Overview

Dataset statistics

Number of variables18
Number of observations7722
Missing cells23783
Missing cells (%)17.1%
Duplicate rows4
Duplicate rows (%)0.1%
Total size in memory1.1 MiB
Average record size in memory149.0 B

Variable types

Numeric5
Categorical2
Text7
DateTime4

Alerts

Dataset has 4 (0.1%) duplicate rowsDuplicates
기준년도 is highly overall correlated with 시군명High correlation
높이(m) is highly overall correlated with 시군명High correlation
위도 is highly overall correlated with 시군명High correlation
경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 기준년도 and 4 other fieldsHigh correlation
원단 is highly overall correlated with 시군명High correlation
기준년도 has 1093 (14.2%) missing valuesMissing
읍면동명 has 429 (5.6%) missing valuesMissing
관리번호 has 429 (5.6%) missing valuesMissing
설치장소명 has 1260 (16.3%) missing valuesMissing
소재지도로명주소 has 4977 (64.5%) missing valuesMissing
설치일자 has 1446 (18.7%) missing valuesMissing
높이(m) has 1711 (22.2%) missing valuesMissing
펼침지름(m) has 1618 (21.0%) missing valuesMissing
당해년도운영시작일자 has 4511 (58.4%) missing valuesMissing
당해년도운영종료일자 has 4658 (60.3%) missing valuesMissing
관리기관전화번호 has 1651 (21.4%) missing valuesMissing

Reproduction

Analysis started2024-04-29 13:33:10.786395
Analysis finished2024-04-29 13:33:17.593671
Duration6.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)0.1%
Missing1093
Missing (%)14.2%
Infinite0
Infinite (%)0.0%
Mean2022.1067
Minimum2017
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size68.0 KiB
2024-04-29T22:33:17.642311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2019
Q12021
median2022
Q32024
95-th percentile2024
Maximum2024
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7820095
Coefficient of variation (CV)0.00088126384
Kurtosis-0.60021334
Mean2022.1067
Median Absolute Deviation (MAD)2
Skewness-0.62293499
Sum13404545
Variance3.1755577
MonotonicityDecreasing
2024-04-29T22:33:17.745341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2024 2127
27.5%
2022 1214
15.7%
2023 1029
13.3%
2021 854
11.1%
2020 724
 
9.4%
2019 495
 
6.4%
2018 141
 
1.8%
2017 45
 
0.6%
(Missing) 1093
14.2%
ValueCountFrequency (%)
2017 45
 
0.6%
2018 141
 
1.8%
2019 495
 
6.4%
2020 724
 
9.4%
2021 854
11.1%
2022 1214
15.7%
2023 1029
13.3%
2024 2127
27.5%
ValueCountFrequency (%)
2024 2127
27.5%
2023 1029
13.3%
2022 1214
15.7%
2021 854
11.1%
2020 724
 
9.4%
2019 495
 
6.4%
2018 141
 
1.8%
2017 45
 
0.6%

시군명
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size60.5 KiB
평택시
990 
용인시
923 
고양시
625 
안산시
593 
수원시
462 
Other values (25)
4129 

Length

Max length4
Median length3
Mean length3.0876716
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
평택시 990
 
12.8%
용인시 923
 
12.0%
고양시 625
 
8.1%
안산시 593
 
7.7%
수원시 462
 
6.0%
남양주시 333
 
4.3%
파주시 326
 
4.2%
부천시 304
 
3.9%
화성시 298
 
3.9%
오산시 279
 
3.6%
Other values (20) 2589
33.5%

Length

2024-04-29T22:33:17.876990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
평택시 990
 
12.8%
용인시 923
 
12.0%
고양시 625
 
8.1%
안산시 593
 
7.7%
수원시 462
 
6.0%
남양주시 333
 
4.3%
파주시 326
 
4.2%
부천시 304
 
3.9%
화성시 298
 
3.9%
오산시 279
 
3.6%
Other values (20) 2589
33.5%

읍면동명
Text

MISSING 

Distinct451
Distinct (%)6.2%
Missing429
Missing (%)5.6%
Memory size60.5 KiB
2024-04-29T22:33:18.176180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length3
Mean length3.3927053
Min length2

Characters and Unicode

Total characters24743
Distinct characters199
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)0.3%

Sample

1st row본오1동
2nd row본오1동
3rd row본오1동
4th row초지동
5th row초지동
ValueCountFrequency (%)
비전1동 141
 
1.9%
중앙동 140
 
1.9%
비전2동 134
 
1.8%
세교동 113
 
1.5%
회천4동 105
 
1.4%
고덕동 102
 
1.4%
동삭동 87
 
1.2%
다산1동 82
 
1.1%
초지동 76
 
1.0%
호수동 65
 
0.9%
Other values (444) 6255
85.7%
2024-04-29T22:33:18.624500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 6866
27.7%
1 1084
 
4.4%
2 965
 
3.9%
읍 585
 
2.4%
정 466
 
1.9%
산 454
 
1.8%
3 417
 
1.7%
신 412
 
1.7%
전 389
 
1.6%
천 371
 
1.5%
Other values (189) 12734
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21949
88.7%
Decimal Number 2787
 
11.3%
Space Separator 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6866
31.3%
읍 585
 
2.7%
정 466
 
2.1%
산 454
 
2.1%
신 412
 
1.9%
전 389
 
1.8%
천 371
 
1.7%
양 317
 
1.4%
중 295
 
1.3%
비 287
 
1.3%
Other values (179) 11507
52.4%
Decimal Number
ValueCountFrequency (%)
1 1084
38.9%
2 965
34.6%
3 417
 
15.0%
4 158
 
5.7%
6 70
 
2.5%
7 44
 
1.6%
5 35
 
1.3%
8 8
 
0.3%
9 6
 
0.2%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21949
88.7%
Common 2794
 
11.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6866
31.3%
읍 585
 
2.7%
정 466
 
2.1%
산 454
 
2.1%
신 412
 
1.9%
전 389
 
1.8%
천 371
 
1.7%
양 317
 
1.4%
중 295
 
1.3%
비 287
 
1.3%
Other values (179) 11507
52.4%
Common
ValueCountFrequency (%)
1 1084
38.8%
2 965
34.5%
3 417
 
14.9%
4 158
 
5.7%
6 70
 
2.5%
7 44
 
1.6%
5 35
 
1.3%
8 8
 
0.3%
7
 
0.3%
9 6
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21949
88.7%
ASCII 2794
 
11.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 6866
31.3%
읍 585
 
2.7%
정 466
 
2.1%
산 454
 
2.1%
신 412
 
1.9%
전 389
 
1.8%
천 371
 
1.7%
양 317
 
1.4%
중 295
 
1.3%
비 287
 
1.3%
Other values (179) 11507
52.4%
ASCII
ValueCountFrequency (%)
1 1084
38.8%
2 965
34.5%
3 417
 
14.9%
4 158
 
5.7%
6 70
 
2.5%
7 44
 
1.6%
5 35
 
1.3%
8 8
 
0.3%
7
 
0.3%
9 6
 
0.2%

관리번호
Text

MISSING 

Distinct6886
Distinct (%)94.4%
Missing429
Missing (%)5.6%
Memory size60.5 KiB
2024-04-29T22:33:18.954235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length13
Mean length5.8593172
Min length1

Characters and Unicode

Total characters42732
Distinct characters209
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6619 ?
Unique (%)90.8%

Sample

1st row상록-0114
2nd row상록-0115
3rd row상록-0117
4th row단원-272
5th row단원-273
ValueCountFrequency (%)
다산1동 23
 
0.3%
갈매동 22
 
0.3%
수택3동 13
 
0.2%
교문2동 11
 
0.1%
동구동 10
 
0.1%
다산2동 9
 
0.1%
인창동 9
 
0.1%
수택1동 8
 
0.1%
스마트-01 8
 
0.1%
별내동 8
 
0.1%
Other values (6842) 7315
98.4%
2024-04-29T22:33:19.406194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 5656
 
13.2%
1 3974
 
9.3%
0 3799
 
8.9%
2 3051
 
7.1%
동 2996
 
7.0%
3 1810
 
4.2%
4 1324
 
3.1%
5 1194
 
2.8%
6 1074
 
2.5%
7 990
 
2.3%
Other values (199) 16864
39.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19097
44.7%
Other Letter 17471
40.9%
Dash Punctuation 5656
 
13.2%
Uppercase Letter 167
 
0.4%
Space Separator 143
 
0.3%
Close Punctuation 77
 
0.2%
Open Punctuation 77
 
0.2%
Lowercase Letter 44
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2996
 
17.1%
본 665
 
3.8%
청 627
 
3.6%
송 445
 
2.5%
산 445
 
2.5%
수 428
 
2.4%
원 421
 
2.4%
정 417
 
2.4%
출 387
 
2.2%
안 379
 
2.2%
Other values (167) 10261
58.7%
Lowercase Letter
ValueCountFrequency (%)
a 8
18.2%
u 6
13.6%
n 5
11.4%
r 5
11.4%
p 4
9.1%
e 4
9.1%
b 2
 
4.5%
y 2
 
4.5%
l 2
 
4.5%
g 2
 
4.5%
Other values (2) 4
9.1%
Decimal Number
ValueCountFrequency (%)
1 3974
20.8%
0 3799
19.9%
2 3051
16.0%
3 1810
9.5%
4 1324
 
6.9%
5 1194
 
6.3%
6 1074
 
5.6%
7 990
 
5.2%
8 949
 
5.0%
9 932
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
S 147
88.0%
J 7
 
4.2%
M 5
 
3.0%
A 4
 
2.4%
O 2
 
1.2%
F 2
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 5656
100.0%
Space Separator
ValueCountFrequency (%)
143
100.0%
Close Punctuation
ValueCountFrequency (%)
) 77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 77
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25050
58.6%
Hangul 17471
40.9%
Latin 211
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2996
 
17.1%
본 665
 
3.8%
청 627
 
3.6%
송 445
 
2.5%
산 445
 
2.5%
수 428
 
2.4%
원 421
 
2.4%
정 417
 
2.4%
출 387
 
2.2%
안 379
 
2.2%
Other values (167) 10261
58.7%
Latin
ValueCountFrequency (%)
S 147
69.7%
a 8
 
3.8%
J 7
 
3.3%
u 6
 
2.8%
n 5
 
2.4%
r 5
 
2.4%
M 5
 
2.4%
p 4
 
1.9%
A 4
 
1.9%
e 4
 
1.9%
Other values (8) 16
 
7.6%
Common
ValueCountFrequency (%)
- 5656
22.6%
1 3974
15.9%
0 3799
15.2%
2 3051
12.2%
3 1810
 
7.2%
4 1324
 
5.3%
5 1194
 
4.8%
6 1074
 
4.3%
7 990
 
4.0%
8 949
 
3.8%
Other values (4) 1229
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25261
59.1%
Hangul 17471
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 5656
22.4%
1 3974
15.7%
0 3799
15.0%
2 3051
12.1%
3 1810
 
7.2%
4 1324
 
5.2%
5 1194
 
4.7%
6 1074
 
4.3%
7 990
 
3.9%
8 949
 
3.8%
Other values (22) 1440
 
5.7%
Hangul
ValueCountFrequency (%)
동 2996
 
17.1%
본 665
 
3.8%
청 627
 
3.6%
송 445
 
2.5%
산 445
 
2.5%
수 428
 
2.4%
원 421
 
2.4%
정 417
 
2.4%
출 387
 
2.2%
안 379
 
2.2%
Other values (167) 10261
58.7%

설치장소명
Text

MISSING 

Distinct5751
Distinct (%)89.0%
Missing1260
Missing (%)16.3%
Memory size60.5 KiB
2024-04-29T22:33:19.701923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length43
Mean length13.838131
Min length2

Characters and Unicode

Total characters89422
Distinct characters726
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5246 ?
Unique (%)81.2%

Sample

1st row본빌딩 앞
2nd row백화점약국 앞
3rd row횡단보도 앞
4th rowe편한세상선부(공원)
5th row주공10단지
ValueCountFrequency (%)
앞 2733
 
15.0%
사거리 549
 
3.0%
횡단보도 480
 
2.6%
교통섬 357
 
2.0%
건너편 320
 
1.8%
맞은편 293
 
1.6%
쪽 254
 
1.4%
정문 221
 
1.2%
삼거리 162
 
0.9%
입구 114
 
0.6%
Other values (6664) 12707
69.9%
2024-04-29T22:33:20.159249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11764
 
13.2%
앞 3115
 
3.5%
리 2891
 
3.2%
거 2416
 
2.7%
사 2249
 
2.5%
동 2015
 
2.3%
교 1973
 
2.2%
1 1802
 
2.0%
( 1657
 
1.9%
) 1655
 
1.9%
Other values (716) 57885
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65403
73.1%
Space Separator 11766
 
13.2%
Decimal Number 7046
 
7.9%
Open Punctuation 1662
 
1.9%
Close Punctuation 1660
 
1.9%
Uppercase Letter 679
 
0.8%
Dash Punctuation 608
 
0.7%
Other Punctuation 442
 
0.5%
Lowercase Letter 104
 
0.1%
Math Symbol 26
 
< 0.1%
Other values (4) 26
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 3115
 
4.8%
리 2891
 
4.4%
거 2416
 
3.7%
사 2249
 
3.4%
동 2015
 
3.1%
교 1973
 
3.0%
지 1348
 
2.1%
단 1261
 
1.9%
트 1031
 
1.6%
도 943
 
1.4%
Other values (636) 46161
70.6%
Uppercase Letter
ValueCountFrequency (%)
G 80
11.8%
S 77
11.3%
L 67
9.9%
C 63
9.3%
K 59
8.7%
A 55
 
8.1%
T 48
 
7.1%
H 30
 
4.4%
P 27
 
4.0%
B 27
 
4.0%
Other values (14) 146
21.5%
Lowercase Letter
ValueCountFrequency (%)
e 43
41.3%
s 13
 
12.5%
c 7
 
6.7%
k 7
 
6.7%
u 5
 
4.8%
g 4
 
3.8%
b 4
 
3.8%
t 4
 
3.8%
l 4
 
3.8%
o 3
 
2.9%
Other values (7) 10
 
9.6%
Decimal Number
ValueCountFrequency (%)
1 1802
25.6%
2 1214
17.2%
3 758
10.8%
0 717
 
10.2%
4 575
 
8.2%
5 489
 
6.9%
6 437
 
6.2%
7 386
 
5.5%
8 353
 
5.0%
9 315
 
4.5%
Other Punctuation
ValueCountFrequency (%)
# 255
57.7%
, 142
32.1%
. 12
 
2.7%
& 10
 
2.3%
@ 9
 
2.0%
/ 6
 
1.4%
: 4
 
0.9%
? 2
 
0.5%
· 2
 
0.5%
Other Number
ValueCountFrequency (%)
④ 1
14.3%
⑥ 1
14.3%
⑧ 1
14.3%
① 1
14.3%
② 1
14.3%
⑨ 1
14.3%
⑤ 1
14.3%
Math Symbol
ValueCountFrequency (%)
~ 19
73.1%
→ 4
 
15.4%
+ 3
 
11.5%
Space Separator
ValueCountFrequency (%)
11764
> 99.9%
　 2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 1657
99.7%
[ 5
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 1655
99.7%
] 5
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 608
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 17
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 65404
73.1%
Common 23234
 
26.0%
Latin 784
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 3115
 
4.8%
리 2891
 
4.4%
거 2416
 
3.7%
사 2249
 
3.4%
동 2015
 
3.1%
교 1973
 
3.0%
지 1348
 
2.1%
단 1261
 
1.9%
트 1031
 
1.6%
도 943
 
1.4%
Other values (637) 46162
70.6%
Latin
ValueCountFrequency (%)
G 80
 
10.2%
S 77
 
9.8%
L 67
 
8.5%
C 63
 
8.0%
K 59
 
7.5%
A 55
 
7.0%
T 48
 
6.1%
e 43
 
5.5%
H 30
 
3.8%
P 27
 
3.4%
Other values (32) 235
30.0%
Common
ValueCountFrequency (%)
11764
50.6%
1 1802
 
7.8%
( 1657
 
7.1%
) 1655
 
7.1%
2 1214
 
5.2%
3 758
 
3.3%
0 717
 
3.1%
- 608
 
2.6%
4 575
 
2.5%
5 489
 
2.1%
Other values (27) 1995
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 65403
73.1%
ASCII 24002
 
26.8%
Enclosed Alphanum 7
 
< 0.1%
None 5
 
< 0.1%
Arrows 4
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11764
49.0%
1 1802
 
7.5%
( 1657
 
6.9%
) 1655
 
6.9%
2 1214
 
5.1%
3 758
 
3.2%
0 717
 
3.0%
- 608
 
2.5%
4 575
 
2.4%
5 489
 
2.0%
Other values (58) 2763
 
11.5%
Hangul
ValueCountFrequency (%)
앞 3115
 
4.8%
리 2891
 
4.4%
거 2416
 
3.7%
사 2249
 
3.4%
동 2015
 
3.1%
교 1973
 
3.0%
지 1348
 
2.1%
단 1261
 
1.9%
트 1031
 
1.6%
도 943
 
1.4%
Other values (636) 46161
70.6%
Arrows
ValueCountFrequency (%)
→ 4
100.0%
None
ValueCountFrequency (%)
· 2
40.0%
　 2
40.0%
㈜ 1
20.0%
Enclosed Alphanum
ValueCountFrequency (%)
④ 1
14.3%
⑥ 1
14.3%
⑧ 1
14.3%
① 1
14.3%
② 1
14.3%
⑨ 1
14.3%
⑤ 1
14.3%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

소재지도로명주소
Text

MISSING 

Distinct2167
Distinct (%)78.9%
Missing4977
Missing (%)64.5%
Memory size60.5 KiB
2024-04-29T22:33:20.466276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length46
Mean length20.131148
Min length13

Characters and Unicode

Total characters55260
Distinct characters375
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1771 ?
Unique (%)64.5%

Sample

1st row경기도 안산시 상록구 오목로 46
2nd row경기도 안산시 상록구 석호로 292
3rd row경기도 안산시 상록구 해안로 1352-6
4th row경기도 안산시 상록구 부곡로 92-1
5th row경기도 안산시 상록구 부곡로 92-1
ValueCountFrequency (%)
경기도 2745
 
20.7%
수원시 327
 
2.5%
안산시 304
 
2.3%
부천시 283
 
2.1%
용인시 235
 
1.8%
고양시 232
 
1.7%
상록구 165
 
1.2%
원미구 160
 
1.2%
의정부시 148
 
1.1%
안양시 145
 
1.1%
Other values (2102) 8516
64.2%
2024-04-29T22:33:20.931483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10974
19.9%
시 2927
 
5.3%
기 2897
 
5.2%
경 2896
 
5.2%
도 2791
 
5.1%
로 2695
 
4.9%
1 1756
 
3.2%
구 1746
 
3.2%
2 1268
 
2.3%
3 887
 
1.6%
Other values (365) 24423
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34923
63.2%
Space Separator 10974
 
19.9%
Decimal Number 8433
 
15.3%
Dash Punctuation 244
 
0.4%
Close Punctuation 230
 
0.4%
Open Punctuation 230
 
0.4%
Other Punctuation 221
 
0.4%
Lowercase Letter 3
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 2927
 
8.4%
기 2897
 
8.3%
경 2896
 
8.3%
도 2791
 
8.0%
로 2695
 
7.7%
구 1746
 
5.0%
안 825
 
2.4%
산 776
 
2.2%
원 765
 
2.2%
수 695
 
2.0%
Other values (346) 15910
45.6%
Decimal Number
ValueCountFrequency (%)
1 1756
20.8%
2 1268
15.0%
3 887
10.5%
5 770
9.1%
4 759
9.0%
6 692
 
8.2%
0 656
 
7.8%
8 584
 
6.9%
7 569
 
6.7%
9 492
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 216
97.7%
. 5
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
10974
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 244
100.0%
Close Punctuation
ValueCountFrequency (%)
) 230
100.0%
Open Punctuation
ValueCountFrequency (%)
( 230
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34923
63.2%
Common 20332
36.8%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 2927
 
8.4%
기 2897
 
8.3%
경 2896
 
8.3%
도 2791
 
8.0%
로 2695
 
7.7%
구 1746
 
5.0%
안 825
 
2.4%
산 776
 
2.2%
원 765
 
2.2%
수 695
 
2.0%
Other values (346) 15910
45.6%
Common
ValueCountFrequency (%)
10974
54.0%
1 1756
 
8.6%
2 1268
 
6.2%
3 887
 
4.4%
5 770
 
3.8%
4 759
 
3.7%
6 692
 
3.4%
0 656
 
3.2%
8 584
 
2.9%
7 569
 
2.8%
Other values (6) 1417
 
7.0%
Latin
ValueCountFrequency (%)
e 3
60.0%
K 1
 
20.0%
S 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34923
63.2%
ASCII 20337
36.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10974
54.0%
1 1756
 
8.6%
2 1268
 
6.2%
3 887
 
4.4%
5 770
 
3.8%
4 759
 
3.7%
6 692
 
3.4%
0 656
 
3.2%
8 584
 
2.9%
7 569
 
2.8%
Other values (9) 1422
 
7.0%
Hangul
ValueCountFrequency (%)
시 2927
 
8.4%
기 2897
 
8.3%
경 2896
 
8.3%
도 2791
 
8.0%
로 2695
 
7.7%
구 1746
 
5.0%
안 825
 
2.4%
산 776
 
2.2%
원 765
 
2.2%
수 695
 
2.0%
Other values (346) 15910
45.6%

소재지지번주소
Text

Distinct5665
Distinct (%)73.4%
Missing0
Missing (%)0.0%
Memory size60.5 KiB
2024-04-29T22:33:21.226243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length37
Mean length20.062808
Min length13

Characters and Unicode

Total characters154925
Distinct characters426
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4448 ?
Unique (%)57.6%

Sample

1st row경기도 안산시 상록구 본오동 923번지
2nd row경기도 안산시 상록구 본오동 870번지
3rd row경기도 안산시 상록구 팔곡이동 137번지
4th row경기도 안산시 단원구 초지동 665-2
5th row경기도 안산시 단원구 초지동 665-2
ValueCountFrequency (%)
경기도 7722
 
21.5%
평택시 990
 
2.8%
용인시 921
 
2.6%
고양시 625
 
1.7%
안산시 593
 
1.7%
수원시 462
 
1.3%
기흥구 386
 
1.1%
수지구 341
 
0.9%
남양주시 333
 
0.9%
단원구 332
 
0.9%
Other values (5995) 23229
64.6%
2024-04-29T22:33:21.688847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28212
18.2%
기 8171
 
5.3%
시 7945
 
5.1%
동 7866
 
5.1%
도 7828
 
5.1%
경 7738
 
5.0%
1 6018
 
3.9%
- 4003
 
2.6%
구 3593
 
2.3%
2 3363
 
2.2%
Other values (416) 70188
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92338
59.6%
Decimal Number 30004
 
19.4%
Space Separator 28212
 
18.2%
Dash Punctuation 4003
 
2.6%
Close Punctuation 145
 
0.1%
Open Punctuation 145
 
0.1%
Uppercase Letter 39
 
< 0.1%
Lowercase Letter 30
 
< 0.1%
Other Punctuation 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 8171
 
8.8%
시 7945
 
8.6%
동 7866
 
8.5%
도 7828
 
8.5%
경 7738
 
8.4%
구 3593
 
3.9%
지 3089
 
3.3%
번 2299
 
2.5%
양 2075
 
2.2%
산 1955
 
2.1%
Other values (374) 39779
43.1%
Uppercase Letter
ValueCountFrequency (%)
K 7
17.9%
S 6
15.4%
C 5
12.8%
E 4
10.3%
D 3
7.7%
M 2
 
5.1%
P 2
 
5.1%
L 2
 
5.1%
A 2
 
5.1%
G 1
 
2.6%
Other values (5) 5
12.8%
Lowercase Letter
ValueCountFrequency (%)
e 16
53.3%
m 2
 
6.7%
h 2
 
6.7%
l 2
 
6.7%
s 2
 
6.7%
g 1
 
3.3%
t 1
 
3.3%
a 1
 
3.3%
c 1
 
3.3%
u 1
 
3.3%
Decimal Number
ValueCountFrequency (%)
1 6018
20.1%
2 3363
11.2%
5 2830
9.4%
3 2799
9.3%
6 2779
9.3%
7 2689
9.0%
4 2611
8.7%
8 2395
 
8.0%
0 2263
 
7.5%
9 2257
 
7.5%
Other Punctuation
ValueCountFrequency (%)
. 5
55.6%
, 4
44.4%
Space Separator
ValueCountFrequency (%)
28212
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4003
100.0%
Close Punctuation
ValueCountFrequency (%)
) 145
100.0%
Open Punctuation
ValueCountFrequency (%)
( 145
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92338
59.6%
Common 62518
40.4%
Latin 69
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 8171
 
8.8%
시 7945
 
8.6%
동 7866
 
8.5%
도 7828
 
8.5%
경 7738
 
8.4%
구 3593
 
3.9%
지 3089
 
3.3%
번 2299
 
2.5%
양 2075
 
2.2%
산 1955
 
2.1%
Other values (374) 39779
43.1%
Latin
ValueCountFrequency (%)
e 16
23.2%
K 7
 
10.1%
S 6
 
8.7%
C 5
 
7.2%
E 4
 
5.8%
D 3
 
4.3%
m 2
 
2.9%
M 2
 
2.9%
h 2
 
2.9%
P 2
 
2.9%
Other values (16) 20
29.0%
Common
ValueCountFrequency (%)
28212
45.1%
1 6018
 
9.6%
- 4003
 
6.4%
2 3363
 
5.4%
5 2830
 
4.5%
3 2799
 
4.5%
6 2779
 
4.4%
7 2689
 
4.3%
4 2611
 
4.2%
8 2395
 
3.8%
Other values (6) 4819
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92338
59.6%
ASCII 62587
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28212
45.1%
1 6018
 
9.6%
- 4003
 
6.4%
2 3363
 
5.4%
5 2830
 
4.5%
3 2799
 
4.5%
6 2779
 
4.4%
7 2689
 
4.3%
4 2611
 
4.2%
8 2395
 
3.8%
Other values (32) 4888
 
7.8%
Hangul
ValueCountFrequency (%)
기 8171
 
8.8%
시 7945
 
8.6%
동 7866
 
8.5%
도 7828
 
8.5%
경 7738
 
8.4%
구 3593
 
3.9%
지 3089
 
3.3%
번 2299
 
2.5%
양 2075
 
2.2%
산 1955
 
2.1%
Other values (374) 39779
43.1%

설치일자
Date

MISSING 

Distinct350
Distinct (%)5.6%
Missing1446
Missing (%)18.7%
Memory size60.5 KiB
Minimum2017-03-31 00:00:00
Maximum2023-10-24 00:00:00
2024-04-29T22:33:21.847354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:21.999580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

높이(m)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)0.4%
Missing1711
Missing (%)22.2%
Infinite0
Infinite (%)0.0%
Mean3.5487872
Minimum2.2
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size68.0 KiB
2024-04-29T22:33:22.125559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.2
5-th percentile3
Q13.4
median3.65
Q33.65
95-th percentile5
Maximum6
Range3.8
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation0.4714405
Coefficient of variation (CV)0.13284553
Kurtosis4.0284329
Mean3.5487872
Median Absolute Deviation (MAD)0.15
Skewness0.8226046
Sum21331.76
Variance0.22225615
MonotonicityNot monotonic
2024-04-29T22:33:22.261730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
3.65 1873
24.3%
3.5 834
10.8%
3.4 660
 
8.5%
3.7 520
 
6.7%
3.0 405
 
5.2%
3.1 325
 
4.2%
5.0 306
 
4.0%
4.0 221
 
2.9%
3.6 219
 
2.8%
3.3 162
 
2.1%
Other values (12) 486
 
6.3%
(Missing) 1711
22.2%
ValueCountFrequency (%)
2.2 7
 
0.1%
2.35 91
 
1.2%
2.4 153
 
2.0%
2.8 23
 
0.3%
3.0 405
5.2%
3.03 2
 
< 0.1%
3.1 325
4.2%
3.2 25
 
0.3%
3.3 162
 
2.1%
3.4 660
8.5%
ValueCountFrequency (%)
6.0 5
 
0.1%
5.0 306
 
4.0%
4.4 2
 
< 0.1%
4.0 221
 
2.9%
3.8 68
 
0.9%
3.75 72
 
0.9%
3.7 520
 
6.7%
3.65 1873
24.3%
3.6 219
 
2.8%
3.55 36
 
0.5%

펼침지름(m)
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)0.3%
Missing1618
Missing (%)21.0%
Infinite0
Infinite (%)0.0%
Mean4.0365662
Minimum0.3
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size68.0 KiB
2024-04-29T22:33:22.392057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile3
Q14
median4
Q34.6
95-th percentile5
Maximum35
Range34.7
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation0.7987146
Coefficient of variation (CV)0.19786981
Kurtosis368.75854
Mean4.0365662
Median Absolute Deviation (MAD)0
Skewness9.5257409
Sum24639.2
Variance0.63794502
MonotonicityNot monotonic
2024-04-29T22:33:22.501928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
4.0 3105
40.2%
5.0 1454
18.8%
3.0 1206
 
15.6%
3.5 192
 
2.5%
5.4 68
 
0.9%
2.8 22
 
0.3%
4.6 12
 
0.2%
3.4 10
 
0.1%
2.5 10
 
0.1%
3.7 10
 
0.1%
Other values (6) 15
 
0.2%
(Missing) 1618
21.0%
ValueCountFrequency (%)
0.3 1
 
< 0.1%
2.0 4
 
0.1%
2.4 2
 
< 0.1%
2.5 10
 
0.1%
2.8 22
 
0.3%
3.0 1206
 
15.6%
3.4 10
 
0.1%
3.5 192
 
2.5%
3.7 10
 
0.1%
4.0 3105
40.2%
ValueCountFrequency (%)
35.0 1
 
< 0.1%
5.4 68
 
0.9%
5.0 1454
18.8%
4.7 1
 
< 0.1%
4.6 12
 
0.2%
4.4 6
 
0.1%
4.0 3105
40.2%
3.7 10
 
0.1%
3.5 192
 
2.5%
3.4 10
 
0.1%

원단
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size60.5 KiB
메쉬
2766 
<NA>
2349 
매쉬
1574 
메시
593 
PE매쉬
 
166
Other values (12)
 
274

Length

Max length10
Median length2
Mean length2.6993007
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
메쉬 2766
35.8%
<NA> 2349
30.4%
매쉬 1574
20.4%
메시 593
 
7.7%
PE매쉬 166
 
2.1%
아크릴 110
 
1.4%
방수 99
 
1.3%
폴리카보네이트 15
 
0.2%
UV발수천 12
 
0.2%
아크릴방수 12
 
0.2%
Other values (7) 26
 
0.3%

Length

2024-04-29T22:33:22.619132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
메쉬 2766
35.8%
na 2349
30.4%
매쉬 1578
20.4%
메시 593
 
7.7%
pe매쉬 166
 
2.1%
아크릴 110
 
1.4%
방수 99
 
1.3%
폴리카보네이트 15
 
0.2%
아크릴방수 12
 
0.2%
uv발수천 12
 
0.2%
Other values (9) 34
 
0.4%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct6931
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.398884
Minimum36.957774
Maximum38.185008
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size68.0 KiB
2024-04-29T22:33:22.748639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.957774
5-th percentile37.002529
Q137.25401
median37.349607
Q337.622934
95-th percentile37.814857
Maximum38.185008
Range1.227234
Interquartile range (IQR)0.36892341

Descriptive statistics

Standard deviation0.24200506
Coefficient of variation (CV)0.0064709165
Kurtosis-0.6304861
Mean37.398884
Median Absolute Deviation (MAD)0.15566317
Skewness0.23581393
Sum288794.18
Variance0.058566447
MonotonicityNot monotonic
2024-04-29T22:33:22.885364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.55187241 10
 
0.1%
37.72600617 9
 
0.1%
37.66973352 9
 
0.1%
37.81781467 8
 
0.1%
37.73167334 7
 
0.1%
37.395852 6
 
0.1%
37.65571433 6
 
0.1%
37.64404174 6
 
0.1%
37.66490916 6
 
0.1%
37.19930281 6
 
0.1%
Other values (6921) 7649
99.1%
ValueCountFrequency (%)
36.957774 1
< 0.1%
36.957862 1
< 0.1%
36.958316 1
< 0.1%
36.958505 1
< 0.1%
36.959121 1
< 0.1%
36.959274 1
< 0.1%
36.961583 1
< 0.1%
36.961739 1
< 0.1%
36.961861 1
< 0.1%
36.96199 1
< 0.1%
ValueCountFrequency (%)
38.185008 1
< 0.1%
38.15132 1
< 0.1%
38.1040733 1
< 0.1%
38.1034401 1
< 0.1%
38.0972458 1
< 0.1%
38.0971321 1
< 0.1%
38.096603 1
< 0.1%
38.096572 1
< 0.1%
38.093708 1
< 0.1%
38.091591 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct6931
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.00849
Minimum126.5965
Maximum127.75224
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size68.0 KiB
2024-04-29T22:33:23.051354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.5965
5-th percentile126.74425
Q1126.85193
median127.05184
Q3127.11385
95-th percentile127.24346
Maximum127.75224
Range1.1557411
Interquartile range (IQR)0.26191902

Descriptive statistics

Standard deviation0.17569095
Coefficient of variation (CV)0.0013833008
Kurtosis0.70307046
Mean127.00849
Median Absolute Deviation (MAD)0.1083294
Skewness0.36222248
Sum980759.57
Variance0.030867309
MonotonicityNot monotonic
2024-04-29T22:33:23.427838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.2034465 10
 
0.1%
126.7626395 9
 
0.1%
126.7608436 9
 
0.1%
127.0879012 8
 
0.1%
126.7358799 7
 
0.1%
127.0986129 7
 
0.1%
126.7280131 6
 
0.1%
126.8911196 6
 
0.1%
126.932705 6
 
0.1%
126.6271124 6
 
0.1%
Other values (6921) 7648
99.0%
ValueCountFrequency (%)
126.5964996 1
 
< 0.1%
126.597813 1
 
< 0.1%
126.6031135 1
 
< 0.1%
126.6033138 1
 
< 0.1%
126.6044198 1
 
< 0.1%
126.6224717 1
 
< 0.1%
126.6240355 3
< 0.1%
126.6244158 2
< 0.1%
126.6249454 2
< 0.1%
126.6267563 1
 
< 0.1%
ValueCountFrequency (%)
127.7522407 2
< 0.1%
127.6878 1
< 0.1%
127.6639611 1
< 0.1%
127.663 1
< 0.1%
127.6543425 1
< 0.1%
127.6538008 1
< 0.1%
127.6507066 1
< 0.1%
127.6502812 1
< 0.1%
127.6500198 1
< 0.1%
127.6465514 1
< 0.1%

당해년도운영시작일자
Date

MISSING 

Distinct28
Distinct (%)0.9%
Missing4511
Missing (%)58.4%
Memory size60.5 KiB
Minimum2019-05-24 00:00:00
Maximum2024-06-01 00:00:00
2024-04-29T22:33:23.540872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:23.658805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

당해년도운영종료일자
Date

MISSING 

Distinct10
Distinct (%)0.3%
Missing4658
Missing (%)60.3%
Memory size60.5 KiB
Minimum2019-09-30 00:00:00
Maximum2024-09-30 00:00:00
2024-04-29T22:33:23.757971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:23.854373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)

관리기관명
Text

Distinct148
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size60.5 KiB
2024-04-29T22:33:24.082277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length8.548692
Min length2

Characters and Unicode

Total characters66013
Distinct characters163
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)0.3%

Sample

1st row상록구청 도로교통과
2nd row상록구청 도로교통과
3rd row상록구청 도로교통과
4th row단원구청 도로교통과
5th row단원구청 도로교통과
ValueCountFrequency (%)
경기도 1246
 
8.7%
안전건설과 795
 
5.5%
건설과 683
 
4.8%
필랜드 651
 
4.5%
평택시청 603
 
4.2%
도로관리과 603
 
4.2%
도로교통과 593
 
4.1%
수원시 462
 
3.2%
건설도시과 387
 
2.7%
단원구청 332
 
2.3%
Other values (153) 7980
55.7%
2024-04-29T22:33:24.466145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6613
 
10.0%
시 4886
 
7.4%
과 4510
 
6.8%
청 4210
 
6.4%
도 3200
 
4.8%
건 2713
 
4.1%
설 2421
 
3.7%
구 2290
 
3.5%
안 1903
 
2.9%
전 1608
 
2.4%
Other values (153) 31659
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58541
88.7%
Space Separator 6613
 
10.0%
Decimal Number 290
 
0.4%
Close Punctuation 247
 
0.4%
Open Punctuation 247
 
0.4%
Other Symbol 75
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4886
 
8.3%
과 4510
 
7.7%
청 4210
 
7.2%
도 3200
 
5.5%
건 2713
 
4.6%
설 2421
 
4.1%
구 2290
 
3.9%
안 1903
 
3.3%
전 1608
 
2.7%
정 1307
 
2.2%
Other values (140) 29493
50.4%
Decimal Number
ValueCountFrequency (%)
1 126
43.4%
2 84
29.0%
3 25
 
8.6%
7 14
 
4.8%
6 13
 
4.5%
4 11
 
3.8%
8 8
 
2.8%
9 6
 
2.1%
5 3
 
1.0%
Space Separator
ValueCountFrequency (%)
6613
100.0%
Close Punctuation
ValueCountFrequency (%)
) 247
100.0%
Open Punctuation
ValueCountFrequency (%)
( 247
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58616
88.8%
Common 7397
 
11.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4886
 
8.3%
과 4510
 
7.7%
청 4210
 
7.2%
도 3200
 
5.5%
건 2713
 
4.6%
설 2421
 
4.1%
구 2290
 
3.9%
안 1903
 
3.2%
전 1608
 
2.7%
정 1307
 
2.2%
Other values (141) 29568
50.4%
Common
ValueCountFrequency (%)
6613
89.4%
) 247
 
3.3%
( 247
 
3.3%
1 126
 
1.7%
2 84
 
1.1%
3 25
 
0.3%
7 14
 
0.2%
6 13
 
0.2%
4 11
 
0.1%
8 8
 
0.1%
Other values (2) 9
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58541
88.7%
ASCII 7397
 
11.2%
None 75
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6613
89.4%
) 247
 
3.3%
( 247
 
3.3%
1 126
 
1.7%
2 84
 
1.1%
3 25
 
0.3%
7 14
 
0.2%
6 13
 
0.2%
4 11
 
0.1%
8 8
 
0.1%
Other values (2) 9
 
0.1%
Hangul
ValueCountFrequency (%)
시 4886
 
8.3%
과 4510
 
7.7%
청 4210
 
7.2%
도 3200
 
5.5%
건 2713
 
4.6%
설 2421
 
4.1%
구 2290
 
3.9%
안 1903
 
3.3%
전 1608
 
2.7%
정 1307
 
2.2%
Other values (140) 29493
50.4%
None
ValueCountFrequency (%)
㈜ 75
100.0%

관리기관전화번호
Text

MISSING 

Distinct97
Distinct (%)1.6%
Missing1651
Missing (%)21.4%
Memory size60.5 KiB
2024-04-29T22:33:24.676163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.382639
Min length12

Characters and Unicode

Total characters75175
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

Unique6 ?
Unique (%)0.1%

Sample

1st row031-481-5579
2nd row031-481-5579
3rd row031-481-5579
4th row031-481-6295
5th row031-481-6295
ValueCountFrequency (%)
031-8024-4775 603
 
9.9%
031-481-6295 332
 
5.5%
031-940-5712 326
 
5.4%
031-8075-5298 289
 
4.8%
031-8036-7798 279
 
4.6%
031-828-4964 272
 
4.5%
031-481-5579 261
 
4.3%
031-8024-6493 261
 
4.3%
031-310-2439 252
 
4.2%
031-390-0409 208
 
3.4%
Other values (87) 2988
49.2%
2024-04-29T22:33:25.023094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 12142
16.2%
0 10736
14.3%
3 8604
11.4%
1 7785
10.4%
8 6452
8.6%
4 6024
8.0%
2 5820
7.7%
5 5136
6.8%
9 4633
 
6.2%
7 4483
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63033
83.8%
Dash Punctuation 12142
 
16.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10736
17.0%
3 8604
13.6%
1 7785
12.4%
8 6452
10.2%
4 6024
9.6%
2 5820
9.2%
5 5136
8.1%
9 4633
7.4%
7 4483
7.1%
6 3360
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 12142
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75175
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 12142
16.2%
0 10736
14.3%
3 8604
11.4%
1 7785
10.4%
8 6452
8.6%
4 6024
8.0%
2 5820
7.7%
5 5136
6.8%
9 4633
 
6.2%
7 4483
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 12142
16.2%
0 10736
14.3%
3 8604
11.4%
1 7785
10.4%
8 6452
8.6%
4 6024
8.0%
2 5820
7.7%
5 5136
6.8%
9 4633
 
6.2%
7 4483
 
6.0%

데이터기준일자
Date

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size60.5 KiB
Minimum2020-03-10 00:00:00
Maximum2024-04-01 00:00:00
2024-04-29T22:33:25.145323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:25.249031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

Interactions

2024-04-29T22:33:16.312476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:14.206459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:14.759514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:15.276114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:15.789366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:16.408772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:14.356868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:14.855870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:15.368685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:15.926487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:16.506032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:14.461119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:14.953144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:15.474018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:16.026070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:16.599055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:14.561543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:15.058450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:15.568726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:16.122821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:16.693502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:14.669635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:15.172938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:15.669637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:33:16.222845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-29T22:33:25.343520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명높이(m)펼침지름(m)원단위도경도당해년도운영시작일자당해년도운영종료일자관리기관전화번호데이터기준일자
기준년도1.0000.9580.4460.2680.5460.6250.5180.9750.8610.9650.924
시군명0.9581.0000.8880.6150.9100.9890.9660.9780.9611.0001.000
높이(m)0.4460.8881.0000.2870.8530.5750.4610.8460.6740.9360.835
펼침지름(m)0.2680.6150.2871.0000.3070.4030.3030.6220.3650.6470.424
원단0.5460.9100.8530.3071.0000.7450.6380.8440.8170.9520.863
위도0.6250.9890.5750.4030.7451.0000.6140.9000.9020.9910.927
경도0.5180.9660.4610.3030.6380.6141.0000.8750.8910.9680.929
당해년도운영시작일자0.9750.9780.8460.6220.8440.9000.8751.0001.0000.9830.980
당해년도운영종료일자0.8610.9610.6740.3650.8170.9020.8911.0001.0000.9840.941
관리기관전화번호0.9651.0000.9360.6470.9520.9910.9680.9830.9841.0001.000
데이터기준일자0.9241.0000.8350.4240.8630.9270.9290.9800.9411.0001.000
2024-04-29T22:33:25.473306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명원단
시군명1.0000.571
원단0.5711.000
2024-04-29T22:33:25.560459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도높이(m)펼침지름(m)위도경도시군명원단
기준년도1.0000.074-0.018-0.2500.1290.6910.296
높이(m)0.0741.0000.152-0.165-0.2650.6150.482
펼침지름(m)-0.0180.1521.000-0.102-0.2650.3570.175
위도-0.250-0.165-0.1021.000-0.2370.8280.408
경도0.129-0.265-0.265-0.2371.0000.7190.312
시군명0.6910.6150.3570.8280.7191.0000.571
원단0.2960.4820.1750.4080.3120.5711.000

Missing values

2024-04-29T22:33:17.016220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-29T22:33:17.244401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-04-29T22:33:17.444898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

기준년도시군명읍면동명관리번호설치장소명소재지도로명주소소재지지번주소설치일자높이(m)펼침지름(m)원단위도경도당해년도운영시작일자당해년도운영종료일자관리기관명관리기관전화번호데이터기준일자
0<NA>안산시본오1동상록-0114본빌딩 앞경기도 안산시 상록구 오목로 46경기도 안산시 상록구 본오동 923번지2021-07-013.655.0메시37.290177126.863092<NA><NA>상록구청 도로교통과031-481-55792024-03-04
1<NA>안산시본오1동상록-0115백화점약국 앞경기도 안산시 상록구 석호로 292경기도 안산시 상록구 본오동 870번지2021-07-013.655.0메시37.293391126.863089<NA><NA>상록구청 도로교통과031-481-55792024-03-04
2<NA>안산시본오1동상록-0117횡단보도 앞경기도 안산시 상록구 해안로 1352-6경기도 안산시 상록구 팔곡이동 137번지2021-07-013.655.0메시37.296396126.888845<NA><NA>상록구청 도로교통과031-481-55792024-03-04
3<NA>안산시초지동단원-272e편한세상선부(공원)<NA>경기도 안산시 단원구 초지동 665-22021-06-013.655.0메시37.321721126.819762<NA><NA>단원구청 도로교통과031-481-62952024-03-04
4<NA>안산시초지동단원-273주공10단지<NA>경기도 안산시 단원구 초지동 665-22021-06-013.655.0메시37.321668126.81972<NA><NA>단원구청 도로교통과031-481-62952024-03-04
5<NA>안산시부곡동상록-1007대흥빌딩사거리경기도 안산시 상록구 부곡로 92-1경기도 안산시 상록구 부곡동 624번지2021-07-013.655.0메시37.330357126.862083<NA><NA>상록구청 도로교통과031-481-55792024-03-04
6<NA>안산시부곡동상록-1009대흥빌딩사거리경기도 안산시 상록구 부곡로 92-1경기도 안산시 상록구 부곡동 624번지2021-07-013.655.0메시37.330346126.862129<NA><NA>상록구청 도로교통과031-481-55792024-03-04
7<NA>안산시부곡동상록-1011부곡종합시장사거리경기도 안산시 상록구 성호로 258경기도 안산시 상록구 부곡동 685-11번지2021-07-013.655.0메시37.326303126.858099<NA><NA>상록구청 도로교통과031-481-55792024-03-04
8<NA>안산시부곡동상록-1012제일CC사거리 부곡고등학교 육교 앞<NA>경기도 안산시 상록구 부곡동 708-52021-08-013.655.0메시37.331777126.858547<NA><NA>상록구청 도로교통과031-481-55792024-03-04
9<NA>안산시월피동상록-1101삼일초등학교경기도 안산시 상록구 월피로 42경기도 안산시 상록구 월피동 448-1번지2018-05-203.655.0메시37.332719126.850325<NA><NA>상록구청 도로교통과031-481-55792024-03-04
기준년도시군명읍면동명관리번호설치장소명소재지도로명주소소재지지번주소설치일자높이(m)펼침지름(m)원단위도경도당해년도운영시작일자당해년도운영종료일자관리기관명관리기관전화번호데이터기준일자
77122017구리시교문1동교문1동 2017-012교문사거리(모델하우스 방향) 교통섬<NA>경기도 구리시 교문동 274-4번지2017-08-223.54.0방수37.60067127.1304662022-05-13<NA>구리시청031-550-21622023-02-03
77132017구리시교문1동교문1동 2017-013구리시청 정문경기도 구리시 아차산로 439경기도 구리시 교문동 390-1번지2017-08-223.54.0방수37.59456127.1309682022-05-13<NA>구리시청031-550-21622023-02-03
77142017구리시교문2동교문2동 2017-014도림삼거리(파파존스 건물) 교통섬경기도 구리시 장자대로 3경기도 구리시 교문동 807-11번지2017-08-223.54.0방수37.587686127.1304262022-05-13<NA>구리시청031-550-21622023-02-03
77152017구리시교문2동교문2동 2017-015장자1사거리(교문2동 주민센터 앞)경기도 구리시 장자대로 34경기도 구리시 교문동 821번지2017-08-223.55.0방수37.587522127.1344572022-05-13<NA>구리시청031-550-21622023-02-03
77162017구리시수택1동수택1동 2017-017중앙예식장 사거리(LG 유플러스 앞)경기도 구리시 경춘로 188경기도 구리시 수택동 370번지2017-08-223.33.0방수37.60042127.1360792022-05-13<NA>구리시청031-550-21622023-02-03
77172017구리시수택1동수택1동 2017-018검배사거리 토평주공APT 앞경기도 구리시 벌말로 226경기도 구리시 수택동 879번지 토평주공아파트2017-08-223.54.0방수37.59446127.1511092022-05-13<NA>구리시청031-550-21622023-02-03
77182017구리시수택2동수택2동 2017-021GS 마트 앞경기도 구리시 검배로 70경기도 구리시 수택동 488-6번지2017-08-223.55.0방수37.596013127.1461492022-05-13<NA>구리시청031-550-21622023-02-03
77192017구리시수택3동수택3동 2017-022벌말삼거리(와인 아울렛) 교통섬<NA>경기도 구리시 토평동 623-14번지2017-08-223.54.0방수37.586522127.1478692022-05-13<NA>구리시청031-550-21622023-02-03
77202017구리시수택3동수택3동 2017-025토평마을e편한APT 앞 횡단보도<NA>경기도 구리시 토평동 955-2번지2017-08-223.55.0방수37.587118127.1428742022-05-13<NA>구리시청031-550-21622023-02-03
77212017용인시구갈동구갈-1<NA><NA>경기도 용인시 기흥구 구갈동 5052017-08-173.13.0매쉬37.275967127.116175<NA><NA>㈜썬세이드<NA>2023-02-21

Duplicate rows

Most frequently occurring

기준년도시군명읍면동명관리번호설치장소명소재지도로명주소소재지지번주소설치일자높이(m)펼침지름(m)원단위도경도당해년도운영시작일자당해년도운영종료일자관리기관명관리기관전화번호데이터기준일자# duplicates
02023군포시<NA><NA>중앙공원사거리(KT 앞 교통섬)<NA>경기도 군포시 산본동 1175<NA><NA><NA><NA>37.362082126.931787<NA><NA>군포시청031-390-04092024-02-272
12023군포시<NA><NA>중앙공원사거리(이마트 앞 교통섬)<NA>경기도 군포시 산본동 1175<NA><NA><NA><NA>37.362082126.931787<NA><NA>군포시청031-390-04092024-02-272
22023하남시감일동감일동-S01메인사거리 로데오프라자 앞<NA>경기도 하남시 감일동 306-66<NA><NA><NA><NA>37.507989127.152683<NA><NA>경기도 하남시청031-790-64562023-06-092
32023하남시감일동감일동-S05CU 감일스윗씨티점 앞<NA>경기도 하남시 감이동 288-7<NA><NA><NA><NA>37.501019127.163039<NA><NA>경기도 하남시청031-790-64562023-06-092