Overview

Dataset statistics

Number of variables32
Number of observations478
Missing cells1834
Missing cells (%)12.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory123.8 KiB
Average record size in memory265.3 B

Variable types

Categorical17
Text6
Numeric9

Dataset

Description경기도 터널 방재시설 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=DMVZSKBEDP076AYLIXL232541233&infSeq=1

Alerts

자동화재탐지설비 is highly imbalanced (69.8%)Imbalance
비상방송설비 is highly imbalanced (50.5%)Imbalance
정보표지판 is highly imbalanced (59.2%)Imbalance
진입차단시설 is highly imbalanced (63.3%)Imbalance
거리표시유도등 is highly imbalanced (64.0%)Imbalance
피난대피소비상주차대 is highly imbalanced (57.7%)Imbalance
제연설비 is highly imbalanced (61.9%)Imbalance
연결송수관 is highly imbalanced (73.8%)Imbalance
비상콘센트 is highly imbalanced (65.2%)Imbalance
무정전설비 is highly imbalanced (51.4%)Imbalance
영상유고감지설비 is highly imbalanced (67.7%)Imbalance
위도 has 50 (10.5%) missing valuesMissing
경도 has 50 (10.5%) missing valuesMissing
위치 has 73 (15.3%) missing valuesMissing
총길이 has 73 (15.3%) missing valuesMissing
총폭 has 73 (15.3%) missing valuesMissing
유효폭 has 214 (44.8%) missing valuesMissing
높이 has 74 (15.5%) missing valuesMissing
준공년도 has 73 (15.3%) missing valuesMissing
소화전 has 96 (20.1%) missing valuesMissing
옥내소화전 has 380 (79.5%) missing valuesMissing
비상경보설비 has 275 (57.5%) missing valuesMissing
긴급전화 has 261 (54.6%) missing valuesMissing
비상조명 has 140 (29.3%) missing valuesMissing

Reproduction

Analysis started2023-12-10 22:15:04.754725
Analysis finished2023-12-10 22:15:05.274697
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도로종류
Categorical

Distinct7
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
고속국도
214 
일반국도
101 
시도
81 
지방도
44 
<NA>
22 
Other values (2)
 
16

Length

Max length7
Median length4
Mean length3.6589958
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row일반국도
2nd row일반국도
3rd row일반국도
4th row시도
5th row시도

Common Values

ValueCountFrequency (%)
고속국도 214
44.8%
일반국도 101
21.1%
시도 81
 
16.9%
지방도 44
 
9.2%
<NA> 22
 
4.6%
국가지원지방도 15
 
3.1%
군도 1
 
0.2%

Length

2023-12-11T07:15:05.349449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:15:05.457219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고속국도 214
44.8%
일반국도 101
21.1%
시도 81
 
16.9%
지방도 44
 
9.2%
na 22
 
4.6%
국가지원지방도 15
 
3.1%
군도 1
 
0.2%

노선명
Text

Distinct54
Distinct (%)11.3%
Missing2
Missing (%)0.4%
Memory size3.9 KiB
2023-12-11T07:15:05.627059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6.2710084
Min length2

Characters and Unicode

Total characters2985
Distinct characters47
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

Unique9 ?
Unique (%)1.9%

Sample

1st row일반국도38호선
2nd row일반국도38호선
3rd row일반국도38호선
4th row시도
5th row시도
ValueCountFrequency (%)
시도 81
16.4%
고속국도400호선 41
 
8.3%
고속국도171호선 32
 
6.5%
3호선 27
 
5.5%
고속국도60호선 23
 
4.7%
고속국도17호선 22
 
4.5%
고속국도 18
 
3.6%
43호선 18
 
3.6%
영동고속국도 16
 
3.2%
중부내륙고속국도 14
 
2.8%
Other values (45) 202
40.9%
2023-12-11T07:15:05.906832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 367
12.3%
호 328
11.0%
선 328
11.0%
국 241
 
8.1%
고 214
 
7.2%
속 214
 
7.2%
1 149
 
5.0%
0 143
 
4.8%
3 128
 
4.3%
4 104
 
3.5%
Other values (37) 769
25.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2210
74.0%
Decimal Number 757
 
25.4%
Space Separator 18
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 367
16.6%
호 328
14.8%
선 328
14.8%
국 241
10.9%
고 214
9.7%
속 214
9.7%
시 81
 
3.7%
지 74
 
3.3%
방 59
 
2.7%
중 25
 
1.1%
Other values (26) 279
12.6%
Decimal Number
ValueCountFrequency (%)
1 149
19.7%
0 143
18.9%
3 128
16.9%
4 104
13.7%
7 88
11.6%
6 52
 
6.9%
2 35
 
4.6%
8 25
 
3.3%
9 20
 
2.6%
5 13
 
1.7%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2210
74.0%
Common 775
 
26.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 367
16.6%
호 328
14.8%
선 328
14.8%
국 241
10.9%
고 214
9.7%
속 214
9.7%
시 81
 
3.7%
지 74
 
3.3%
방 59
 
2.7%
중 25
 
1.1%
Other values (26) 279
12.6%
Common
ValueCountFrequency (%)
1 149
19.2%
0 143
18.5%
3 128
16.5%
4 104
13.4%
7 88
11.4%
6 52
 
6.7%
2 35
 
4.5%
8 25
 
3.2%
9 20
 
2.6%
18
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2210
74.0%
ASCII 775
 
26.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 367
16.6%
호 328
14.8%
선 328
14.8%
국 241
10.9%
고 214
9.7%
속 214
9.7%
시 81
 
3.7%
지 74
 
3.3%
방 59
 
2.7%
중 25
 
1.1%
Other values (26) 279
12.6%
ASCII
ValueCountFrequency (%)
1 149
19.2%
0 143
18.5%
3 128
16.5%
4 104
13.4%
7 88
11.4%
6 52
 
6.7%
2 35
 
4.5%
8 25
 
3.2%
9 20
 
2.6%
18
 
2.3%

시설명
Text

Distinct476
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-11T07:15:06.164296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.9665272
Min length4

Characters and Unicode

Total characters3808
Distinct characters201
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

Unique474 ?
Unique (%)99.2%

Sample

1st row대덕터널(하)
2nd row비봉터널(상)
3rd row비봉터널(하)
4th row충훈터널(상,하)
5th row호암2터널(상,하)
ValueCountFrequency (%)
동탄ic 3
 
0.6%
산성터널 2
 
0.4%
서판교터널 2
 
0.4%
운중터널 2
 
0.4%
초막터널 1
 
0.2%
쌍학터널 1
 
0.2%
판교ic지하차도(부산 1
 
0.2%
지하차도 1
 
0.2%
ramp-c 1
 
0.2%
수기지하차도(하 1
 
0.2%
Other values (469) 469
96.9%
2023-12-11T07:15:06.567955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 440
 
11.6%
널 440
 
11.6%
( 407
 
10.7%
) 407
 
10.7%
하 134
 
3.5%
상 94
 
2.5%
산 80
 
2.1%
양 71
 
1.9%
방 48
 
1.3%
지 46
 
1.2%
Other values (191) 1641
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2860
75.1%
Open Punctuation 407
 
10.7%
Close Punctuation 407
 
10.7%
Decimal Number 109
 
2.9%
Uppercase Letter 16
 
0.4%
Space Separator 6
 
0.2%
Other Punctuation 2
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 440
 
15.4%
널 440
 
15.4%
하 134
 
4.7%
상 94
 
3.3%
산 80
 
2.8%
양 71
 
2.5%
방 48
 
1.7%
지 46
 
1.6%
도 45
 
1.6%
봉 43
 
1.5%
Other values (171) 1419
49.6%
Uppercase Letter
ValueCountFrequency (%)
C 5
31.2%
I 4
25.0%
B 1
 
6.2%
X 1
 
6.2%
O 1
 
6.2%
M 1
 
6.2%
R 1
 
6.2%
A 1
 
6.2%
P 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 39
35.8%
2 33
30.3%
3 20
18.3%
4 8
 
7.3%
0 5
 
4.6%
5 4
 
3.7%
Open Punctuation
ValueCountFrequency (%)
( 407
100.0%
Close Punctuation
ValueCountFrequency (%)
) 407
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2860
75.1%
Common 932
 
24.5%
Latin 16
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 440
 
15.4%
널 440
 
15.4%
하 134
 
4.7%
상 94
 
3.3%
산 80
 
2.8%
양 71
 
2.5%
방 48
 
1.7%
지 46
 
1.6%
도 45
 
1.6%
봉 43
 
1.5%
Other values (171) 1419
49.6%
Common
ValueCountFrequency (%)
( 407
43.7%
) 407
43.7%
1 39
 
4.2%
2 33
 
3.5%
3 20
 
2.1%
4 8
 
0.9%
6
 
0.6%
0 5
 
0.5%
5 4
 
0.4%
, 2
 
0.2%
Latin
ValueCountFrequency (%)
C 5
31.2%
I 4
25.0%
B 1
 
6.2%
X 1
 
6.2%
O 1
 
6.2%
M 1
 
6.2%
R 1
 
6.2%
A 1
 
6.2%
P 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2860
75.1%
ASCII 948
 
24.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 440
 
15.4%
널 440
 
15.4%
하 134
 
4.7%
상 94
 
3.3%
산 80
 
2.8%
양 71
 
2.5%
방 48
 
1.7%
지 46
 
1.6%
도 45
 
1.6%
봉 43
 
1.5%
Other values (171) 1419
49.6%
ASCII
ValueCountFrequency (%)
( 407
42.9%
) 407
42.9%
1 39
 
4.1%
2 33
 
3.5%
3 20
 
2.1%
4 8
 
0.8%
6
 
0.6%
C 5
 
0.5%
0 5
 
0.5%
5 4
 
0.4%
Other values (10) 14
 
1.5%

위도
Real number (ℝ)

MISSING 

Distinct337
Distinct (%)78.7%
Missing50
Missing (%)10.5%
Infinite0
Infinite (%)0.0%
Mean37.455391
Minimum35.787776
Maximum38.043983
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2023-12-11T07:15:06.692159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.787776
5-th percentile37.068933
Q137.309422
median37.421604
Q337.656984
95-th percentile37.866157
Maximum38.043983
Range2.2562072
Interquartile range (IQR)0.34756175

Descriptive statistics

Standard deviation0.26057308
Coefficient of variation (CV)0.0069568912
Kurtosis7.3220752
Mean37.455391
Median Absolute Deviation (MAD)0.15629873
Skewness-1.1989886
Sum16030.907
Variance0.06789833
MonotonicityNot monotonic
2023-12-11T07:15:06.805247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.275065 4
 
0.8%
37.411851 4
 
0.8%
37.397846 4
 
0.8%
37.334684 3
 
0.6%
37.313408 3
 
0.6%
37.242834 3
 
0.6%
37.517231 3
 
0.6%
37.868179 3
 
0.6%
37.372168 2
 
0.4%
37.649098 2
 
0.4%
Other values (327) 397
83.1%
(Missing) 50
 
10.5%
ValueCountFrequency (%)
35.7877757907573 2
0.4%
36.4895039789924 2
0.4%
36.940683 1
0.2%
36.940909 1
0.2%
36.975075 2
0.4%
36.997821997032 2
0.4%
37.022147 1
0.2%
37.022418 1
0.2%
37.022421 1
0.2%
37.02256 1
0.2%
ValueCountFrequency (%)
38.043983 1
0.2%
38.041073 1
0.2%
38.00364 1
0.2%
38.002049 1
0.2%
37.998317 1
0.2%
37.955643 1
0.2%
37.946027 1
0.2%
37.935858 1
0.2%
37.935443 1
0.2%
37.933205 1
0.2%

경도
Real number (ℝ)

MISSING 

Distinct337
Distinct (%)78.7%
Missing50
Missing (%)10.5%
Infinite0
Infinite (%)0.0%
Mean127.14014
Minimum126.49945
Maximum127.8309
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2023-12-11T07:15:06.919832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.49945
5-th percentile126.8362
Q1127.02369
median127.11935
Q3127.26392
95-th percentile127.52349
Maximum127.8309
Range1.3314539
Interquartile range (IQR)0.24023

Descriptive statistics

Standard deviation0.21583522
Coefficient of variation (CV)0.0016976167
Kurtosis0.76439952
Mean127.14014
Median Absolute Deviation (MAD)0.12896696
Skewness0.39286663
Sum54415.979
Variance0.046584841
MonotonicityNot monotonic
2023-12-11T07:15:07.039864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.177851 4
 
0.8%
127.506053 4
 
0.8%
127.519849 4
 
0.8%
126.87904 3
 
0.6%
127.023694 3
 
0.6%
127.279057 3
 
0.6%
127.18073 3
 
0.6%
127.142153 3
 
0.6%
126.9033 2
 
0.4%
127.441518 2
 
0.4%
Other values (327) 397
83.1%
(Missing) 50
 
10.5%
ValueCountFrequency (%)
126.499449904896 2
0.4%
126.601637 1
0.2%
126.602004 1
0.2%
126.602802948931 2
0.4%
126.703658 1
0.2%
126.703837 1
0.2%
126.708065 1
0.2%
126.717959 1
0.2%
126.718374 1
0.2%
126.723569 1
0.2%
ValueCountFrequency (%)
127.830903767836 2
0.4%
127.755581 1
0.2%
127.752309 1
0.2%
127.73588 2
0.4%
127.732527 1
0.2%
127.731651 1
0.2%
127.723183 1
0.2%
127.677087 1
0.2%
127.578465894922 2
0.4%
127.574294 1
0.2%

위치
Text

MISSING 

Distinct221
Distinct (%)54.6%
Missing73
Missing (%)15.3%
Memory size3.9 KiB
2023-12-11T07:15:07.266257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length14.402469
Min length10

Characters and Unicode

Total characters5833
Distinct characters188
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

Unique112 ?
Unique (%)27.7%

Sample

1st row경기도 안성시 신모산동
2nd row경기도 안성시 당왕동
3rd row경기도 안성시 당왕동
4th row경기도 안양시 만안구 석수동
5th row경기도 안양시 만안구 석수동
ValueCountFrequency (%)
경기도 395
25.9%
용인시 50
 
3.3%
성남시 44
 
2.9%
남양주시 43
 
2.8%
광주시 32
 
2.1%
가평군 21
 
1.4%
기흥구 21
 
1.4%
처인구 18
 
1.2%
중원구 18
 
1.2%
여주시 17
 
1.1%
Other values (316) 867
56.8%
2023-12-11T07:15:07.612072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1133
19.4%
기 421
 
7.2%
도 410
 
7.0%
경 395
 
6.8%
시 373
 
6.4%
동 252
 
4.3%
리 192
 
3.3%
면 129
 
2.2%
구 126
 
2.2%
주 124
 
2.1%
Other values (178) 2278
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4700
80.6%
Space Separator 1133
 
19.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 421
 
9.0%
도 410
 
8.7%
경 395
 
8.4%
시 373
 
7.9%
동 252
 
5.4%
리 192
 
4.1%
면 129
 
2.7%
구 126
 
2.7%
주 124
 
2.6%
남 113
 
2.4%
Other values (177) 2165
46.1%
Space Separator
ValueCountFrequency (%)
1133
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4700
80.6%
Common 1133
 
19.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 421
 
9.0%
도 410
 
8.7%
경 395
 
8.4%
시 373
 
7.9%
동 252
 
5.4%
리 192
 
4.1%
면 129
 
2.7%
구 126
 
2.7%
주 124
 
2.6%
남 113
 
2.4%
Other values (177) 2165
46.1%
Common
ValueCountFrequency (%)
1133
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4700
80.6%
ASCII 1133
 
19.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1133
100.0%
Hangul
ValueCountFrequency (%)
기 421
 
9.0%
도 410
 
8.7%
경 395
 
8.4%
시 373
 
7.9%
동 252
 
5.4%
리 192
 
4.1%
면 129
 
2.7%
구 126
 
2.7%
주 124
 
2.6%
남 113
 
2.4%
Other values (177) 2165
46.1%

총길이
Real number (ℝ)

MISSING 

Distinct302
Distinct (%)74.6%
Missing73
Missing (%)15.3%
Infinite0
Infinite (%)0.0%
Mean766.22395
Minimum4.5
Maximum4885
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2023-12-11T07:15:08.033729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.5
5-th percentile127.6
Q1320
median502
Q3925
95-th percentile2158.6
Maximum4885
Range4880.5
Interquartile range (IQR)605

Descriptive statistics

Standard deviation734.92397
Coefficient of variation (CV)0.95915035
Kurtosis7.8413874
Mean766.22395
Median Absolute Deviation (MAD)246
Skewness2.4807243
Sum310320.7
Variance540113.24
MonotonicityNot monotonic
2023-12-11T07:15:08.196790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
180.0 6
 
1.3%
550.0 4
 
0.8%
370.0 4
 
0.8%
900.0 4
 
0.8%
495.0 4
 
0.8%
680.0 4
 
0.8%
310.0 4
 
0.8%
390.0 4
 
0.8%
500.0 4
 
0.8%
750.0 3
 
0.6%
Other values (292) 364
76.2%
(Missing) 73
 
15.3%
ValueCountFrequency (%)
4.5 1
0.2%
40.0 1
0.2%
43.0 1
0.2%
45.0 1
0.2%
57.0 1
0.2%
58.0 1
0.2%
60.0 2
0.4%
62.0 1
0.2%
72.0 1
0.2%
80.0 2
0.4%
ValueCountFrequency (%)
4885.0 1
0.2%
4848.0 1
0.2%
3997.0 1
0.2%
3993.0 1
0.2%
3665.0 1
0.2%
3605.0 1
0.2%
3483.5 1
0.2%
3310.0 1
0.2%
3295.0 1
0.2%
2998.0 1
0.2%

총폭
Real number (ℝ)

MISSING 

Distinct88
Distinct (%)21.7%
Missing73
Missing (%)15.3%
Infinite0
Infinite (%)0.0%
Mean12.217284
Minimum3.3
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2023-12-11T07:15:08.339685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.3
5-th percentile7
Q19.6
median11
Q313.3
95-th percentile20.38
Maximum52
Range48.7
Interquartile range (IQR)3.7

Descriptive statistics

Standard deviation5.2084706
Coefficient of variation (CV)0.42631984
Kurtosis18.625629
Mean12.217284
Median Absolute Deviation (MAD)1.8
Skewness3.3635036
Sum4948
Variance27.128166
MonotonicityNot monotonic
2023-12-11T07:15:08.470834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.0 36
 
7.5%
7.0 23
 
4.8%
12.5 21
 
4.4%
10.7 18
 
3.8%
10.5 16
 
3.3%
17.6 15
 
3.1%
9.0 13
 
2.7%
11.3 12
 
2.5%
11.5 10
 
2.1%
13.3 10
 
2.1%
Other values (78) 231
48.3%
(Missing) 73
 
15.3%
ValueCountFrequency (%)
3.3 1
 
0.2%
3.5 1
 
0.2%
6.0 2
 
0.4%
6.5 6
 
1.3%
7.0 23
4.8%
7.2 5
 
1.0%
7.3 1
 
0.2%
7.5 1
 
0.2%
8.0 8
 
1.7%
8.4 1
 
0.2%
ValueCountFrequency (%)
52.0 2
0.4%
34.0 1
0.2%
33.7 1
0.2%
32.5 1
0.2%
32.0 2
0.4%
28.8 2
0.4%
26.5 1
0.2%
26.0 1
0.2%
25.0 1
0.2%
23.0 1
0.2%

유효폭
Real number (ℝ)

MISSING 

Distinct65
Distinct (%)24.6%
Missing214
Missing (%)44.8%
Infinite0
Infinite (%)0.0%
Mean10.698864
Minimum3.3
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2023-12-11T07:15:08.601402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.3
5-th percentile6.5
Q17.075
median9
Q311
95-th percentile21
Maximum52
Range48.7
Interquartile range (IQR)3.925

Descriptive statistics

Standard deviation5.9894869
Coefficient of variation (CV)0.55982458
Kurtosis18.940868
Mean10.698864
Median Absolute Deviation (MAD)2
Skewness3.7391804
Sum2824.5
Variance35.873953
MonotonicityNot monotonic
2023-12-11T07:15:08.731211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.0 44
 
9.2%
10.5 15
 
3.1%
9.0 14
 
2.9%
6.5 14
 
2.9%
8.5 13
 
2.7%
9.5 11
 
2.3%
8.0 9
 
1.9%
11.0 8
 
1.7%
16.7 8
 
1.7%
10.0 7
 
1.5%
Other values (55) 121
25.3%
(Missing) 214
44.8%
ValueCountFrequency (%)
3.3 1
 
0.2%
3.5 1
 
0.2%
5.8 1
 
0.2%
6.0 3
 
0.6%
6.5 14
 
2.9%
6.7 1
 
0.2%
6.8 1
 
0.2%
7.0 44
9.2%
7.1 1
 
0.2%
7.2 3
 
0.6%
ValueCountFrequency (%)
52.0 2
0.4%
34.0 1
0.2%
33.7 1
0.2%
32.0 2
0.4%
30.5 1
0.2%
28.8 1
0.2%
26.0 1
0.2%
23.0 1
0.2%
22.4 1
0.2%
21.4 1
0.2%

높이
Real number (ℝ)

MISSING 

Distinct51
Distinct (%)12.6%
Missing74
Missing (%)15.5%
Infinite0
Infinite (%)0.0%
Mean8.0480198
Minimum0
Maximum390
Zeros2
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2023-12-11T07:15:08.859689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.8
Q16.6
median7
Q37.9
95-th percentile9.1
Maximum390
Range390
Interquartile range (IQR)1.3

Descriptive statistics

Standard deviation19.10049
Coefficient of variation (CV)2.3733154
Kurtosis399.71159
Mean8.0480198
Median Absolute Deviation (MAD)0.5
Skewness19.939849
Sum3251.4
Variance364.82871
MonotonicityNot monotonic
2023-12-11T07:15:08.997399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.7 44
 
9.2%
7.3 41
 
8.6%
8.0 34
 
7.1%
7.0 34
 
7.1%
6.5 29
 
6.1%
4.8 23
 
4.8%
7.4 21
 
4.4%
6.6 18
 
3.8%
7.8 16
 
3.3%
9.1 13
 
2.7%
Other values (41) 131
27.4%
(Missing) 74
15.5%
ValueCountFrequency (%)
0.0 2
 
0.4%
4.0 6
 
1.3%
4.5 6
 
1.3%
4.7 4
 
0.8%
4.8 23
4.8%
5.0 5
 
1.0%
5.3 2
 
0.4%
5.6 1
 
0.2%
5.7 2
 
0.4%
6.0 2
 
0.4%
ValueCountFrequency (%)
390.0 1
0.2%
14.9 1
0.2%
12.6 1
0.2%
12.0 1
0.2%
11.4 1
0.2%
11.0 1
0.2%
10.0 1
0.2%
9.6 1
0.2%
9.5 1
0.2%
9.3 1
0.2%

도로관리청
Categorical

Distinct40
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
한국도로공사
68 
의정부국토관리청
58 
수원국토관리청
53 
경수고속도로㈜
32 
화성광주고속도로㈜
31 
Other values (35)
236 

Length

Max length11
Median length9
Mean length6.4539749
Min length3

Unique

Unique3 ?
Unique (%)0.6%

Sample

1st row안성시
2nd row안성시
3rd row안성시
4th row안양시
5th row안양시

Common Values

ValueCountFrequency (%)
한국도로공사 68
14.2%
의정부국토관리청 58
12.1%
수원국토관리청 53
11.1%
경수고속도로㈜ 32
 
6.7%
화성광주고속도로㈜ 31
 
6.5%
성남시 28
 
5.9%
경기도 28
 
5.9%
서울춘천고속도로㈜ 23
 
4.8%
용인시기흥구 17
 
3.6%
서울고속도로㈜ 12
 
2.5%
Other values (30) 128
26.8%

Length

2023-12-11T07:15:09.156266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한국도로공사 68
14.2%
의정부국토관리청 58
12.1%
수원국토관리청 53
11.1%
경수고속도로㈜ 32
 
6.7%
화성광주고속도로㈜ 31
 
6.5%
성남시 28
 
5.9%
경기도 28
 
5.9%
서울춘천고속도로㈜ 23
 
4.8%
용인시기흥구 17
 
3.6%
수도권서부고속도로㈜ 12
 
2.5%
Other values (30) 128
26.8%

준공년도
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)8.1%
Missing73
Missing (%)15.3%
Infinite0
Infinite (%)0.0%
Mean2008.716
Minimum1978
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2023-12-11T07:15:09.285300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1978
5-th percentile1993.2
Q12005
median2009
Q32016
95-th percentile2020
Maximum2021
Range43
Interquartile range (IQR)11

Descriptive statistics

Standard deviation8.533328
Coefficient of variation (CV)0.0042481505
Kurtosis0.11443806
Mean2008.716
Median Absolute Deviation (MAD)7
Skewness-0.77960057
Sum813530
Variance72.817687
MonotonicityNot monotonic
2023-12-11T07:15:09.451641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
2009 65
13.6%
2017 44
 
9.2%
2018 24
 
5.0%
2012 21
 
4.4%
2016 19
 
4.0%
2006 18
 
3.8%
2011 16
 
3.3%
2020 16
 
3.3%
2008 13
 
2.7%
1998 13
 
2.7%
Other values (23) 156
32.6%
(Missing) 73
15.3%
ValueCountFrequency (%)
1978 1
 
0.2%
1980 1
 
0.2%
1987 8
1.7%
1991 6
1.3%
1992 1
 
0.2%
1993 4
 
0.8%
1994 11
2.3%
1995 6
1.3%
1996 8
1.7%
1997 4
 
0.8%
ValueCountFrequency (%)
2021 10
 
2.1%
2020 16
 
3.3%
2019 4
 
0.8%
2018 24
5.0%
2017 44
9.2%
2016 19
4.0%
2015 11
 
2.3%
2014 13
 
2.7%
2013 3
 
0.6%
2012 21
4.4%

소화전
Text

MISSING 

Distinct77
Distinct (%)20.2%
Missing96
Missing (%)20.1%
Memory size3.9 KiB
2023-12-11T07:15:09.686361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.9267016
Min length1

Characters and Unicode

Total characters736
Distinct characters12
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

Unique21 ?
Unique (%)5.5%

Sample

1st row15
2nd row17
3rd row18
4th row40
5th row18
ValueCountFrequency (%)
16 30
 
7.9%
18 23
 
6.0%
10 21
 
5.5%
20 19
 
5.0%
12 18
 
4.7%
30 18
 
4.7%
8 14
 
3.7%
14 14
 
3.7%
38 11
 
2.9%
11 11
 
2.9%
Other values (67) 203
53.1%
2023-12-11T07:15:10.056523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 169
23.0%
2 120
16.3%
0 88
12.0%
8 83
11.3%
6 79
10.7%
4 79
10.7%
3 54
 
7.3%
5 28
 
3.8%
7 25
 
3.4%
9 9
 
1.2%
Other values (2) 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 734
99.7%
Other Letter 2
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 169
23.0%
2 120
16.3%
0 88
12.0%
8 83
11.3%
6 79
10.8%
4 79
10.8%
3 54
 
7.4%
5 28
 
3.8%
7 25
 
3.4%
9 9
 
1.2%
Other Letter
ValueCountFrequency (%)
설 1
50.0%
치 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 734
99.7%
Hangul 2
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 169
23.0%
2 120
16.3%
0 88
12.0%
8 83
11.3%
6 79
10.8%
4 79
10.8%
3 54
 
7.4%
5 28
 
3.8%
7 25
 
3.4%
9 9
 
1.2%
Hangul
ValueCountFrequency (%)
설 1
50.0%
치 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 734
99.7%
Hangul 2
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 169
23.0%
2 120
16.3%
0 88
12.0%
8 83
11.3%
6 79
10.8%
4 79
10.8%
3 54
 
7.4%
5 28
 
3.8%
7 25
 
3.4%
9 9
 
1.2%
Hangul
ValueCountFrequency (%)
설 1
50.0%
치 1
50.0%

옥내소화전
Real number (ℝ)

MISSING 

Distinct48
Distinct (%)49.0%
Missing380
Missing (%)79.5%
Infinite0
Infinite (%)0.0%
Mean38.071429
Minimum1
Maximum102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2023-12-11T07:15:10.208564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q124
median33
Q351
95-th percentile75.2
Maximum102
Range101
Interquartile range (IQR)27

Descriptive statistics

Standard deviation21.40539
Coefficient of variation (CV)0.56224289
Kurtosis0.40546205
Mean38.071429
Median Absolute Deviation (MAD)12
Skewness0.82690305
Sum3731
Variance458.19072
MonotonicityNot monotonic
2023-12-11T07:15:10.341228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
20 7
 
1.5%
29 6
 
1.3%
25 5
 
1.0%
66 4
 
0.8%
36 4
 
0.8%
21 3
 
0.6%
47 3
 
0.6%
33 3
 
0.6%
28 3
 
0.6%
34 3
 
0.6%
Other values (38) 57
 
11.9%
(Missing) 380
79.5%
ValueCountFrequency (%)
1 1
 
0.2%
5 2
 
0.4%
8 3
0.6%
9 2
 
0.4%
10 1
 
0.2%
14 1
 
0.2%
15 1
 
0.2%
20 7
1.5%
21 3
0.6%
23 3
0.6%
ValueCountFrequency (%)
102 1
0.2%
101 1
0.2%
84 1
0.2%
83 1
0.2%
82 1
0.2%
74 2
0.4%
72 1
0.2%
69 1
0.2%
68 1
0.2%
67 2
0.4%

비상경보설비
Text

MISSING 

Distinct54
Distinct (%)26.6%
Missing275
Missing (%)57.5%
Memory size3.9 KiB
2023-12-11T07:15:10.510051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.9655172
Min length1

Characters and Unicode

Total characters399
Distinct characters12
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

Unique17 ?
Unique (%)8.4%

Sample

1st row설치
2nd row설치
3rd row설치
4th row설치
5th row설치
ValueCountFrequency (%)
설치 34
 
16.7%
15 11
 
5.4%
19 10
 
4.9%
20 8
 
3.9%
11 8
 
3.9%
12 7
 
3.4%
18 7
 
3.4%
1 7
 
3.4%
29 7
 
3.4%
16 6
 
3.0%
Other values (44) 98
48.3%
2023-12-11T07:15:10.816139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 92
23.1%
2 55
13.8%
3 39
9.8%
설 34
 
8.5%
치 34
 
8.5%
6 29
 
7.3%
5 27
 
6.8%
4 26
 
6.5%
0 20
 
5.0%
9 18
 
4.5%
Other values (2) 25
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 331
83.0%
Other Letter 68
 
17.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 92
27.8%
2 55
16.6%
3 39
11.8%
6 29
 
8.8%
5 27
 
8.2%
4 26
 
7.9%
0 20
 
6.0%
9 18
 
5.4%
8 17
 
5.1%
7 8
 
2.4%
Other Letter
ValueCountFrequency (%)
설 34
50.0%
치 34
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 331
83.0%
Hangul 68
 
17.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 92
27.8%
2 55
16.6%
3 39
11.8%
6 29
 
8.8%
5 27
 
8.2%
4 26
 
7.9%
0 20
 
6.0%
9 18
 
5.4%
8 17
 
5.1%
7 8
 
2.4%
Hangul
ValueCountFrequency (%)
설 34
50.0%
치 34
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 331
83.0%
Hangul 68
 
17.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 92
27.8%
2 55
16.6%
3 39
11.8%
6 29
 
8.8%
5 27
 
8.2%
4 26
 
7.9%
0 20
 
6.0%
9 18
 
5.4%
8 17
 
5.1%
7 8
 
2.4%
Hangul
ValueCountFrequency (%)
설 34
50.0%
치 34
50.0%

자동화재탐지설비
Categorical

IMBALANCE 

Distinct22
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
377 
1
40 
설치
 
28
20
 
6
2
 
4
Other values (17)
 
23

Length

Max length4
Median length4
Mean length3.4832636
Min length1

Unique

Unique13 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
78.9%
1 40
 
8.4%
설치 28
 
5.9%
20 6
 
1.3%
2 4
 
0.8%
11 4
 
0.8%
12 2
 
0.4%
18 2
 
0.4%
17 2
 
0.4%
66 1
 
0.2%
Other values (12) 12
 
2.5%

Length

2023-12-11T07:15:10.941293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 377
78.9%
1 40
 
8.4%
설치 28
 
5.9%
20 6
 
1.3%
2 4
 
0.8%
11 4
 
0.8%
12 2
 
0.4%
18 2
 
0.4%
17 2
 
0.4%
52 1
 
0.2%
Other values (12) 12
 
2.5%

비상방송설비
Categorical

IMBALANCE 

Distinct47
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
275 
1
60 
설치
36 
20
 
7
12
 
7
Other values (42)
93 

Length

Max length4
Median length4
Mean length3.0041841
Min length1

Unique

Unique20 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 275
57.5%
1 60
 
12.6%
설치 36
 
7.5%
20 7
 
1.5%
12 7
 
1.5%
10 6
 
1.3%
16 6
 
1.3%
19 4
 
0.8%
15 4
 
0.8%
11 4
 
0.8%
Other values (37) 69
 
14.4%

Length

2023-12-11T07:15:11.048604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 275
57.5%
1 60
 
12.6%
설치 36
 
7.5%
12 7
 
1.5%
20 7
 
1.5%
10 6
 
1.3%
16 6
 
1.3%
37 4
 
0.8%
18 4
 
0.8%
5 4
 
0.8%
Other values (37) 69
 
14.4%

긴급전화
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)11.1%
Missing261
Missing (%)54.6%
Infinite0
Infinite (%)0.0%
Mean6.0737327
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2023-12-11T07:15:11.165674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q38
95-th percentile16.2
Maximum25
Range24
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.7262174
Coefficient of variation (CV)0.7781405
Kurtosis2.8636856
Mean6.0737327
Median Absolute Deviation (MAD)2
Skewness1.7428718
Sum1318
Variance22.337131
MonotonicityNot monotonic
2023-12-11T07:15:11.294754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
4 42
 
8.8%
3 38
 
7.9%
2 34
 
7.1%
6 17
 
3.6%
5 16
 
3.3%
8 11
 
2.3%
9 10
 
2.1%
7 8
 
1.7%
15 6
 
1.3%
10 6
 
1.3%
Other values (14) 29
 
6.1%
(Missing) 261
54.6%
ValueCountFrequency (%)
1 4
 
0.8%
2 34
7.1%
3 38
7.9%
4 42
8.8%
5 16
 
3.3%
6 17
3.6%
7 8
 
1.7%
8 11
 
2.3%
9 10
 
2.1%
10 6
 
1.3%
ValueCountFrequency (%)
25 1
 
0.2%
23 1
 
0.2%
22 1
 
0.2%
21 2
 
0.4%
20 2
 
0.4%
19 1
 
0.2%
18 2
 
0.4%
17 1
 
0.2%
16 1
 
0.2%
15 6
1.3%

CCTV
Categorical

Distinct20
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
158 
1
66 
3
44 
4
42 
2
37 
Other values (15)
131 

Length

Max length4
Median length1
Mean length2.0732218
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row3
2nd row3
3rd row3
4th row10
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 158
33.1%
1 66
13.8%
3 44
 
9.2%
4 42
 
8.8%
2 37
 
7.7%
5 31
 
6.5%
6 21
 
4.4%
8 19
 
4.0%
7 16
 
3.3%
13 10
 
2.1%
Other values (10) 34
 
7.1%

Length

2023-12-11T07:15:11.428678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 158
33.1%
1 66
13.8%
3 44
 
9.2%
4 42
 
8.8%
2 37
 
7.7%
5 31
 
6.5%
6 21
 
4.4%
8 19
 
4.0%
7 16
 
3.3%
13 10
 
2.1%
Other values (10) 34
 
7.1%

재방송설비
Categorical

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
1
201 
<NA>
184 
설치
83 
2
 
8
8
 
2

Length

Max length4
Median length2
Mean length2.3284519
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 201
42.1%
<NA> 184
38.5%
설치 83
17.4%
2 8
 
1.7%
8 2
 
0.4%

Length

2023-12-11T07:15:11.565493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:15:11.717997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 201
42.1%
na 184
38.5%
설치 83
17.4%
2 8
 
1.7%
8 2
 
0.4%

정보표지판
Categorical

IMBALANCE 

Distinct15
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
331 
1
83 
2
 
21
4
 
12
3
 
8
Other values (10)
 
23

Length

Max length4
Median length4
Mean length3.0983264
Min length1

Unique

Unique4 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 331
69.2%
1 83
 
17.4%
2 21
 
4.4%
4 12
 
2.5%
3 8
 
1.7%
5 5
 
1.0%
6 4
 
0.8%
설치 4
 
0.8%
14 2
 
0.4%
8 2
 
0.4%
Other values (5) 6
 
1.3%

Length

2023-12-11T07:15:11.832035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 331
69.2%
1 83
 
17.4%
2 21
 
4.4%
4 12
 
2.5%
3 8
 
1.7%
5 5
 
1.0%
6 4
 
0.8%
설치 4
 
0.8%
14 2
 
0.4%
8 2
 
0.4%
Other values (5) 6
 
1.3%

진입차단시설
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
411 
설치
47 
1
 
17
2
 
3

Length

Max length4
Median length4
Mean length3.6778243
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 411
86.0%
설치 47
 
9.8%
1 17
 
3.6%
2 3
 
0.6%

Length

2023-12-11T07:15:11.955198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:15:12.043672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 411
86.0%
설치 47
 
9.8%
1 17
 
3.6%
2 3
 
0.6%

비상조명
Text

MISSING 

Distinct131
Distinct (%)38.8%
Missing140
Missing (%)29.3%
Memory size3.9 KiB
2023-12-11T07:15:12.268822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.3106509
Min length1

Characters and Unicode

Total characters781
Distinct characters12
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

Unique63 ?
Unique (%)18.6%

Sample

1st row설치
2nd row설치
3rd row설치
4th row설치
5th row설치
ValueCountFrequency (%)
설치 83
24.6%
40 7
 
2.1%
41 7
 
2.1%
140 6
 
1.8%
27 6
 
1.8%
28 5
 
1.5%
30 5
 
1.5%
62 4
 
1.2%
42 4
 
1.2%
36 4
 
1.2%
Other values (121) 207
61.2%
2023-12-11T07:15:12.658501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 126
16.1%
2 91
11.7%
설 83
10.6%
치 83
10.6%
4 75
9.6%
0 57
7.3%
5 55
7.0%
6 54
6.9%
3 47
 
6.0%
8 43
 
5.5%
Other values (2) 67
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 615
78.7%
Other Letter 166
 
21.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 126
20.5%
2 91
14.8%
4 75
12.2%
0 57
9.3%
5 55
8.9%
6 54
8.8%
3 47
 
7.6%
8 43
 
7.0%
7 35
 
5.7%
9 32
 
5.2%
Other Letter
ValueCountFrequency (%)
설 83
50.0%
치 83
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 615
78.7%
Hangul 166
 
21.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 126
20.5%
2 91
14.8%
4 75
12.2%
0 57
9.3%
5 55
8.9%
6 54
8.8%
3 47
 
7.6%
8 43
 
7.0%
7 35
 
5.7%
9 32
 
5.2%
Hangul
ValueCountFrequency (%)
설 83
50.0%
치 83
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 615
78.7%
Hangul 166
 
21.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 126
20.5%
2 91
14.8%
4 75
12.2%
0 57
9.3%
5 55
8.9%
6 54
8.8%
3 47
 
7.6%
8 43
 
7.0%
7 35
 
5.7%
9 32
 
5.2%
Hangul
ValueCountFrequency (%)
설 83
50.0%
치 83
50.0%

거리표시유도등
Categorical

IMBALANCE 

Distinct26
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
353 
설치
56 
16
 
10
12
 
7
10
 
6
Other values (21)
46 

Length

Max length4
Median length4
Mean length3.4351464
Min length1

Unique

Unique8 ?
Unique (%)1.7%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row40
5th row10

Common Values

ValueCountFrequency (%)
<NA> 353
73.8%
설치 56
 
11.7%
16 10
 
2.1%
12 7
 
1.5%
10 6
 
1.3%
11 6
 
1.3%
4 6
 
1.3%
8 4
 
0.8%
5 3
 
0.6%
15 3
 
0.6%
Other values (16) 24
 
5.0%

Length

2023-12-11T07:15:12.804148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 353
73.8%
설치 56
 
11.7%
16 10
 
2.1%
12 7
 
1.5%
10 6
 
1.3%
11 6
 
1.3%
4 6
 
1.3%
8 4
 
0.8%
5 3
 
0.6%
15 3
 
0.6%
Other values (16) 24
 
5.0%

피난대피소비상주차대
Categorical

IMBALANCE 

Distinct14
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
352 
1
36 
2
 
26
3
 
19
4
 
13
Other values (9)
 
32

Length

Max length4
Median length4
Mean length3.2447699
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 352
73.6%
1 36
 
7.5%
2 26
 
5.4%
3 19
 
4.0%
4 13
 
2.7%
5 8
 
1.7%
10 6
 
1.3%
6 6
 
1.3%
11 4
 
0.8%
19 2
 
0.4%
Other values (4) 6
 
1.3%

Length

2023-12-11T07:15:12.913023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 352
73.6%
1 36
 
7.5%
2 26
 
5.4%
3 19
 
4.0%
4 13
 
2.7%
5 8
 
1.7%
10 6
 
1.3%
6 6
 
1.3%
11 4
 
0.8%
19 2
 
0.4%
Other values (4) 6
 
1.3%

제연설비
Categorical

IMBALANCE 

Distinct20
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
362 
6
 
26
8
 
19
7
 
15
설치
 
11
Other values (15)
45 

Length

Max length4
Median length4
Mean length3.3472803
Min length1

Unique

Unique5 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 362
75.7%
6 26
 
5.4%
8 19
 
4.0%
7 15
 
3.1%
설치 11
 
2.3%
9 10
 
2.1%
12 7
 
1.5%
10 6
 
1.3%
5 5
 
1.0%
11 2
 
0.4%
Other values (10) 15
 
3.1%

Length

2023-12-11T07:15:13.029300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 362
75.7%
6 26
 
5.4%
8 19
 
4.0%
7 15
 
3.1%
설치 11
 
2.3%
9 10
 
2.1%
12 7
 
1.5%
10 6
 
1.3%
5 5
 
1.0%
24 2
 
0.4%
Other values (10) 15
 
3.1%

무선통신보조설비
Categorical

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
294 
설치
147 
2
 
20
1
 
11
4
 
4

Length

Max length4
Median length4
Mean length3.1527197
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 294
61.5%
설치 147
30.8%
2 20
 
4.2%
1 11
 
2.3%
4 4
 
0.8%
3 2
 
0.4%

Length

2023-12-11T07:15:13.140072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:15:13.236621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 294
61.5%
설치 147
30.8%
2 20
 
4.2%
1 11
 
2.3%
4 4
 
0.8%
3 2
 
0.4%

연결송수관
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
418 
설치
48 
2
 
6
1
 
4
4
 
1

Length

Max length4
Median length4
Mean length3.7259414
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 418
87.4%
설치 48
 
10.0%
2 6
 
1.3%
1 4
 
0.8%
4 1
 
0.2%
74 1
 
0.2%

Length

2023-12-11T07:15:13.349645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:15:13.467856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 418
87.4%
설치 48
 
10.0%
2 6
 
1.3%
1 4
 
0.8%
4 1
 
0.2%
74 1
 
0.2%

비상콘센트
Categorical

IMBALANCE 

Distinct28
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
350 
설치
66 
11
 
9
18
 
6
15
 
5
Other values (23)
42 

Length

Max length4
Median length4
Mean length3.460251
Min length1

Unique

Unique10 ?
Unique (%)2.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row40
5th row18

Common Values

ValueCountFrequency (%)
<NA> 350
73.2%
설치 66
 
13.8%
11 9
 
1.9%
18 6
 
1.3%
15 5
 
1.0%
16 3
 
0.6%
13 3
 
0.6%
29 3
 
0.6%
12 3
 
0.6%
22 3
 
0.6%
Other values (18) 27
 
5.6%

Length

2023-12-11T07:15:13.616493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 350
73.2%
설치 66
 
13.8%
11 9
 
1.9%
18 6
 
1.3%
15 5
 
1.0%
16 3
 
0.6%
13 3
 
0.6%
29 3
 
0.6%
12 3
 
0.6%
22 3
 
0.6%
Other values (18) 27
 
5.6%

무정전설비
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
283 
설치
184 
1
 
8
3
 
2
6
 
1

Length

Max length4
Median length4
Mean length3.1610879
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 283
59.2%
설치 184
38.5%
1 8
 
1.7%
3 2
 
0.4%
6 1
 
0.2%

Length

2023-12-11T07:15:13.740760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:15:13.870775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 283
59.2%
설치 184
38.5%
1 8
 
1.7%
3 2
 
0.4%
6 1
 
0.2%

영상유고감지설비
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
426 
설치
51 
1
 
1

Length

Max length4
Median length4
Mean length3.7803347
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 426
89.1%
설치 51
 
10.7%
1 1
 
0.2%

Length

2023-12-11T07:15:14.244333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:15:14.359732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 426
89.1%
설치 51
 
10.7%
1 1
 
0.2%

데이터기준일자
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-01-26
151 
2023-02-16
148 
2023-01-05
111 
2022-12-28
68 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-01-26
2nd row2023-01-26
3rd row2023-01-26
4th row2023-01-26
5th row2023-01-26

Common Values

ValueCountFrequency (%)
2023-01-26 151
31.6%
2023-02-16 148
31.0%
2023-01-05 111
23.2%
2022-12-28 68
14.2%

Length

2023-12-11T07:15:14.474345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:15:14.587331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-01-26 151
31.6%
2023-02-16 148
31.0%
2023-01-05 111
23.2%
2022-12-28 68
14.2%

Sample

도로종류노선명시설명위도경도위치총길이총폭유효폭높이도로관리청준공년도소화전옥내소화전비상경보설비자동화재탐지설비비상방송설비긴급전화CCTV재방송설비정보표지판진입차단시설비상조명거리표시유도등피난대피소비상주차대제연설비무선통신보조설비연결송수관비상콘센트무정전설비영상유고감지설비데이터기준일자
0일반국도일반국도38호선대덕터널(하)37.02366127.251513경기도 안성시 신모산동395.59.59.54.0안성시199415<NA><NA><NA><NA><NA>3<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2023-01-26
1일반국도일반국도38호선비봉터널(상)37.022421127.277874경기도 안성시 당왕동497.59.59.56.5안성시199417<NA><NA><NA><NA><NA>3<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2023-01-26
2일반국도일반국도38호선비봉터널(하)37.022147127.283914경기도 안성시 당왕동488.59.59.56.5안성시199418<NA><NA><NA><NA><NA>3<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2023-01-26
3시도시도충훈터널(상,하)37.411114126.904683경기도 안양시 만안구 석수동880.019.312.86.6안양시200440<NA>설치<NA><NA>1010설치<NA><NA><NA>40<NA><NA>설치<NA>40설치<NA>2023-01-26
4시도시도호암2터널(상,하)37.437638126.914961경기도 안양시 만안구 석수동605.019.612.86.3안양시200018<NA>설치<NA><NA>2<NA>설치<NA><NA><NA>10<NA><NA>설치<NA>18설치<NA>2023-01-26
5지방도지방도360호선어하터널(상)37.807732127.119444경기도 양주시 삼숭동980.09.07.06.7양주시2011<NA><NA>설치설치<NA>13<NA>1<NA>설치<NA><NA><NA>설치<NA>설치<NA><NA>2023-01-26
6지방도지방도360호선어하터널(하)37.807732127.119444경기도 포천시 소흘읍 이동교리960.09.07.06.7양주시2011<NA><NA>설치설치<NA>13<NA>1<NA>설치<NA><NA><NA>설치<NA>설치<NA><NA>2023-01-26
7지방도지방도379호선천보터널37.862403127.103925경기도 양주시 회암동500.010.010.06.0양주시2006<NA><NA>설치설치<NA><NA><NA><NA><NA><NA>설치<NA><NA><NA>설치<NA>설치<NA><NA>2023-01-26
8국가지원지방도국가지원지방도57호선학의터널(상행)<NA><NA>경기도 의왕시 학의동374.09.06.56.8의왕시20208<NA><NA><NA><NA><NA><NA>설치<NA><NA><NA><NA><NA><NA>설치<NA><NA><NA><NA>2023-01-26
9국가지원지방도국가지원지방도57호선학의터널(하행)<NA><NA>경기도 의왕시 학의동384.03.53.56.1의왕시20208<NA><NA><NA><NA><NA><NA>설치<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2023-01-26
도로종류노선명시설명위도경도위치총길이총폭유효폭높이도로관리청준공년도소화전옥내소화전비상경보설비자동화재탐지설비비상방송설비긴급전화CCTV재방송설비정보표지판진입차단시설비상조명거리표시유도등피난대피소비상주차대제연설비무선통신보조설비연결송수관비상콘센트무정전설비영상유고감지설비데이터기준일자
468지방도지방도305호선굴고개터널37.194025126.717959경기도 화성시 서신면 상안리88.09.38.36.7경기도20088<NA><NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2023-01-26
469지방도지방도318호선당성터널37.193787126.718374경기도 화성시 서신면 상안리112.019.215.511.4경기도20086<NA><NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2023-01-26
470지방도지방도318호선문수산터널37.155191127.274489경기도 용인시 처인구 이동읍 묵리1566.09.39.36.6경기도20098241설치설치121420설치22설치1638설치설치41설치12023-01-26
471지방도지방도321호선서리터널37.194236127.181273경기도 용인시 처인구 이동읍 서리313.012.011.08.5경기도201424<NA><NA><NA><NA><NA>2설치<NA><NA>설치5<NA><NA>설치<NA><NA>설치<NA>2023-01-26
472지방도지방도313호선신왕터널(팽성)36.940909126.975511경기도 평택시 현덕면 덕목리394.06.06.04.8경기도201916<NA><NA><NA><NA><NA>4설치<NA><NA>설치<NA><NA><NA>설치<NA><NA>설치<NA>2023-01-26
473지방도지방도313호선신왕터널(포승)36.940683126.971094경기도 평택시 현덕면 신왕리413.06.06.04.8경기도201916<NA><NA><NA><NA><NA>3설치<NA><NA>설치<NA>1<NA>설치<NA><NA>설치<NA>2023-01-26
474지방도지방도337호선진우터널37.309124127.356979경기도 광주시 도척면 진우리270.08.58.06.8경기도201014<NA><NA><NA><NA><NA>2설치<NA><NA>설치4<NA><NA>설치<NA><NA>설치<NA>2023-01-26
475지방도지방도318호선초막터널37.133847127.421906경기도 용인시 처인구 백암면 고안리680.010.510.06.8경기도201054<NA>설치<NA>585설치<NA><NA>설치10<NA>설치설치<NA>27설치<NA>2023-01-26
476지방도지방도391호선화악터널37.998317127.526096경기도 가평군 북면 화악리680.07.35.87.0경기도200854<NA>설치<NA>2235설치<NA><NA>설치13<NA>설치설치<NA>27설치<NA>2023-01-26
477지방도지방도349호선황골터널37.371082127.731651경기도 여주시 강천면 도전리730.010.07.04.8경기도200622<NA>설치<NA>646설치<NA><NA>설치11<NA>설치설치<NA>11설치<NA>2023-01-26