
10.5%
- 8291
 
7.7%
1 3515
 
3.3%
5 3496
 
3.2%
4 3482
 
3.2%
3 3473
 
3.2%
7 3406
 
3.2%
6 3362
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 107783
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 53232
49.4%
2 11805
 
11.0%
8 11288
 
10.5%
- 8291
 
7.7%
1 3515
 
3.3%
5 3496
 
3.2%
4 3482
 
3.2%
3 3473
 
3.2%
7 3406
 
3.2%
6 3362
 
3.1%

공간데이터
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8291
Missing (%)100.0%
Memory size73.0 KiB

신규정규화ID
Real number (ℝ)

MISSING 

Distinct5447
Distinct (%)99.4%
Missing2813
Missing (%)33.9%
Infinite0
Infinite (%)0.0%
Mean3779933.1
Minimum1
Maximum62149911
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size73.0 KiB
2024-05-04T05:08:09.321795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1167160.9
Q12257782.2
median4147041
Q35201448.8
95-th percentile6238003
Maximum62149911
Range62149910
Interquartile range (IQR)2943666.5

Descriptive statistics

Standard deviation2253827.7
Coefficient of variation (CV)0.59626127
Kurtosis200.18838
Mean3779933.1
Median Absolute Deviation (MAD)1259455.5
Skewness9.2473625
Sum2.0706474 × 1010
Variance5.0797394 × 1012
MonotonicityNot monotonic
2024-05-04T05:08:09.832576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3
 
< 0.1%
5401662 2
 
< 0.1%
2100943 2
 
< 0.1%
5201113 2
 
< 0.1%
5503944 2
 
< 0.1%
4261562 2
 
< 0.1%
4136622 2
 
< 0.1%
2098994 2
 
< 0.1%
370552 2
 
< 0.1%
2099406 2
 
< 0.1%
Other values (5437) 5457
65.8%
(Missing) 2813
33.9%
ValueCountFrequency (%)
1 3
< 0.1%
180232 1
 
< 0.1%
180343 1
 
< 0.1%
180532 1
 
< 0.1%
180641 1
 
< 0.1%
180863 1
 
< 0.1%
181962 1
 
< 0.1%
190052 1
 
< 0.1%
190333 1
 
< 0.1%
190352 1
 
< 0.1%
ValueCountFrequency (%)
62149911 1
< 0.1%
54403410 1
< 0.1%
51078810 1
< 0.1%
43115210 1
< 0.1%
41747213 1
< 0.1%
33624110 1
< 0.1%
23488910 1
< 0.1%
7320352 1
< 0.1%
7320332 1
< 0.1%
7320282 1
< 0.1%

이력ID
Real number (ℝ)

UNIQUE 

Distinct8291
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4290.6122
Minimum1
Maximum8575
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size73.0 KiB
2024-05-04T05:08:10.335037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile430.5
Q12130.5
median4277
Q36469.5
95-th percentile8160.5
Maximum8575
Range8574
Interquartile range (IQR)4339

Descriptive statistics

Standard deviation2487.2455
Coefficient of variation (CV)0.57969477
Kurtosis-1.2084832
Mean4290.6122
Median Absolute Deviation (MAD)2168
Skewness0.0078753212
Sum35573466
Variance6186390.1
MonotonicityNot monotonic
2024-05-04T05:08:10.772790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
976 1
 
< 0.1%
5805 1
 
< 0.1%
5866 1
 
< 0.1%
5865 1
 
< 0.1%
5829 1
 
< 0.1%
5827 1
 
< 0.1%
5826 1
 
< 0.1%
5825 1
 
< 0.1%
5824 1
 
< 0.1%
5823 1
 
< 0.1%
Other values (8281) 8281
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
ValueCountFrequency (%)
8575 1
< 0.1%
8574 1
< 0.1%
8573 1
< 0.1%
8572 1
< 0.1%
8571 1
< 0.1%
8570 1
< 0.1%
8569 1
< 0.1%
8568 1
< 0.1%
8567 1
< 0.1%
8566 1
< 0.1%

동코드 (공통);
Real number (ℝ)

Distinct84
Distinct (%)1.0%
Missing5
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean11036.507
Minimum0
Maximum18700
Zeros13
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size73.0 KiB
2024-05-04T05:08:11.450113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10100
Q110300
median10600
Q311100
95-th percentile13600
Maximum18700
Range18700
Interquartile range (IQR)800

Descriptive statistics

Standard deviation1413.7
Coefficient of variation (CV)0.12809306
Kurtosis12.542279
Mean11036.507
Median Absolute Deviation (MAD)400
Skewness1.6368426
Sum91448500
Variance1998547.6
MonotonicityNot monotonic
2024-05-04T05:08:12.373585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10100 1047
12.6%
10200 982
11.8%
10300 789
 
9.5%
10500 584
 
7.0%
10600 518
 
6.2%
10700 508
 
6.1%
10800 487
 
5.9%
10400 450
 
5.4%
10900 415
 
5.0%
11000 246
 
3.0%
Other values (74) 2260
27.3%
ValueCountFrequency (%)
0 13
 
0.2%
10100 1047
12.6%
10200 982
11.8%
10300 789
9.5%
10400 450
5.4%
10500 584
7.0%
10600 518
6.2%
10700 508
6.1%
10800 487
5.9%
10900 415
 
5.0%
ValueCountFrequency (%)
18700 4
 
< 0.1%
18600 4
 
< 0.1%
18500 5
 
0.1%
18400 7
0.1%
18300 12
0.1%
18200 3
 
< 0.1%
18000 2
 
< 0.1%
17800 1
 
< 0.1%
17700 1
 
< 0.1%
17500 15
0.2%

공사형태 (공통);
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8291
Missing (%)100.0%
Memory size73.0 KiB

지도표출구분
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1152
Missing (%)13.9%
Memory size16.3 KiB
False
7085 
True
 
54
(Missing)
1152 
ValueCountFrequency (%)
False 7085
85.5%
True 54
 
0.7%
(Missing) 1152
 
13.9%
2024-05-04T05:08:12.737333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

X좌표
Real number (ℝ)

MISSING 

Distinct8101
Distinct (%)> 99.9%
Missing188
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean199270.32
Minimum176512.7
Maximum247186.37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size73.0 KiB
2024-05-04T05:08:13.084850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum176512.7
5-th percentile185846.26
Q1192466.34
median200495.33
Q3205660.17
95-th percentile212204.43
Maximum247186.37
Range70673.671
Interquartile range (IQR)13193.835

Descriptive statistics

Standard deviation8149.9113
Coefficient of variation (CV)0.040898771
Kurtosis-0.85975001
Mean199270.32
Median Absolute Deviation (MAD)6558.4352
Skewness-0.05785534
Sum1.6146874 × 109
Variance66421055
MonotonicityNot monotonic
2024-05-04T05:08:13.633028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
197961.319127735 2
 
< 0.1%
194672.42444472 2
 
< 0.1%
185645.462003095 1
 
< 0.1%
207075.118309857 1
 
< 0.1%
206293.017865532 1
 
< 0.1%
186600.071821229 1
 
< 0.1%
193731.002972544 1
 
< 0.1%
191832.413769248 1
 
< 0.1%
185755.079916437 1
 
< 0.1%
188773.297469664 1
 
< 0.1%
Other values (8091) 8091
97.6%
(Missing) 188
 
2.3%
ValueCountFrequency (%)
176512.695247617 1
< 0.1%
179499.787020116 1
< 0.1%
182189.545581719 1
< 0.1%
182193.687681461 1
< 0.1%
182198.070679963 1
< 0.1%
182219.853491436 1
< 0.1%
182255.297844849 1
< 0.1%
182263.181973116 1
< 0.1%
182310.495118976 1
< 0.1%
182443.11257376 1
< 0.1%
ValueCountFrequency (%)
247186.366146463 1
< 0.1%
216127.633129248 1
< 0.1%
216118.372765431 1
< 0.1%
216078.089154609 1
< 0.1%
216075.847040424 1
< 0.1%
216067.89164 1
< 0.1%
216040.528117986 1
< 0.1%
215948.743911905 1
< 0.1%
215911.704035603 1
< 0.1%
215900.624692099 1
< 0.1%

Y좌표
Real number (ℝ)

MISSING 

Distinct8103
Distinct (%)100.0%
Missing188
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean549853.79
Minimum511143.94
Maximum566136.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size73.0 KiB
2024-05-04T05:08:14.174659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum511143.94
5-th percentile541609.17
Q1544953.15
median549571.09
Q3553661.89
95-th percentile560848.51
Maximum566136.31
Range54992.368
Interquartile range (IQR)8708.739

Descriptive statistics

Standard deviation5890.9656
Coefficient of variation (CV)0.010713695
Kurtosis-0.37536071
Mean549853.79
Median Absolute Deviation (MAD)4410.1745
Skewness0.34735447
Sum4.4554652 × 109
Variance34703475
MonotonicityNot monotonic
2024-05-04T05:08:14.655221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
557137.837532458 1
 
< 0.1%
550255.011404952 1
 
< 0.1%
543929.212408831 1
 
< 0.1%
547794.736571603 1
 
< 0.1%
547801.736315909 1
 
< 0.1%
552555.75329214 1
 
< 0.1%
543188.568529152 1
 
< 0.1%
553501.00497984 1
 
< 0.1%
555212.131683768 1
 
< 0.1%
554380.420305288 1
 
< 0.1%
Other values (8093) 8093
97.6%
(Missing) 188
 
2.3%
ValueCountFrequency (%)
511143.943641133 1
< 0.1%
537272.522268358 1
< 0.1%
537409.373973825 1
< 0.1%
537546.953327869 1
< 0.1%
537563.61480962 1
< 0.1%
537653.880649935 1
< 0.1%
537705.880451983 1
< 0.1%
537711.470753305 1
< 0.1%
537887.101768025 1
< 0.1%
538140.476481714 1
< 0.1%
ValueCountFrequency (%)
566136.311988516 1
< 0.1%
565837.586360972 1
< 0.1%
565781.644112327 1
< 0.1%
565694.390064212 1
< 0.1%
565646.807668835 1
< 0.1%
565543.336057079 1
< 0.1%
565522.900667283 1
< 0.1%
565516.397640671 1
< 0.1%
565484.24622506 1
< 0.1%
565387.002958238 1
< 0.1%

Sample

교차로코드입력일자교차로명칭유형코드연동교차로코드구코드 (공통);지번구경찰서 (공통);신경찰서 (공통);작업구분 (공통);표출구분 (공통);고객번호계약종별계량기번호도로구분 (공통);관할사업소 (공통);교차로관리번호공간데이터신규정규화ID이력ID동코드 (공통);공사형태 (공통);지도표출구분X좌표Y좌표
01302<NA>삼성산성지10620321-12 천29029012<NA><NA><NA>110582-0000000976<NA>208613297610200<NA>N193773.589738539911.427179
11304<NA>난향삼거리(연등)25376620산87-11도29029012<NA><NA><NA>110582-0000000201<NA><NA>20110200<NA>N193419.866495540179.920949
21327<NA>대우당약국305401000-118도<NA>26012<NA><NA><NA>110582-0000001561<NA><NA>156110300<NA>N191675.051919539051.325799
31454<NA>수동물병원(연등)211453530442-185도33033012<NA><NA><NA>210482-0000003649<NA><NA>364910200<NA>N190062.508304544145.216358
41300<NA>삼성동자치회관10620310-5도29029012<NA><NA><NA>110582-0000004279<NA><NA>427910200<NA>N193953.299244540500.194027
51305<NA>인헌초교106201679-9 대29029012<NA><NA><NA>110582-0000002929<NA>3130422292910100<NA>N196378.738953541868.057988
61309<NA>금천경찰서(연등)111310620543도29029011<NA><NA><NA>110582-0000001560<NA><NA>156010200<NA>N192240.108329542444.534806
71328<NA>은행나무사거리305401000-99도<NA>26012<NA><NA><NA>110582-0000000382<NA><NA>38210300<NA>N191682.657529539208.202239
81329<NA>은행나무사거리(연등)113285401000-101도<NA>26012<NA><NA><NA>110582-0000002049<NA><NA>204910300<NA>N191768.785579539161.468929
91330<NA>관악농협105401000-123구<NA>26012<NA><NA><NA>110582-0000002361<NA><NA>236110300<NA>N192011.430219539037.622892
교차로코드입력일자교차로명칭유형코드연동교차로코드구코드 (공통);지번구경찰서 (공통);신경찰서 (공통);작업구분 (공통);표출구분 (공통);고객번호계약종별계량기번호도로구분 (공통);관할사업소 (공통);교차로관리번호공간데이터신규정규화ID이력ID동코드 (공통);공사형태 (공통);지도표출구분X좌표Y좌표
82818891<NA>여의도공원(연등)1<NA>5602-11도17017012<NA><NA><NA>110482-0000008561<NA>2260881856111000<NA>N<NA><NA>
82828897<NA>개원길138동(연등)3<NA>680660-12 대41041012<NA><NA><NA><NA>10682-0000008567<NA>5100781856710300<NA>N<NA><NA>
82838892<NA>가산어반워크2<NA>540459-16도26026012<NA><NA><NA>210582-0000008562<NA>1191211856210100<NA>N<NA><NA>
82848895<NA>개원초교앞3<NA>680660-11 도41041012<NA><NA><NA><NA>10682-0000008565<NA>5111332856510300<NA>N<NA><NA>
82858896<NA>개원길138동3<NA>680660-11 도41041012<NA><NA><NA><NA>10682-0000008566<NA>5100892856610300<NA>N<NA><NA>
82868898<NA>올림픽대교북단진입램프1<NA>210562천23023012<NA><NA><NA>110982-0000008568<NA>5283471856810300<NA>N<NA><NA>
82878884<NA>올림픽대교남단램프(동)1<NA>710255-1천36036012<NA><NA><NA>110682-0000008554<NA>5292625855410200<NA>N<NA><NA>
82888885<NA>조이라이프앞2<NA>54060-35 도26026012<NA><NA><NA>210582-0000008555<NA>2100401855510100<NA>N<NA><NA>
82898901<NA>한서빌딩1<NA>4701060도35035012<NA><NA><NA>110482-0000008571<NA>1251691857110100<NA>N<NA><NA>
82908874<NA>개포1동우체국3<NA>680647 도41041012<NA><NA><NA>210682-0000008544<NA>5111371854410300<NA>N<NA><NA>