Overview

Dataset statistics

Number of variables22
Number of observations10000
Missing cells28004
Missing cells (%)12.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 MiB
Average record size in memory201.0 B

Variable types

Categorical12
Text3
Numeric7

Dataset

Description노드링크 유형,노드 WKT,노드 ID,노드 유형 코드,링크 WKT,링크 ID,링크 유형 코드,시작노드 ID,종료노드 ID,링크 길이,시군구코드,시군구명,읍면동코드,읍면동명,고가도로,지하철네트워크,교량,터널,육교,횡단보도,공원,녹지,건물내
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21208/S/1/datasetView.do

Alerts

육교 is highly imbalanced (94.9%)Imbalance
횡단보도 is highly imbalanced (68.9%)Imbalance
노드 WKT has 5499 (55.0%) missing valuesMissing
링크 WKT has 4501 (45.0%) missing valuesMissing
링크 유형 코드 has 4501 (45.0%) missing valuesMissing
시작노드 ID has 4501 (45.0%) missing valuesMissing
종료노드 ID has 4501 (45.0%) missing valuesMissing
링크 길이 has 4501 (45.0%) missing valuesMissing
노드 ID has 5499 (55.0%) zerosZeros
링크 ID has 4501 (45.0%) zerosZeros

Reproduction

Analysis started2024-05-03 20:43:24.353567
Analysis finished2024-05-03 20:43:25.783738
Duration1.43 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

노드링크 유형
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
LINK
5499 
NODE
4501 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLINK
2nd rowLINK
3rd rowLINK
4th rowNODE
5th rowNODE

Common Values

ValueCountFrequency (%)
LINK 5499
55.0%
NODE 4501
45.0%

Length

2024-05-03T20:43:25.987938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T20:43:26.342721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
link 5499
55.0%
node 4501
45.0%

노드 WKT
Text

MISSING 

Distinct4501
Distinct (%)100.0%
Missing5499
Missing (%)55.0%
Memory size156.2 KiB
2024-05-03T20:43:26.901721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length43
Mean length43.045323
Min length39

Characters and Unicode

Total characters193747
Distinct characters19
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4501 ?
Unique (%)100.0%

Sample

1st rowPOINT(127.00931862495058 37.56972059789929)
2nd rowPOINT(126.99344978239326 37.54101206127678)
3rd rowPOINT(126.96742733110658 37.54399705155888)
4th rowPOINT(126.98768680375296 37.54346504856895)
5th rowPOINT(126.96103689407173 37.59175482320546)
ValueCountFrequency (%)
point(126.98171892728625 1
 
< 0.1%
37.534507011038535 1
 
< 0.1%
37.54515570561704 1
 
< 0.1%
point(126.97438541411168 1
 
< 0.1%
37.57121322862307 1
 
< 0.1%
point(127.01475796804415 1
 
< 0.1%
37.56449855715056 1
 
< 0.1%
point(126.9531639183244 1
 
< 0.1%
point(126.96518658902421 1
 
< 0.1%
37.56312337266496 1
 
< 0.1%
Other values (8992) 8992
99.9%
2024-05-03T20:43:27.996015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 17993
 
9.3%
5 16434
 
8.5%
6 16110
 
8.3%
1 16097
 
8.3%
3 15933
 
8.2%
2 15726
 
8.1%
9 14802
 
7.6%
0 12174
 
6.3%
4 11771
 
6.1%
8 11697
 
6.0%
Other values (9) 45010
23.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 148737
76.8%
Uppercase Letter 22505
 
11.6%
Other Punctuation 9002
 
4.6%
Space Separator 4501
 
2.3%
Open Punctuation 4501
 
2.3%
Close Punctuation 4501
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 17993
12.1%
5 16434
11.0%
6 16110
10.8%
1 16097
10.8%
3 15933
10.7%
2 15726
10.6%
9 14802
10.0%
0 12174
8.2%
4 11771
7.9%
8 11697
7.9%
Uppercase Letter
ValueCountFrequency (%)
P 4501
20.0%
O 4501
20.0%
T 4501
20.0%
N 4501
20.0%
I 4501
20.0%
Other Punctuation
ValueCountFrequency (%)
. 9002
100.0%
Space Separator
ValueCountFrequency (%)
4501
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4501
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4501
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 171242
88.4%
Latin 22505
 
11.6%

Most frequent character per script

Common
ValueCountFrequency (%)
7 17993
10.5%
5 16434
9.6%
6 16110
9.4%
1 16097
9.4%
3 15933
9.3%
2 15726
9.2%
9 14802
8.6%
0 12174
7.1%
4 11771
6.9%
8 11697
6.8%
Other values (4) 22505
13.1%
Latin
ValueCountFrequency (%)
P 4501
20.0%
O 4501
20.0%
T 4501
20.0%
N 4501
20.0%
I 4501
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 193747
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 17993
 
9.3%
5 16434
 
8.5%
6 16110
 
8.3%
1 16097
 
8.3%
3 15933
 
8.2%
2 15726
 
8.1%
9 14802
 
7.6%
0 12174
 
6.3%
4 11771
 
6.1%
8 11697
 
6.0%
Other values (9) 45010
23.2%

노드 ID
Real number (ℝ)

ZEROS 

Distinct4502
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44764.274
Minimum0
Maximum215420
Zeros5499
Zeros (%)55.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T20:43:28.474289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3128012.25
95-th percentile164246.1
Maximum215420
Range215420
Interquartile range (IQR)128012.25

Descriptive statistics

Standard deviation65050.289
Coefficient of variation (CV)1.4531742
Kurtosis-0.78037809
Mean44764.274
Median Absolute Deviation (MAD)0
Skewness0.9872723
Sum4.4764274 × 108
Variance4.2315401 × 109
MonotonicityNot monotonic
2024-05-03T20:43:28.882130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5499
55.0%
151994 1
 
< 0.1%
128508 1
 
< 0.1%
73274 1
 
< 0.1%
160577 1
 
< 0.1%
128921 1
 
< 0.1%
169625 1
 
< 0.1%
128636 1
 
< 0.1%
157867 1
 
< 0.1%
6147 1
 
< 0.1%
Other values (4492) 4492
44.9%
ValueCountFrequency (%)
0 5499
55.0%
19 1
 
< 0.1%
91 1
 
< 0.1%
95 1
 
< 0.1%
99 1
 
< 0.1%
102 1
 
< 0.1%
103 1
 
< 0.1%
132 1
 
< 0.1%
5565 1
 
< 0.1%
5576 1
 
< 0.1%
ValueCountFrequency (%)
215420 1
< 0.1%
214819 1
< 0.1%
214568 1
< 0.1%
214527 1
< 0.1%
214526 1
< 0.1%
214498 1
< 0.1%
214497 1
< 0.1%
214224 1
< 0.1%
214199 1
< 0.1%
214121 1
< 0.1%

노드 유형 코드
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5499 
0
4325 
2
 
169
3
 
7

Length

Max length4
Median length4
Mean length2.6497
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 5499
55.0%
0 4325
43.2%
2 169
 
1.7%
3 7
 
0.1%

Length

2024-05-03T20:43:29.301024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T20:43:29.698850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5499
55.0%
0 4325
43.2%
2 169
 
1.7%
3 7
 
0.1%

링크 WKT
Text

MISSING 

Distinct5499
Distinct (%)100.0%
Missing4501
Missing (%)45.0%
Memory size156.2 KiB
2024-05-03T20:43:30.502406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length824
Mean length113.41989
Min length80

Characters and Unicode

Total characters623696
Distinct characters23
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5499 ?
Unique (%)100.0%

Sample

1st rowLINESTRING(126.9629182056037 37.538771729966086,126.96263198363484 37.538853266533884)
2nd rowLINESTRING(126.99392324838544 37.56399630739919,126.99437031258607 37.56393412781712)
3rd rowLINESTRING(127.01062484118093 37.56166584958611,127.01071397013663 37.561727631884416,127.0107513427869 37.56172533995552)
4th rowLINESTRING(127.01256850761713 37.55483891541356,127.01236155279742 37.55492933436382)
5th rowLINESTRING(126.9733716835916 37.57892829931779,126.97347812979645 37.57894244347945)
ValueCountFrequency (%)
linestring(126.99138042152967 3
 
< 0.1%
linestring(127.00157270951554 3
 
< 0.1%
linestring(127.00765737594702 3
 
< 0.1%
37.552474357645295 3
 
< 0.1%
37.56117313445876 3
 
< 0.1%
37.5756551860012 3
 
< 0.1%
37.564017730482654 3
 
< 0.1%
linestring(126.97815443694091 3
 
< 0.1%
37.58130068769916 3
 
< 0.1%
37.572118852282266 3
 
< 0.1%
Other values (19995) 20670
99.9%
2024-05-03T20:43:31.685356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 61992
9.9%
5 55352
8.9%
6 54469
8.7%
1 53722
8.6%
3 53184
8.5%
2 52787
8.5%
9 49565
7.9%
0 41793
 
6.7%
8 39977
 
6.4%
4 39561
 
6.3%
Other values (13) 121294
19.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 502402
80.6%
Uppercase Letter 54990
 
8.8%
Other Punctuation 40106
 
6.4%
Space Separator 15201
 
2.4%
Open Punctuation 5499
 
0.9%
Close Punctuation 5498
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 61992
12.3%
5 55352
11.0%
6 54469
10.8%
1 53722
10.7%
3 53184
10.6%
2 52787
10.5%
9 49565
9.9%
0 41793
8.3%
8 39977
8.0%
4 39561
7.9%
Uppercase Letter
ValueCountFrequency (%)
N 10998
20.0%
I 10998
20.0%
L 5499
10.0%
G 5499
10.0%
R 5499
10.0%
T 5499
10.0%
S 5499
10.0%
E 5499
10.0%
Other Punctuation
ValueCountFrequency (%)
. 30403
75.8%
, 9703
 
24.2%
Space Separator
ValueCountFrequency (%)
15201
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5499
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5498
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 568706
91.2%
Latin 54990
 
8.8%

Most frequent character per script

Common
ValueCountFrequency (%)
7 61992
10.9%
5 55352
9.7%
6 54469
9.6%
1 53722
9.4%
3 53184
9.4%
2 52787
9.3%
9 49565
8.7%
0 41793
7.3%
8 39977
7.0%
4 39561
7.0%
Other values (5) 66304
11.7%
Latin
ValueCountFrequency (%)
N 10998
20.0%
I 10998
20.0%
L 5499
10.0%
G 5499
10.0%
R 5499
10.0%
T 5499
10.0%
S 5499
10.0%
E 5499
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 623696
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 61992
9.9%
5 55352
8.9%
6 54469
8.7%
1 53722
8.6%
3 53184
8.5%
2 52787
8.5%
9 49565
7.9%
0 41793
 
6.7%
8 39977
 
6.4%
4 39561
 
6.3%
Other values (13) 121294
19.4%

링크 ID
Real number (ℝ)

ZEROS 

Distinct5500
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80023.089
Minimum0
Maximum282232
Zeros4501
Zeros (%)45.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T20:43:32.153694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median25056.5
Q3164262.75
95-th percentile258312.6
Maximum282232
Range282232
Interquartile range (IQR)164262.75

Descriptive statistics

Standard deviation94512.423
Coefficient of variation (CV)1.1810644
Kurtosis-0.98483143
Mean80023.089
Median Absolute Deviation (MAD)25056.5
Skewness0.73520873
Sum8.0023089 × 108
Variance8.9325982 × 109
MonotonicityNot monotonic
2024-05-03T20:43:32.635731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4501
45.0%
105635 1
 
< 0.1%
228134 1
 
< 0.1%
237750 1
 
< 0.1%
177203 1
 
< 0.1%
204947 1
 
< 0.1%
77270 1
 
< 0.1%
195768 1
 
< 0.1%
247530 1
 
< 0.1%
242207 1
 
< 0.1%
Other values (5490) 5490
54.9%
ValueCountFrequency (%)
0 4501
45.0%
76 1
 
< 0.1%
86 1
 
< 0.1%
87 1
 
< 0.1%
214 1
 
< 0.1%
236 1
 
< 0.1%
249 1
 
< 0.1%
273 1
 
< 0.1%
275 1
 
< 0.1%
299 1
 
< 0.1%
ValueCountFrequency (%)
282232 1
< 0.1%
282219 1
< 0.1%
282209 1
< 0.1%
282199 1
< 0.1%
282156 1
< 0.1%
282106 1
< 0.1%
282105 1
< 0.1%
282046 1
< 0.1%
282045 1
< 0.1%
281975 1
< 0.1%

링크 유형 코드
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)0.1%
Missing4501
Missing (%)45.0%
Infinite0
Infinite (%)0.0%
Mean1091.8862
Minimum100
Maximum1111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T20:43:33.035661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile1000
Q11111
median1111
Q31111
95-th percentile1111
Maximum1111
Range1011
Interquartile range (IQR)0

Descriptive statistics

Standard deviation60.076144
Coefficient of variation (CV)0.05502052
Kurtosis156.49883
Mean1091.8862
Median Absolute Deviation (MAD)0
Skewness-10.105202
Sum6004282
Variance3609.1431
MonotonicityNot monotonic
2024-05-03T20:43:33.451142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1111 4594
45.9%
1011 552
 
5.5%
1000 340
 
3.4%
111 6
 
0.1%
100 6
 
0.1%
1010 1
 
< 0.1%
(Missing) 4501
45.0%
ValueCountFrequency (%)
100 6
 
0.1%
111 6
 
0.1%
1000 340
 
3.4%
1010 1
 
< 0.1%
1011 552
 
5.5%
1111 4594
45.9%
ValueCountFrequency (%)
1111 4594
45.9%
1011 552
 
5.5%
1010 1
 
< 0.1%
1000 340
 
3.4%
111 6
 
0.1%
100 6
 
0.1%

시작노드 ID
Real number (ℝ)

MISSING 

Distinct5056
Distinct (%)91.9%
Missing4501
Missing (%)45.0%
Infinite0
Infinite (%)0.0%
Mean97030.149
Minimum11
Maximum215448
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T20:43:34.066468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile6510.4
Q114165
median128885
Q3148540.5
95-th percentile176986.1
Maximum215448
Range215437
Interquartile range (IQR)134375.5

Descriptive statistics

Standard deviation63391.742
Coefficient of variation (CV)0.65332005
Kurtosis-1.426285
Mean97030.149
Median Absolute Deviation (MAD)38414
Skewness-0.34248954
Sum5.3356879 × 108
Variance4.018513 × 109
MonotonicityNot monotonic
2024-05-03T20:43:34.643254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6011 3
 
< 0.1%
139224 3
 
< 0.1%
177776 3
 
< 0.1%
135560 3
 
< 0.1%
149783 3
 
< 0.1%
211535 2
 
< 0.1%
10407 2
 
< 0.1%
57845 2
 
< 0.1%
157838 2
 
< 0.1%
5785 2
 
< 0.1%
Other values (5046) 5474
54.7%
(Missing) 4501
45.0%
ValueCountFrequency (%)
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
23 1
< 0.1%
35 1
< 0.1%
36 1
< 0.1%
89 1
< 0.1%
91 1
< 0.1%
95 1
< 0.1%
103 1
< 0.1%
ValueCountFrequency (%)
215448 1
< 0.1%
215420 1
< 0.1%
214940 1
< 0.1%
214617 1
< 0.1%
214550 2
< 0.1%
214526 1
< 0.1%
214199 1
< 0.1%
214182 1
< 0.1%
214178 1
< 0.1%
214177 1
< 0.1%

종료노드 ID
Real number (ℝ)

MISSING 

Distinct5246
Distinct (%)95.4%
Missing4501
Missing (%)45.0%
Infinite0
Infinite (%)0.0%
Mean96832.587
Minimum11
Maximum215449
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T20:43:35.185059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile6535.9
Q114213.5
median128793
Q3148521.5
95-th percentile176992.4
Maximum215449
Range215438
Interquartile range (IQR)134308

Descriptive statistics

Standard deviation63317.558
Coefficient of variation (CV)0.65388688
Kurtosis-1.4323391
Mean96832.587
Median Absolute Deviation (MAD)39073
Skewness-0.3323308
Sum5.324824 × 108
Variance4.0091131 × 109
MonotonicityNot monotonic
2024-05-03T20:43:35.758113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
152449 3
 
< 0.1%
9918 3
 
< 0.1%
7055 3
 
< 0.1%
132961 3
 
< 0.1%
6421 3
 
< 0.1%
89717 3
 
< 0.1%
9765 3
 
< 0.1%
177062 2
 
< 0.1%
144199 2
 
< 0.1%
136654 2
 
< 0.1%
Other values (5236) 5472
54.7%
(Missing) 4501
45.0%
ValueCountFrequency (%)
11 1
< 0.1%
14 1
< 0.1%
25 1
< 0.1%
29 1
< 0.1%
39 1
< 0.1%
42 1
< 0.1%
81 1
< 0.1%
89 1
< 0.1%
93 1
< 0.1%
95 1
< 0.1%
ValueCountFrequency (%)
215449 1
< 0.1%
215411 1
< 0.1%
214937 1
< 0.1%
214618 1
< 0.1%
214616 1
< 0.1%
214527 1
< 0.1%
214220 1
< 0.1%
214161 1
< 0.1%
213948 1
< 0.1%
213938 1
< 0.1%

링크 길이
Real number (ℝ)

MISSING 

Distinct5154
Distinct (%)93.7%
Missing4501
Missing (%)45.0%
Infinite0
Infinite (%)0.0%
Mean41.292437
Minimum1.508
Maximum1718.332
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T20:43:36.289983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.508
5-th percentile8.0993
Q116.8465
median29.066
Q349.741
95-th percentile108.9892
Maximum1718.332
Range1716.824
Interquartile range (IQR)32.8945

Descriptive statistics

Standard deviation54.999427
Coefficient of variation (CV)1.3319492
Kurtosis312.04972
Mean41.292437
Median Absolute Deviation (MAD)14.705
Skewness13.271298
Sum227067.11
Variance3024.937
MonotonicityNot monotonic
2024-05-03T20:43:36.867017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.244 5
 
0.1%
14.028 4
 
< 0.1%
8.443 4
 
< 0.1%
13.327 4
 
< 0.1%
33.176 4
 
< 0.1%
13.5 3
 
< 0.1%
16.512 3
 
< 0.1%
14.601 3
 
< 0.1%
13.484 3
 
< 0.1%
15.02 3
 
< 0.1%
Other values (5144) 5463
54.6%
(Missing) 4501
45.0%
ValueCountFrequency (%)
1.508 1
< 0.1%
1.832 1
< 0.1%
2.247 1
< 0.1%
2.68 1
< 0.1%
2.795 1
< 0.1%
2.985 1
< 0.1%
3.142 1
< 0.1%
3.171 1
< 0.1%
3.213 1
< 0.1%
3.231 2
< 0.1%
ValueCountFrequency (%)
1718.332 1
< 0.1%
1534.393 1
< 0.1%
1091.023 1
< 0.1%
909.982 1
< 0.1%
829.333 1
< 0.1%
790.995 1
< 0.1%
610.454 1
< 0.1%
583.994 1
< 0.1%
512.809 1
< 0.1%
452.546 1
< 0.1%

시군구코드
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1111000000
3999 
1117000000
3124 
1114000000
2877 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1117000000
2nd row1114000000
3rd row1114000000
4th row1114000000
5th row1117000000

Common Values

ValueCountFrequency (%)
1111000000 3999
40.0%
1117000000 3124
31.2%
1114000000 2877
28.8%

Length

2024-05-03T20:43:37.367033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T20:43:37.708278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1111000000 3999
40.0%
1117000000 3124
31.2%
1114000000 2877
28.8%

시군구명
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
종로구
3999 
용산구
3124 
중구
2877 

Length

Max length3
Median length3
Mean length2.7123
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row용산구
2nd row중구
3rd row중구
4th row중구
5th row용산구

Common Values

ValueCountFrequency (%)
종로구 3999
40.0%
용산구 3124
31.2%
중구 2877
28.8%

Length

2024-05-03T20:43:38.081956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T20:43:38.409011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종로구 3999
40.0%
용산구 3124
31.2%
중구 2877
28.8%

읍면동코드
Real number (ℝ)

Distinct205
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1138139 × 109
Minimum1.1110101 × 109
Maximum1.1650107 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T20:43:38.800483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110101 × 109
5-th percentile1.1110114 × 109
Q11.1110173 × 109
median1.1140144 × 109
Q31.1170109 × 109
95-th percentile1.1170131 × 109
Maximum1.1650107 × 109
Range54000600
Interquartile range (IQR)5993600

Descriptive statistics

Standard deviation2901815.8
Coefficient of variation (CV)0.0026052969
Kurtosis41.083978
Mean1.1138139 × 109
Median Absolute Deviation (MAD)2997000
Skewness3.237621
Sum1.1138139 × 1013
Variance8.4205352 × 1012
MonotonicityNot monotonic
2024-05-03T20:43:39.247508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1114016200 897
 
9.0%
1111017400 381
 
3.8%
1117013100 374
 
3.7%
1117013000 352
 
3.5%
1111017500 258
 
2.6%
1117013600 252
 
2.5%
1117012900 242
 
2.4%
1117010100 237
 
2.4%
1111018300 209
 
2.1%
1114014400 170
 
1.7%
Other values (195) 6628
66.3%
ValueCountFrequency (%)
1111010100 60
0.6%
1111010200 31
0.3%
1111010300 6
 
0.1%
1111010400 33
0.3%
1111010500 19
 
0.2%
1111010600 47
0.5%
1111010700 11
 
0.1%
1111010800 31
0.3%
1111010900 43
0.4%
1111011000 46
0.5%
ValueCountFrequency (%)
1165010700 2
 
< 0.1%
1156011000 2
 
< 0.1%
1144010700 2
 
< 0.1%
1144010300 3
 
< 0.1%
1144010100 6
 
0.1%
1141010900 2
 
< 0.1%
1138010300 1
 
< 0.1%
1120010100 1
 
< 0.1%
1117013600 252
2.5%
1117013500 25
 
0.2%

읍면동명
Text

Distinct205
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-03T20:43:39.954496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.4862
Min length2

Characters and Unicode

Total characters34862
Distinct characters147
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row효창동
2nd row인현동1가
3rd row신당동
4th row을지로6가
5th row이태원동
ValueCountFrequency (%)
신당동 897
 
9.0%
창신동 381
 
3.8%
한남동 374
 
3.7%
이태원동 352
 
3.5%
숭인동 258
 
2.6%
보광동 252
 
2.5%
이촌동 242
 
2.4%
후암동 237
 
2.4%
평창동 209
 
2.1%
장충동2가 170
 
1.7%
Other values (195) 6628
66.3%
2024-05-03T20:43:41.318221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 8653
24.8%
가 2590
 
7.4%
신 1622
 
4.7%
로 1265
 
3.6%
2 923
 
2.6%
당 910
 
2.6%
창 824
 
2.4%
원 708
 
2.0%
이 661
 
1.9%
남 639
 
1.8%
Other values (137) 16067
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 32325
92.7%
Decimal Number 2537
 
7.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 8653
26.8%
가 2590
 
8.0%
신 1622
 
5.0%
로 1265
 
3.9%
당 910
 
2.8%
창 824
 
2.5%
원 708
 
2.2%
이 661
 
2.0%
남 639
 
2.0%
한 629
 
1.9%
Other values (130) 13824
42.8%
Decimal Number
ValueCountFrequency (%)
2 923
36.4%
1 610
24.0%
3 490
19.3%
4 182
 
7.2%
6 164
 
6.5%
5 157
 
6.2%
7 11
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 32325
92.7%
Common 2537
 
7.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 8653
26.8%
가 2590
 
8.0%
신 1622
 
5.0%
로 1265
 
3.9%
당 910
 
2.8%
창 824
 
2.5%
원 708
 
2.2%
이 661
 
2.0%
남 639
 
2.0%
한 629
 
1.9%
Other values (130) 13824
42.8%
Common
ValueCountFrequency (%)
2 923
36.4%
1 610
24.0%
3 490
19.3%
4 182
 
7.2%
6 164
 
6.5%
5 157
 
6.2%
7 11
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 32325
92.7%
ASCII 2537
 
7.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 8653
26.8%
가 2590
 
8.0%
신 1622
 
5.0%
로 1265
 
3.9%
당 910
 
2.8%
창 824
 
2.5%
원 708
 
2.2%
이 661
 
2.0%
남 639
 
2.0%
한 629
 
1.9%
Other values (130) 13824
42.8%
ASCII
ValueCountFrequency (%)
2 923
36.4%
1 610
24.0%
3 490
19.3%
4 182
 
7.2%
6 164
 
6.5%
5 157
 
6.2%
7 11
 
0.4%

고가도로
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5496 
<NA>
4501 
1
 
3

Length

Max length4
Median length1
Mean length2.3503
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 5496
55.0%
<NA> 4501
45.0%
1 3
 
< 0.1%

Length

2024-05-03T20:43:41.729522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T20:43:42.124499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5496
55.0%
na 4501
45.0%
1 3
 
< 0.1%

지하철네트워크
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5491 
<NA>
4501 
1
 
8

Length

Max length4
Median length1
Mean length2.3503
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 5491
54.9%
<NA> 4501
45.0%
1 8
 
0.1%

Length

2024-05-03T20:43:42.562558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T20:43:42.966966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5491
54.9%
na 4501
45.0%
1 8
 
0.1%

교량
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5485 
<NA>
4501 
1
 
14

Length

Max length4
Median length1
Mean length2.3503
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 5485
54.9%
<NA> 4501
45.0%
1 14
 
0.1%

Length

2024-05-03T20:43:43.455868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T20:43:43.788700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5485
54.9%
na 4501
45.0%
1 14
 
0.1%

터널
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5492 
<NA>
4501 
1
 
7

Length

Max length4
Median length1
Mean length2.3503
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 5492
54.9%
<NA> 4501
45.0%
1 7
 
0.1%

Length

2024-05-03T20:43:44.121749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T20:43:44.457837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5492
54.9%
na 4501
45.0%
1 7
 
0.1%

육교
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9943 
1
 
57

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 9943
99.4%
1 57
 
0.6%

Length

2024-05-03T20:43:44.925889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T20:43:45.218041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9943
99.4%
1 57
 
0.6%

횡단보도
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9440 
1
 
560

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 9440
94.4%
1 560
 
5.6%

Length

2024-05-03T20:43:45.535115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T20:43:45.877475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9440
94.4%
1 560
 
5.6%

공원,녹지
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5465 
<NA>
4501 
1
 
34

Length

Max length4
Median length1
Mean length2.3503
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 5465
54.6%
<NA> 4501
45.0%
1 34
 
0.3%

Length

2024-05-03T20:43:46.314805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T20:43:46.729267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5465
54.6%
na 4501
45.0%
1 34
 
0.3%

건물내
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5269 
<NA>
4501 
1
 
230

Length

Max length4
Median length1
Mean length2.3503
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 5269
52.7%
<NA> 4501
45.0%
1 230
 
2.3%

Length

2024-05-03T20:43:47.249950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T20:43:47.581478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5269
52.7%
na 4501
45.0%
1 230
 
2.3%

Sample

노드링크 유형노드 WKT노드 ID노드 유형 코드링크 WKT링크 ID링크 유형 코드시작노드 ID종료노드 ID링크 길이시군구코드시군구명읍면동코드읍면동명고가도로지하철네트워크교량터널육교횡단보도공원,녹지건물내
35164LINK<NA>0<NA>LINESTRING(126.9629182056037 37.538771729966086,126.96263198363484 37.538853266533884)105635111115606615606726.8661117000000용산구1117011900효창동00000000
31757LINK<NA>0<NA>LINESTRING(126.99392324838544 37.56399630739919,126.99437031258607 37.56393412781712)25498911119848696040.0961114000000중구1114016000인현동1가00000000
29175LINK<NA>0<NA>LINESTRING(127.01062484118093 37.56166584958611,127.01071397013663 37.561727631884416,127.0107513427869 37.56172533995552)3865210118229822513.7541114000000중구1114016200신당동00000000
26073NODEPOINT(127.00931862495058 37.56972059789929)2126270<NA>0<NA><NA><NA><NA>1114000000중구1114014800을지로6가<NA><NA><NA><NA>10<NA><NA>
45764NODEPOINT(126.99344978239326 37.54101206127678)1485440<NA>0<NA><NA><NA><NA>1117000000용산구1117013000이태원동<NA><NA><NA><NA>00<NA><NA>
34733NODEPOINT(126.96742733110658 37.54399705155888)1643390<NA>0<NA><NA><NA><NA>1117000000용산구1117011100청파동3가<NA><NA><NA><NA>00<NA><NA>
44090NODEPOINT(126.98768680375296 37.54346504856895)1413530<NA>0<NA><NA><NA><NA>1117000000용산구1117010200용산동2가<NA><NA><NA><NA>01<NA><NA>
11898NODEPOINT(126.96103689407173 37.59175482320546)1285010<NA>0<NA><NA><NA><NA>1111000000종로구1111018400부암동<NA><NA><NA><NA>00<NA><NA>
678NODEPOINT(126.9972317231956 37.589024408905125)1360450<NA>0<NA><NA><NA><NA>1111000000종로구1111017000명륜1가<NA><NA><NA><NA>00<NA><NA>
22371LINK<NA>0<NA>LINESTRING(127.01256850761713 37.55483891541356,127.01236155279742 37.55492933436382)776911119008900920.8591114000000중구1114016200신당동00000000
노드링크 유형노드 WKT노드 ID노드 유형 코드링크 WKT링크 ID링크 유형 코드시작노드 ID종료노드 ID링크 길이시군구코드시군구명읍면동코드읍면동명고가도로지하철네트워크교량터널육교횡단보도공원,녹지건물내
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