Overview

Dataset statistics

Number of variables28
Number of observations10000
Missing cells49500
Missing cells (%)17.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 MiB
Average record size in memory251.0 B

Variable types

Text4
Categorical8
Numeric10
Unsupported6

Dataset

Description횡단보도관리번호,상태 (공통),횡단보도종류코드,가로길이,세로길이,화살표시수량,화살표시길이,고가 (공통),구경찰서코드 (공통),구코드 (공통),동코드 (공통),지번,신경찰서코드 (공통),작업구분 (공통),표출구분 (공통),도로구분 (공통),관할사업소 (공통),신규정규화ID,설치일,교체일,공간데이터,이력ID,공사관리번호,구횡단보도관리번호,공사형태 (공통),교차로코드,X좌표,Y좌표
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15554/S/1/datasetView.do

Alerts

상태 (공통) is highly imbalanced (92.8%)Imbalance
고가 (공통) is highly imbalanced (99.4%)Imbalance
화살표시수량 has 210 (2.1%) missing valuesMissing
화살표시길이 has 437 (4.4%) missing valuesMissing
신규정규화ID has 8548 (85.5%) missing valuesMissing
설치일 has 9825 (98.2%) missing valuesMissing
교체일 has 9827 (98.3%) missing valuesMissing
공간데이터 has 10000 (100.0%) missing valuesMissing
공사형태 (공통) has 1327 (13.3%) missing valuesMissing
교차로코드 has 9127 (91.3%) missing valuesMissing
Y좌표 is highly skewed (γ1 = -24.65746169)Skewed
이력ID has unique valuesUnique
신규정규화ID is an unsupported type, check if it needs cleaning or further analysisUnsupported
설치일 is an unsupported type, check if it needs cleaning or further analysisUnsupported
교체일 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
교차로코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
화살표시수량 has 2434 (24.3%) zerosZeros

Reproduction

Analysis started2024-05-04 02:36:16.768929
Analysis finished2024-05-04 02:36:18.142628
Duration1.37 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

횡단보도관리번호
Text

Distinct7258
Distinct (%)72.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T02:36:18.501004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters130000
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

Unique5375 ?
Unique (%)53.8%

Sample

1st row06-0000001056
2nd row06-0000001346
3rd row06-0000013600
4th row06-0000010471
5th row06-0000034754
ValueCountFrequency (%)
06-0000000746 74
 
0.7%
06-0000001277 22
 
0.2%
06-0000000484 21
 
0.2%
06-0000002406 20
 
0.2%
06-0000002340 18
 
0.2%
06-0000013457 18
 
0.2%
06-0000013622 16
 
0.2%
06-0000011086 14
 
0.1%
06-0000002825 13
 
0.1%
06-0000010328 12
 
0.1%
Other values (7248) 9772
97.7%
2024-05-04T02:36:19.209460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 70578
54.3%
6 13562
 
10.4%
- 10000
 
7.7%
1 7029
 
5.4%
3 5913
 
4.5%
2 4711
 
3.6%
4 4084
 
3.1%
5 3681
 
2.8%
7 3532
 
2.7%
9 3530
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 120000
92.3%
Dash Punctuation 10000
 
7.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 70578
58.8%
6 13562
 
11.3%
1 7029
 
5.9%
3 5913
 
4.9%
2 4711
 
3.9%
4 4084
 
3.4%
5 3681
 
3.1%
7 3532
 
2.9%
9 3530
 
2.9%
8 3380
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 130000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 70578
54.3%
6 13562
 
10.4%
- 10000
 
7.7%
1 7029
 
5.4%
3 5913
 
4.5%
2 4711
 
3.6%
4 4084
 
3.1%
5 3681
 
2.8%
7 3532
 
2.7%
9 3530
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 130000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 70578
54.3%
6 13562
 
10.4%
- 10000
 
7.7%
1 7029
 
5.4%
3 5913
 
4.5%
2 4711
 
3.6%
4 4084
 
3.1%
5 3681
 
2.8%
7 3532
 
2.7%
9 3530
 
2.7%

상태 (공통)
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9866 
4
 
93
3
 
41

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 9866
98.7%
4 93
 
0.9%
3 41
 
0.4%

Length

2024-05-04T02:36:19.462403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:36:19.641440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9866
98.7%
4 93
 
0.9%
3 41
 
0.4%

횡단보도종류코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
6219 
1
2471 
3
1266 
4
 
41
6
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 6219
62.2%
1 2471
 
24.7%
3 1266
 
12.7%
4 41
 
0.4%
6 3
 
< 0.1%

Length

2024-05-04T02:36:19.824938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:36:20.011905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 6219
62.2%
1 2471
 
24.7%
3 1266
 
12.7%
4 41
 
0.4%
6 3
 
< 0.1%

가로길이
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
15
7026 
0
1896 
<NA>
1078 

Length

Max length4
Median length2
Mean length2.026
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row15
2nd row15
3rd row15
4th row15
5th row<NA>

Common Values

ValueCountFrequency (%)
15 7026
70.3%
0 1896
 
19.0%
<NA> 1078
 
10.8%

Length

2024-05-04T02:36:20.280575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:36:20.473734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
15 7026
70.3%
0 1896
 
19.0%
na 1078
 
10.8%

세로길이
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
8
7026 
0
1896 
<NA>
1078 

Length

Max length4
Median length1
Mean length1.3234
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row8
2nd row8
3rd row8
4th row8
5th row<NA>

Common Values

ValueCountFrequency (%)
8 7026
70.3%
0 1896
 
19.0%
<NA> 1078
 
10.8%

Length

2024-05-04T02:36:20.811166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:36:20.996574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8 7026
70.3%
0 1896
 
19.0%
na 1078
 
10.8%

화살표시수량
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.1%
Missing210
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean1.9899898
Minimum0
Maximum10
Zeros2434
Zeros (%)24.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:36:21.168461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile4
Maximum10
Range10
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.5170573
Coefficient of variation (CV)0.76234425
Kurtosis-1.2418851
Mean1.9899898
Median Absolute Deviation (MAD)2
Skewness0.11771943
Sum19482
Variance2.3014628
MonotonicityNot monotonic
2024-05-04T02:36:21.440621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 3378
33.8%
4 2910
29.1%
0 2434
24.3%
1 1065
 
10.7%
10 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 210
 
2.1%
ValueCountFrequency (%)
0 2434
24.3%
1 1065
 
10.7%
2 3378
33.8%
4 2910
29.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
4 2910
29.1%
2 3378
33.8%
1 1065
 
10.7%
0 2434
24.3%

화살표시길이
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)0.1%
Missing437
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean1.3535501
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:36:21.688298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum6
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0423799
Coefficient of variation (CV)0.77010808
Kurtosis13.917479
Mean1.3535501
Median Absolute Deviation (MAD)0
Skewness3.7927373
Sum12944
Variance1.0865558
MonotonicityNot monotonic
2024-05-04T02:36:21.898033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 7831
78.3%
2 1311
 
13.1%
6 408
 
4.1%
3 10
 
0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
(Missing) 437
 
4.4%
ValueCountFrequency (%)
1 7831
78.3%
2 1311
 
13.1%
3 10
 
0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
6 408
 
4.1%
ValueCountFrequency (%)
6 408
 
4.1%
5 1
 
< 0.1%
4 2
 
< 0.1%
3 10
 
0.1%
2 1311
 
13.1%
1 7831
78.3%

고가 (공통)
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9993 
2
 
6
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 9993
99.9%
2 6
 
0.1%
3 1
 
< 0.1%

Length

2024-05-04T02:36:22.187452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:36:22.484562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9993
99.9%
2 6
 
0.1%
3 1
 
< 0.1%

구경찰서코드 (공통)
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean265.42654
Minimum110
Maximum410
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:36:22.899726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110
5-th percentile130
Q1200
median280
Q3340
95-th percentile390
Maximum410
Range300
Interquartile range (IQR)140

Descriptive statistics

Standard deviation82.593825
Coefficient of variation (CV)0.31117395
Kurtosis-1.1118772
Mean265.42654
Median Absolute Deviation (MAD)70
Skewness-0.099630572
Sum2654000
Variance6821.7399
MonotonicityNot monotonic
2024-05-04T02:36:23.271852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
280 809
 
8.1%
170 768
 
7.7%
210 552
 
5.5%
350 550
 
5.5%
310 544
 
5.4%
300 491
 
4.9%
330 486
 
4.9%
340 472
 
4.7%
390 462
 
4.6%
360 448
 
4.5%
Other values (21) 4417
44.2%
ValueCountFrequency (%)
110 141
 
1.4%
120 276
 
2.8%
130 151
 
1.5%
140 279
 
2.8%
150 95
 
0.9%
160 419
4.2%
170 768
7.7%
180 263
 
2.6%
190 59
 
0.6%
200 169
 
1.7%
ValueCountFrequency (%)
410 294
2.9%
400 61
 
0.6%
390 462
4.6%
380 233
2.3%
370 25
 
0.2%
360 448
4.5%
350 550
5.5%
340 472
4.7%
330 486
4.9%
320 104
 
1.0%

구코드 (공통)
Real number (ℝ)

Distinct25
Distinct (%)0.3%
Missing32
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean478.83527
Minimum110
Maximum740
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:36:23.626241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110
5-th percentile140
Q1380
median530
Q3650
95-th percentile740
Maximum740
Range630
Interquartile range (IQR)270

Descriptive statistics

Standard deviation190.07583
Coefficient of variation (CV)0.39695454
Kurtosis-0.89360153
Mean478.83527
Median Absolute Deviation (MAD)150
Skewness-0.52737317
Sum4773030
Variance36128.823
MonotonicityNot monotonic
2024-05-04T02:36:24.003423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
680 1001
 
10.0%
560 962
 
9.6%
650 662
 
6.6%
380 606
 
6.1%
740 546
 
5.5%
470 539
 
5.4%
710 526
 
5.3%
440 524
 
5.2%
500 501
 
5.0%
530 486
 
4.9%
Other values (15) 3615
36.1%
ValueCountFrequency (%)
110 376
3.8%
140 416
4.2%
170 423
4.2%
200 301
3.0%
210 343
3.4%
230 167
 
1.7%
260 16
 
0.2%
290 134
 
1.3%
300 79
 
0.8%
320 33
 
0.3%
ValueCountFrequency (%)
740 546
5.5%
710 526
5.3%
680 1001
10.0%
650 662
6.6%
620 314
 
3.1%
590 307
 
3.1%
560 962
9.6%
540 318
 
3.2%
530 486
4.9%
500 501
5.0%

동코드 (공통)
Real number (ℝ)

Distinct84
Distinct (%)0.8%
Missing8
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean11074.189
Minimum0
Maximum18700
Zeros61
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:36:24.327753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10100
Q110300
median10700
Q311400
95-th percentile13500
Maximum18700
Range18700
Interquartile range (IQR)1100

Descriptive statistics

Standard deviation1631.0032
Coefficient of variation (CV)0.14727969
Kurtosis15.82276
Mean11074.189
Median Absolute Deviation (MAD)500
Skewness-0.26475839
Sum1.106533 × 108
Variance2660171.5
MonotonicityNot monotonic
2024-05-04T02:36:24.592576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10200 1199
 
12.0%
10100 1185
 
11.8%
10300 808
 
8.1%
10800 785
 
7.8%
10700 760
 
7.6%
10600 502
 
5.0%
10400 485
 
4.9%
10500 466
 
4.7%
10900 357
 
3.6%
11000 298
 
3.0%
Other values (74) 3147
31.5%
ValueCountFrequency (%)
0 61
 
0.6%
10100 1185
11.8%
10200 1199
12.0%
10300 808
8.1%
10400 485
4.9%
10500 466
 
4.7%
10600 502
5.0%
10700 760
7.6%
10800 785
7.8%
10900 357
 
3.6%
ValueCountFrequency (%)
18700 1
 
< 0.1%
18600 7
 
0.1%
18500 9
0.1%
18400 6
 
0.1%
18300 22
0.2%
18200 7
 
0.1%
18000 3
 
< 0.1%
17800 2
 
< 0.1%
17700 3
 
< 0.1%
17500 12
0.1%

지번
Text

Distinct5074
Distinct (%)51.2%
Missing87
Missing (%)0.9%
Memory size156.2 KiB
2024-05-04T02:36:25.237373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.9943509
Min length2

Characters and Unicode

Total characters59422
Distinct characters35
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

Unique3163 ?
Unique (%)31.9%

Sample

1st row416-8구
2nd row404-8도
3rd row451구
4th row38-2도
5th row8-3제
ValueCountFrequency (%)
도 1401
 
12.0%
대 206
 
1.8%
16-33도 76
 
0.7%
668-6 69
 
0.6%
132-2장 52
 
0.4%
19-1도 43
 
0.4%
가 26
 
0.2%
10-1도 25
 
0.2%
427도 23
 
0.2%
101도 23
 
0.2%
Other values (5069) 9713
83.3%
2024-05-04T02:36:26.089584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8150
13.7%
- 8043
13.5%
도 7499
12.6%
2 5154
8.7%
3 4176
7.0%
4 3743
 
6.3%
6 3527
 
5.9%
5 3146
 
5.3%
0 3062
 
5.2%
7 3033
 
5.1%
Other values (25) 9889
16.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39551
66.6%
Other Letter 10084
 
17.0%
Dash Punctuation 8043
 
13.5%
Space Separator 1744
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 7499
74.4%
대 1172
 
11.6%
천 332
 
3.3%
구 174
 
1.7%
산 172
 
1.7%
임 146
 
1.4%
장 88
 
0.9%
전 87
 
0.9%
철 79
 
0.8%
잡 74
 
0.7%
Other values (13) 261
 
2.6%
Decimal Number
ValueCountFrequency (%)
1 8150
20.6%
2 5154
13.0%
3 4176
10.6%
4 3743
9.5%
6 3527
8.9%
5 3146
 
8.0%
0 3062
 
7.7%
7 3033
 
7.7%
8 2839
 
7.2%
9 2721
 
6.9%
Dash Punctuation
ValueCountFrequency (%)
- 8043
100.0%
Space Separator
ValueCountFrequency (%)
1744
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 49338
83.0%
Hangul 10084
 
17.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 7499
74.4%
대 1172
 
11.6%
천 332
 
3.3%
구 174
 
1.7%
산 172
 
1.7%
임 146
 
1.4%
장 88
 
0.9%
전 87
 
0.9%
철 79
 
0.8%
잡 74
 
0.7%
Other values (13) 261
 
2.6%
Common
ValueCountFrequency (%)
1 8150
16.5%
- 8043
16.3%
2 5154
10.4%
3 4176
8.5%
4 3743
7.6%
6 3527
7.1%
5 3146
 
6.4%
0 3062
 
6.2%
7 3033
 
6.1%
8 2839
 
5.8%
Other values (2) 4465
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49338
83.0%
Hangul 10084
 
17.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8150
16.5%
- 8043
16.3%
2 5154
10.4%
3 4176
8.5%
4 3743
7.6%
6 3527
7.1%
5 3146
 
6.4%
0 3062
 
6.2%
7 3033
 
6.1%
8 2839
 
5.8%
Other values (2) 4465
9.0%
Hangul
ValueCountFrequency (%)
도 7499
74.4%
대 1172
 
11.6%
천 332
 
3.3%
구 174
 
1.7%
산 172
 
1.7%
임 146
 
1.4%
장 88
 
0.9%
전 87
 
0.9%
철 79
 
0.8%
잡 74
 
0.7%
Other values (13) 261
 
2.6%

신경찰서코드 (공통)
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean263.365
Minimum110
Maximum410
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:36:26.435751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110
5-th percentile130
Q1170
median280
Q3340
95-th percentile390
Maximum410
Range300
Interquartile range (IQR)170

Descriptive statistics

Standard deviation87.484582
Coefficient of variation (CV)0.33217999
Kurtosis-1.2478412
Mean263.365
Median Absolute Deviation (MAD)70
Skewness-0.062388926
Sum2633650
Variance7653.5521
MonotonicityNot monotonic
2024-05-04T02:36:26.672086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
170 962
 
9.6%
280 567
 
5.7%
310 547
 
5.5%
350 539
 
5.4%
210 529
 
5.3%
360 527
 
5.3%
300 501
 
5.0%
330 489
 
4.9%
390 434
 
4.3%
410 434
 
4.3%
Other values (21) 4471
44.7%
ValueCountFrequency (%)
110 200
 
2.0%
120 293
 
2.9%
130 216
 
2.2%
140 348
 
3.5%
150 83
 
0.8%
160 423
4.2%
170 962
9.6%
180 301
 
3.0%
190 59
 
0.6%
200 167
 
1.7%
ValueCountFrequency (%)
410 434
4.3%
400 41
 
0.4%
390 434
4.3%
380 239
2.4%
370 54
 
0.5%
360 527
5.3%
350 539
5.4%
340 428
4.3%
330 489
4.9%
320 75
 
0.8%

작업구분 (공통)
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
4
6524 
1
2351 
2
950 
3
 
159
6
 
16

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row4
3rd row4
4th row4
5th row1

Common Values

ValueCountFrequency (%)
4 6524
65.2%
1 2351
 
23.5%
2 950
 
9.5%
3 159
 
1.6%
6 16
 
0.2%

Length

2024-05-04T02:36:26.913939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:36:27.099944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 6524
65.2%
1 2351
 
23.5%
2 950
 
9.5%
3 159
 
1.6%
6 16
 
0.2%

표출구분 (공통)
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
8320 
2
1680 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 8320
83.2%
2 1680
 
16.8%

Length

2024-05-04T02:36:27.303715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:36:27.509575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 8320
83.2%
2 1680
 
16.8%

도로구분 (공통)
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
6056 
2
3936 
<NA>
 
8

Length

Max length4
Median length1
Mean length1.0024
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 6056
60.6%
2 3936
39.4%
<NA> 8
 
0.1%

Length

2024-05-04T02:36:27.712913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:36:27.900354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 6056
60.6%
2 3936
39.4%
na 8
 
0.1%

관할사업소 (공통)
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing38
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean106.15077
Minimum104
Maximum109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:36:28.065421image/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 deviation1.6744218
Coefficient of variation (CV)0.015773995
Kurtosis-1.2996641
Mean106.15077
Median Absolute Deviation (MAD)2
Skewness0.19933879
Sum1057474
Variance2.8036883
MonotonicityNot monotonic
2024-05-04T02:36:28.263611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
108 2314
23.1%
104 2228
22.3%
106 2090
20.9%
105 1832
18.3%
109 832
 
8.3%
107 666
 
6.7%
(Missing) 38
 
0.4%
ValueCountFrequency (%)
104 2228
22.3%
105 1832
18.3%
106 2090
20.9%
107 666
 
6.7%
108 2314
23.1%
109 832
 
8.3%
ValueCountFrequency (%)
109 832
 
8.3%
108 2314
23.1%
107 666
 
6.7%
106 2090
20.9%
105 1832
18.3%
104 2228
22.3%

신규정규화ID
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8548
Missing (%)85.5%
Memory size156.2 KiB

설치일
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9825
Missing (%)98.2%
Memory size156.2 KiB

교체일
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9827
Missing (%)98.3%
Memory size156.2 KiB

공간데이터
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

이력ID
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50890.885
Minimum2
Maximum159440
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:36:28.494544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2583
Q122461.25
median51374
Q376438
95-th percentile101366.9
Maximum159440
Range159438
Interquartile range (IQR)53976.75

Descriptive statistics

Standard deviation31839.695
Coefficient of variation (CV)0.62564632
Kurtosis-0.9494282
Mean50890.885
Median Absolute Deviation (MAD)26006.5
Skewness0.046019749
Sum5.0890885 × 108
Variance1.0137662 × 109
MonotonicityNot monotonic
2024-05-04T02:36:28.864508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
88837 1
 
< 0.1%
57684 1
 
< 0.1%
45403 1
 
< 0.1%
16505 1
 
< 0.1%
75350 1
 
< 0.1%
72091 1
 
< 0.1%
1543 1
 
< 0.1%
84416 1
 
< 0.1%
27484 1
 
< 0.1%
14657 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
4 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
13 1
< 0.1%
17 1
< 0.1%
25 1
< 0.1%
36 1
< 0.1%
37 1
< 0.1%
45 1
< 0.1%
ValueCountFrequency (%)
159440 1
< 0.1%
157906 1
< 0.1%
157859 1
< 0.1%
157858 1
< 0.1%
156892 1
< 0.1%
156785 1
< 0.1%
156669 1
< 0.1%
153914 1
< 0.1%
153731 1
< 0.1%
153349 1
< 0.1%

공사관리번호
Text

Distinct1441
Distinct (%)14.4%
Missing12
Missing (%)0.1%
Memory size156.2 KiB
2024-05-04T02:36:29.360686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters129844
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

Unique406 ?
Unique (%)4.1%

Sample

1st row2010-1008-019
2nd row2011-0108-003
3rd row2003-0208-008
4th row2010-1008-004
5th row2000-0000-000
ValueCountFrequency (%)
2000-0000-000 1532
 
15.3%
2010-0104-002 94
 
0.9%
2004-0108-222 75
 
0.8%
2012-0112-003 74
 
0.7%
2009-1008-012 57
 
0.6%
2003-0108-058 49
 
0.5%
2009-1004-002 48
 
0.5%
2009-0108-049 45
 
0.5%
2011-1008-017 44
 
0.4%
2010-0108-016 43
 
0.4%
Other values (1431) 7927
79.4%
2024-05-04T02:36:30.050622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 52737
40.6%
- 19976
 
15.4%
1 19454
 
15.0%
2 15110
 
11.6%
8 9285
 
7.2%
4 2911
 
2.2%
5 2472
 
1.9%
3 2162
 
1.7%
9 2077
 
1.6%
7 1835
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 109868
84.6%
Dash Punctuation 19976
 
15.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 52737
48.0%
1 19454
 
17.7%
2 15110
 
13.8%
8 9285
 
8.5%
4 2911
 
2.6%
5 2472
 
2.2%
3 2162
 
2.0%
9 2077
 
1.9%
7 1835
 
1.7%
6 1825
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 19976
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 129844
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 52737
40.6%
- 19976
 
15.4%
1 19454
 
15.0%
2 15110
 
11.6%
8 9285
 
7.2%
4 2911
 
2.2%
5 2472
 
1.9%
3 2162
 
1.7%
9 2077
 
1.6%
7 1835
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 129844
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 52737
40.6%
- 19976
 
15.4%
1 19454
 
15.0%
2 15110
 
11.6%
8 9285
 
7.2%
4 2911
 
2.2%
5 2472
 
1.9%
3 2162
 
1.7%
9 2077
 
1.6%
7 1835
 
1.4%

구횡단보도관리번호
Text

Distinct7245
Distinct (%)72.6%
Missing19
Missing (%)0.2%
Memory size156.2 KiB
2024-05-04T02:36:30.606602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters89829
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

Unique5366 ?
Unique (%)53.8%

Sample

1st row06-001056
2nd row06-001346
3rd row06-013600
4th row06-010471
5th row06-034754
ValueCountFrequency (%)
06-000746 74
 
0.7%
06-001277 22
 
0.2%
06-000484 21
 
0.2%
06-002406 20
 
0.2%
06-002340 18
 
0.2%
06-013457 18
 
0.2%
06-013622 16
 
0.2%
06-011086 14
 
0.1%
06-002825 13
 
0.1%
06-010328 12
 
0.1%
Other values (7235) 9753
97.7%
2024-05-04T02:36:31.515615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 30521
34.0%
6 13536
15.1%
- 9981
 
11.1%
1 7023
 
7.8%
3 5899
 
6.6%
2 4702
 
5.2%
4 4075
 
4.5%
5 3668
 
4.1%
7 3527
 
3.9%
9 3525
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79848
88.9%
Dash Punctuation 9981
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 30521
38.2%
6 13536
17.0%
1 7023
 
8.8%
3 5899
 
7.4%
2 4702
 
5.9%
4 4075
 
5.1%
5 3668
 
4.6%
7 3527
 
4.4%
9 3525
 
4.4%
8 3372
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 9981
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 89829
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 30521
34.0%
6 13536
15.1%
- 9981
 
11.1%
1 7023
 
7.8%
3 5899
 
6.6%
2 4702
 
5.2%
4 4075
 
4.5%
5 3668
 
4.1%
7 3527
 
3.9%
9 3525
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89829
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 30521
34.0%
6 13536
15.1%
- 9981
 
11.1%
1 7023
 
7.8%
3 5899
 
6.6%
2 4702
 
5.2%
4 4075
 
4.5%
5 3668
 
4.1%
7 3527
 
3.9%
9 3525
 
3.9%

공사형태 (공통)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1327
Missing (%)13.3%
Memory size156.2 KiB

교차로코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9127
Missing (%)91.3%
Memory size156.2 KiB

X좌표
Real number (ℝ)

Distinct9339
Distinct (%)93.4%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean197606.45
Minimum18
Maximum472112.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:36:31.848413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile186066.03
Q1191592.11
median196982.84
Q3203474.55
95-th percentile211609.96
Maximum472112.3
Range472094.3
Interquartile range (IQR)11882.434

Descriptive statistics

Standard deviation10552.403
Coefficient of variation (CV)0.053401107
Kurtosis179.19739
Mean197606.45
Median Absolute Deviation (MAD)5925.3858
Skewness-5.2592595
Sum1.9758669 × 109
Variance1.1135322 × 108
MonotonicityNot monotonic
2024-05-04T02:36:32.300353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193092.053257002 74
 
0.7%
195994.812289485 22
 
0.2%
193029.741227089 19
 
0.2%
189133.246923306 18
 
0.2%
199363.020195707 17
 
0.2%
200785.990496908 16
 
0.2%
197264.065358864 16
 
0.2%
202093.430529509 14
 
0.1%
193096.652213123 13
 
0.1%
211398.26068495 12
 
0.1%
Other values (9329) 9778
97.8%
ValueCountFrequency (%)
18.0 2
 
< 0.1%
19.0 5
0.1%
20.0 4
< 0.1%
180505.013235616 1
 
< 0.1%
182622.608640425 1
 
< 0.1%
182666.125456182 1
 
< 0.1%
182674.61436605 1
 
< 0.1%
182677.277170413 1
 
< 0.1%
182680.450512854 1
 
< 0.1%
182710.900311526 1
 
< 0.1%
ValueCountFrequency (%)
472112.29970243 1
< 0.1%
281239.440779965 1
< 0.1%
216075.105707211 1
< 0.1%
216046.587224328 1
< 0.1%
216046.418009536 1
< 0.1%
216046.406465003 1
< 0.1%
215922.010699482 1
< 0.1%
215910.059439591 1
< 0.1%
215909.742230651 1
< 0.1%
215894.629008442 1
< 0.1%

Y좌표
Real number (ℝ)

SKEWED 

Distinct9331
Distinct (%)93.3%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean547781.3
Minimum54
Maximum952693.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:36:32.917394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile541898.28
Q1544920.45
median547772.33
Q3551282.63
95-th percentile556595.51
Maximum952693.7
Range952639.7
Interquartile range (IQR)6362.1865

Descriptive statistics

Standard deviation19183.596
Coefficient of variation (CV)0.035020539
Kurtosis748.48596
Mean547781.3
Median Absolute Deviation (MAD)3216.1483
Skewness-24.657462
Sum5.4772652 × 109
Variance3.6801037 × 108
MonotonicityNot monotonic
2024-05-04T02:36:33.216106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
556445.202172404 74
 
0.7%
549941.626194084 22
 
0.2%
553124.982085217 19
 
0.2%
547335.710076538 18
 
0.2%
551872.493782077 17
 
0.2%
552439.475106349 16
 
0.2%
550859.393326222 16
 
0.2%
551242.046636656 14
 
0.1%
556462.66293011 13
 
0.1%
550589.994967899 12
 
0.1%
Other values (9321) 9778
97.8%
ValueCountFrequency (%)
54.0 6
0.1%
55.0 5
0.1%
537482.742479926 1
 
< 0.1%
537535.1702123102 1
 
< 0.1%
537557.293176607 1
 
< 0.1%
537559.277011146 1
 
< 0.1%
537712.614279657 1
 
< 0.1%
537727.998071783 1
 
< 0.1%
537892.4401669896 1
 
< 0.1%
538121.22698927 1
 
< 0.1%
ValueCountFrequency (%)
952693.695268617 1
< 0.1%
597260.25691676 1
< 0.1%
589196.389595178 1
< 0.1%
565692.753782872 1
< 0.1%
565678.627704794 1
< 0.1%
565676.793674729 1
< 0.1%
565573.656904849 1
< 0.1%
565566.419757831 1
< 0.1%
565566.058141574 1
< 0.1%
565566.029774242 1
< 0.1%

Sample

횡단보도관리번호상태 (공통)횡단보도종류코드가로길이세로길이화살표시수량화살표시길이고가 (공통)구경찰서코드 (공통)구코드 (공통)동코드 (공통)지번신경찰서코드 (공통)작업구분 (공통)표출구분 (공통)도로구분 (공통)관할사업소 (공통)신규정규화ID설치일교체일공간데이터이력ID공사관리번호구횡단보도관리번호공사형태 (공통)교차로코드X좌표Y좌표
1148606-00000010561215846121044012300416-8구210212108NaNNaNNaN<NA>888372010-1008-01906-001056005NaN191560.797953550854.968858
1199106-00000013461215822121044010800404-8도210412108NaNNaNNaN<NA>505302011-0108-00306-001346005NaN194866.276265549640.393951
4556406-00000136001215821135047010200451구350411104NaNNaNNaN<NA>435902003-0208-00806-0136001.0NaN188932.525278547040.904882
3627306-0000010471121582113607101080038-2도360411106NaNNaNNaN<NA>768512010-1008-00406-0104715.0NaN211184.063552542990.192505
496106-000003475413<NA><NA>0<NA>1170560110008-3제1701211042199952NaNNaN<NA>779142000-0000-00006-0347540047070194662.355816546537.126722
245206-000003032012000113607101020020대360412106NaNNaNNaN<NA>432292000-0000-00006-030320NaNNaN209671.921742546994.448663
493906-000003531312000111801401620061-53대110122108NaNNaNNaN<NA>859052011-1108-09006-035313001NaN201818.570534551293.840056
895706-00000006871115822139038010400536-2도390411108NaNNaNNaN<NA>9832011-0408-00306-000687005NaN192207.464796557151.698095
563806-000003523513<NA><NA>011190290105002-3도19012110743157110NaNNaN<NA>977832000-0000-00006-035235004562200573.510591554319.300279
3329006-00000095741215821136071011100209-7도360411106NaNNaNNaN<NA>813592008-1002-46506-0095745.0NaN211122.498264545481.536805
횡단보도관리번호상태 (공통)횡단보도종류코드가로길이세로길이화살표시수량화살표시길이고가 (공통)구경찰서코드 (공통)구코드 (공통)동코드 (공통)지번신경찰서코드 (공통)작업구분 (공통)표출구분 (공통)도로구분 (공통)관할사업소 (공통)신규정규화ID설치일교체일공간데이터이력ID공사관리번호구횡단보도관리번호공사형태 (공통)교차로코드X좌표Y좌표
4077206-00000119031215821118020010800124-2도180411109NaNNaNNaN<NA>516122010-0508-00406-0119035.0NaN202964.181407550466.542244
3839506-00000112541215821131074010500463도310411106NaNNaNNaN<NA>201052008-1008-80506-0112545.0NaN211880.514979548457.381355
4113206-000001212112158411300500104001454-8도300411104NaNNaNNaN<NA>950512005-0108-14006-0121215.0NaN185712.6876551037.787583
3404306-00000093991215821131074010300163도310112106NaNNaNNaN<NA>63092010-0108-01606-0093995.0NaN214583.856589550124.915445
2493606-000000599812<NA><NA>41117056013200232-65도1701211052146734NaNNaN<NA>1056402003-1108-14206-0059980011622192055.299804544923.605985
890606-00000004461215822124038011000199-12도240411108NaNNaNNaN<NA>17142008-0108-95306-000446005NaN191677.474677553417.178342
4101206-000001192012158211350470101001068도350412104NaNNaNNaN<NA>103372011-0108-05506-0119205.0NaN187975.649328547589.772313
895906-00000006871115822139038010400536-2도390411108NaNNaNNaN<NA>416172011-0408-00306-000687005NaN192208.924468557150.907012
4321706-00000125991115821130050010100284-66도300111104NaNNaNNaN<NA>427502009-0108-05706-0125995.0NaN189092.980534549990.872707
3657506-00000108261115821131074010900373도310411106NaNNaNNaN<NA>370122005-0108-01506-0108265.0NaN211034.072373549206.246517