Overview

Dataset statistics

Number of variables20
Number of observations10000
Missing cells1624
Missing cells (%)0.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 MiB
Average record size in memory175.0 B

Variable types

Text8
Numeric7
Categorical2
Boolean2
DateTime1

Alerts

데이터기준일자 has constant value ""Constant
시설유형코드 is highly overall correlated with 보호틀유무High correlation
시군구코드 is highly overall correlated with 관할기관명High correlation
경도 is highly overall correlated with 관할기관명High correlation
보호틀유무 is highly overall correlated with 시설유형코드High correlation
관할기관명 is highly overall correlated with 시군구코드 and 1 other fieldsHigh correlation
시도명 is highly imbalanced (94.7%)Imbalance
사용가능여부 is highly imbalanced (82.5%)Imbalance
상세위치 has 182 (1.8%) missing valuesMissing
설치연도 has 145 (1.5%) missing valuesMissing
배관깊이 has 371 (3.7%) missing valuesMissing
출수압력 has 475 (4.8%) missing valuesMissing
배관지름 has 337 (3.4%) missing valuesMissing
배관깊이 has 198 (2.0%) zerosZeros
출수압력 has 121 (1.2%) zerosZeros

Reproduction

Analysis started2023-12-10 21:17:02.122535
Analysis finished2023-12-10 21:17:12.538456
Duration10.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct9566
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:17:12.782045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length7.1039
Min length1

Characters and Unicode

Total characters71039
Distinct characters239
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9226 ?
Unique (%)92.3%

Sample

1st row여주19
2nd row광주시청-387
3rd row신길-64
4th row경기-월롱-17
5th row화성목동-18
ValueCountFrequency (%)
김포시 431
 
3.3%
소화전 218
 
1.6%
시관리 211
 
1.6%
미인수 176
 
1.3%
화성시 118
 
0.9%
사설-평택 111
 
0.8%
신장 94
 
0.7%
2022 94
 
0.7%
구리 75
 
0.6%
시청 63
 
0.5%
Other values (8736) 11662
88.0%
2023-12-11T06:17:13.332632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 6625
 
9.3%
1 5894
 
8.3%
0 5245
 
7.4%
2 4808
 
6.8%
3303
 
4.6%
3270
 
4.6%
3 2852
 
4.0%
4 2671
 
3.8%
6 2167
 
3.1%
5 2131
 
3.0%
Other values (229) 32073
45.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31283
44.0%
Other Letter 27879
39.2%
Dash Punctuation 6625
 
9.3%
Space Separator 3303
 
4.6%
Open Punctuation 819
 
1.2%
Close Punctuation 818
 
1.2%
Lowercase Letter 211
 
0.3%
Uppercase Letter 60
 
0.1%
Connector Punctuation 23
 
< 0.1%
Other Punctuation 18
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3270
 
11.7%
2063
 
7.4%
815
 
2.9%
663
 
2.4%
660
 
2.4%
656
 
2.4%
611
 
2.2%
545
 
2.0%
541
 
1.9%
536
 
1.9%
Other values (195) 17519
62.8%
Decimal Number
ValueCountFrequency (%)
1 5894
18.8%
0 5245
16.8%
2 4808
15.4%
3 2852
9.1%
4 2671
8.5%
6 2167
 
6.9%
5 2131
 
6.8%
7 2036
 
6.5%
8 1801
 
5.8%
9 1678
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
L 19
31.7%
H 17
28.3%
N 5
 
8.3%
E 5
 
8.3%
T 5
 
8.3%
X 5
 
8.3%
S 2
 
3.3%
J 1
 
1.7%
A 1
 
1.7%
Lowercase Letter
ValueCountFrequency (%)
m 69
32.7%
v 69
32.7%
t 69
32.7%
u 2
 
0.9%
l 1
 
0.5%
g 1
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 810
98.9%
[ 9
 
1.1%
Close Punctuation
ValueCountFrequency (%)
) 810
99.0%
] 8
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 10
55.6%
, 8
44.4%
Dash Punctuation
ValueCountFrequency (%)
- 6625
100.0%
Space Separator
ValueCountFrequency (%)
3303
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42889
60.4%
Hangul 27879
39.2%
Latin 271
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3270
 
11.7%
2063
 
7.4%
815
 
2.9%
663
 
2.4%
660
 
2.4%
656
 
2.4%
611
 
2.2%
545
 
2.0%
541
 
1.9%
536
 
1.9%
Other values (195) 17519
62.8%
Common
ValueCountFrequency (%)
- 6625
15.4%
1 5894
13.7%
0 5245
12.2%
2 4808
11.2%
3303
7.7%
3 2852
6.6%
4 2671
6.2%
6 2167
 
5.1%
5 2131
 
5.0%
7 2036
 
4.7%
Other values (9) 5157
12.0%
Latin
ValueCountFrequency (%)
m 69
25.5%
v 69
25.5%
t 69
25.5%
L 19
 
7.0%
H 17
 
6.3%
N 5
 
1.8%
E 5
 
1.8%
T 5
 
1.8%
X 5
 
1.8%
u 2
 
0.7%
Other values (5) 6
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43160
60.8%
Hangul 27879
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 6625
15.3%
1 5894
13.7%
0 5245
12.2%
2 4808
11.1%
3303
7.7%
3 2852
6.6%
4 2671
6.2%
6 2167
 
5.0%
5 2131
 
4.9%
7 2036
 
4.7%
Other values (24) 5428
12.6%
Hangul
ValueCountFrequency (%)
3270
 
11.7%
2063
 
7.4%
815
 
2.9%
663
 
2.4%
660
 
2.4%
656
 
2.4%
611
 
2.2%
545
 
2.0%
541
 
1.9%
536
 
1.9%
Other values (195) 17519
62.8%

시설유형코드
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3751
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:17:13.455556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile5
Maximum6
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.177004
Coefficient of variation (CV)0.85594069
Kurtosis9.7112496
Mean1.3751
Median Absolute Deviation (MAD)0
Skewness3.3257415
Sum13751
Variance1.3853385
MonotonicityNot monotonic
2023-12-11T06:17:13.561004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 8702
87.0%
2 581
 
5.8%
6 476
 
4.8%
5 137
 
1.4%
3 70
 
0.7%
4 34
 
0.3%
ValueCountFrequency (%)
1 8702
87.0%
2 581
 
5.8%
3 70
 
0.7%
4 34
 
0.3%
5 137
 
1.4%
6 476
 
4.8%
ValueCountFrequency (%)
6 476
 
4.8%
5 137
 
1.4%
4 34
 
0.3%
3 70
 
0.7%
2 581
 
5.8%
1 8702
87.0%

시도명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도
9940 
경기도
 
60

Length

Max length4
Median length3
Mean length3.006
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 9940
99.4%
경기도 60
 
0.6%

Length

2023-12-11T06:17:13.668735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:17:13.754884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 10000
100.0%
Distinct68
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:17:13.948022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length4.2682
Min length3

Characters and Unicode

Total characters42682
Distinct characters74
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

Unique8 ?
Unique (%)0.1%

Sample

1st row여주시
2nd row광주시
3rd row안산시 단원구
4th row파주시
5th row화성시
ValueCountFrequency (%)
평택시 856
 
6.6%
성남시 679
 
5.3%
김포시 646
 
5.0%
수원시 611
 
4.7%
시흥시 558
 
4.3%
용인시 524
 
4.1%
고양시 507
 
3.9%
부천시 494
 
3.8%
안산시 476
 
3.7%
화성시 442
 
3.4%
Other values (54) 7118
55.1%
2023-12-11T06:17:14.304461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10273
24.1%
2977
 
7.0%
2935
 
6.9%
1492
 
3.5%
1460
 
3.4%
1384
 
3.2%
1376
 
3.2%
1213
 
2.8%
1140
 
2.7%
1121
 
2.6%
Other values (64) 17311
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39705
93.0%
Space Separator 2977
 
7.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10273
25.9%
2935
 
7.4%
1492
 
3.8%
1460
 
3.7%
1384
 
3.5%
1376
 
3.5%
1213
 
3.1%
1140
 
2.9%
1121
 
2.8%
1067
 
2.7%
Other values (63) 16244
40.9%
Space Separator
ValueCountFrequency (%)
2977
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39705
93.0%
Common 2977
 
7.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10273
25.9%
2935
 
7.4%
1492
 
3.8%
1460
 
3.7%
1384
 
3.5%
1376
 
3.5%
1213
 
3.1%
1140
 
2.9%
1121
 
2.8%
1067
 
2.7%
Other values (63) 16244
40.9%
Common
ValueCountFrequency (%)
2977
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39705
93.0%
ASCII 2977
 
7.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
10273
25.9%
2935
 
7.4%
1492
 
3.8%
1460
 
3.7%
1384
 
3.5%
1376
 
3.5%
1213
 
3.1%
1140
 
2.9%
1121
 
2.8%
1067
 
2.7%
Other values (63) 16244
40.9%
ASCII
ValueCountFrequency (%)
2977
100.0%

시군구코드
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41368.575
Minimum41105
Maximum41830
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:17:14.486103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41105
5-th percentile41117
Q141210
median41360
Q341550
95-th percentile41650
Maximum41830
Range725
Interquartile range (IQR)340

Descriptive statistics

Standard deviation184.96404
Coefficient of variation (CV)0.0044711242
Kurtosis-0.85374295
Mean41368.575
Median Absolute Deviation (MAD)150
Skewness0.37018364
Sum4.1368575 × 108
Variance34211.696
MonotonicityNot monotonic
2023-12-11T06:17:14.652372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
41220 856
 
8.6%
41570 646
 
6.5%
41390 558
 
5.6%
41190 494
 
4.9%
41590 442
 
4.4%
41480 428
 
4.3%
41610 360
 
3.6%
41360 349
 
3.5%
41273 314
 
3.1%
41210 264
 
2.6%
Other values (35) 5289
52.9%
ValueCountFrequency (%)
41105 3
 
< 0.1%
41111 135
1.4%
41113 226
2.3%
41115 134
1.3%
41117 164
1.6%
41131 175
1.8%
41133 197
2.0%
41135 259
2.6%
41150 260
2.6%
41170 1
 
< 0.1%
ValueCountFrequency (%)
41830 100
 
1.0%
41820 81
 
0.8%
41800 95
 
0.9%
41670 102
 
1.0%
41650 197
 
2.0%
41630 253
 
2.5%
41610 360
3.6%
41590 442
4.4%
41570 646
6.5%
41550 262
2.6%
Distinct9539
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:17:15.061003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length41
Mean length19.3034
Min length1

Characters and Unicode

Total characters193034
Distinct characters407
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9174 ?
Unique (%)91.7%

Sample

1st row경기도 여주시 연양동 332원 부근
2nd row경기도 광주시 양벌동 390-5
3rd row경기도 안산시 단원구 원곡동 747-7
4th row 경기도 파주시 월롱면 덕은리 1239
5th row화성시 중동 산 119-5
ValueCountFrequency (%)
경기도 9836
 
21.3%
평택시 856
 
1.9%
성남시 679
 
1.5%
김포시 646
 
1.4%
수원시 611
 
1.3%
시흥시 551
 
1.2%
용인시 530
 
1.1%
고양시 508
 
1.1%
부천시 494
 
1.1%
안산시 476
 
1.0%
Other values (8843) 31050
67.2%
2023-12-11T06:17:15.524001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36538
18.9%
10301
 
5.3%
10150
 
5.3%
10086
 
5.2%
9861
 
5.1%
7864
 
4.1%
1 7678
 
4.0%
- 6731
 
3.5%
2 4924
 
2.6%
3 4201
 
2.2%
Other values (397) 84700
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 109637
56.8%
Decimal Number 39926
 
20.7%
Space Separator 36567
 
18.9%
Dash Punctuation 6731
 
3.5%
Open Punctuation 52
 
< 0.1%
Close Punctuation 52
 
< 0.1%
Other Punctuation 37
 
< 0.1%
Uppercase Letter 28
 
< 0.1%
Lowercase Letter 2
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10301
 
9.4%
10150
 
9.3%
10086
 
9.2%
9861
 
9.0%
7864
 
7.2%
3324
 
3.0%
3123
 
2.8%
2369
 
2.2%
2033
 
1.9%
1753
 
1.6%
Other values (363) 48773
44.5%
Uppercase Letter
ValueCountFrequency (%)
N 5
17.9%
B 4
14.3%
I 3
10.7%
G 3
10.7%
C 2
 
7.1%
S 2
 
7.1%
R 2
 
7.1%
M 2
 
7.1%
Q 1
 
3.6%
H 1
 
3.6%
Other values (3) 3
10.7%
Decimal Number
ValueCountFrequency (%)
1 7678
19.2%
2 4924
12.3%
3 4201
10.5%
4 3839
9.6%
6 3767
9.4%
5 3620
9.1%
7 3349
8.4%
8 3031
 
7.6%
9 2782
 
7.0%
0 2735
 
6.9%
Space Separator
ValueCountFrequency (%)
36538
99.9%
  29
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 34
91.9%
? 3
 
8.1%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
m 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 6731
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 109637
56.8%
Common 83366
43.2%
Latin 31
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10301
 
9.4%
10150
 
9.3%
10086
 
9.2%
9861
 
9.0%
7864
 
7.2%
3324
 
3.0%
3123
 
2.8%
2369
 
2.2%
2033
 
1.9%
1753
 
1.6%
Other values (363) 48773
44.5%
Common
ValueCountFrequency (%)
36538
43.8%
1 7678
 
9.2%
- 6731
 
8.1%
2 4924
 
5.9%
3 4201
 
5.0%
4 3839
 
4.6%
6 3767
 
4.5%
5 3620
 
4.3%
7 3349
 
4.0%
8 3031
 
3.6%
Other values (8) 5688
 
6.8%
Latin
ValueCountFrequency (%)
N 5
16.1%
B 4
12.9%
I 3
9.7%
G 3
9.7%
C 2
 
6.5%
S 2
 
6.5%
R 2
 
6.5%
M 2
 
6.5%
1
 
3.2%
Q 1
 
3.2%
Other values (6) 6
19.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 109637
56.8%
ASCII 83367
43.2%
None 29
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36538
43.8%
1 7678
 
9.2%
- 6731
 
8.1%
2 4924
 
5.9%
3 4201
 
5.0%
4 3839
 
4.6%
6 3767
 
4.5%
5 3620
 
4.3%
7 3349
 
4.0%
8 3031
 
3.6%
Other values (22) 5689
 
6.8%
Hangul
ValueCountFrequency (%)
10301
 
9.4%
10150
 
9.3%
10086
 
9.2%
9861
 
9.0%
7864
 
7.2%
3324
 
3.0%
3123
 
2.8%
2369
 
2.2%
2033
 
1.9%
1753
 
1.6%
Other values (363) 48773
44.5%
None
ValueCountFrequency (%)
  29
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct7179
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:17:15.902807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length45
Mean length15.0009
Min length1

Characters and Unicode

Total characters150009
Distinct characters543
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6929 ?
Unique (%)69.3%

Sample

1st rowN
2nd rowN
3rd row경기도 안산시 단원구 원곡로37
4th row경기도 파주시 엘씨디로 201
5th rowN
ValueCountFrequency (%)
경기도 7239
 
19.6%
n 2526
 
6.8%
평택시 633
 
1.7%
성남시 631
 
1.7%
수원시 549
 
1.5%
부천시 479
 
1.3%
안산시 468
 
1.3%
고양시 386
 
1.0%
단원구 325
 
0.9%
김포시 314
 
0.8%
Other values (7078) 23431
63.4%
2023-12-11T06:17:16.413457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27516
 
18.3%
7626
 
5.1%
7517
 
5.0%
7473
 
5.0%
7436
 
5.0%
6354
 
4.2%
1 5667
 
3.8%
2 3874
 
2.6%
3663
 
2.4%
3 2970
 
2.0%
Other values (533) 69913
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91092
60.7%
Space Separator 27519
 
18.3%
Decimal Number 26830
 
17.9%
Uppercase Letter 2559
 
1.7%
Dash Punctuation 1493
 
1.0%
Close Punctuation 217
 
0.1%
Open Punctuation 216
 
0.1%
Other Punctuation 73
 
< 0.1%
Lowercase Letter 9
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7626
 
8.4%
7517
 
8.3%
7473
 
8.2%
7436
 
8.2%
6354
 
7.0%
3663
 
4.0%
2677
 
2.9%
2675
 
2.9%
1672
 
1.8%
1556
 
1.7%
Other values (494) 42443
46.6%
Uppercase Letter
ValueCountFrequency (%)
N 2526
98.7%
G 6
 
0.2%
S 4
 
0.2%
X 4
 
0.2%
L 4
 
0.2%
B 4
 
0.2%
K 3
 
0.1%
A 2
 
0.1%
P 2
 
0.1%
T 1
 
< 0.1%
Other values (3) 3
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 5667
21.1%
2 3874
14.4%
3 2970
11.1%
4 2545
9.5%
5 2443
9.1%
6 2095
 
7.8%
7 1899
 
7.1%
0 1866
 
7.0%
8 1830
 
6.8%
9 1641
 
6.1%
Lowercase Letter
ValueCountFrequency (%)
m 4
44.4%
x 1
 
11.1%
c 1
 
11.1%
p 1
 
11.1%
s 1
 
11.1%
e 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
? 45
61.6%
, 22
30.1%
@ 4
 
5.5%
. 2
 
2.7%
Space Separator
ValueCountFrequency (%)
27516
> 99.9%
  3
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 1493
100.0%
Close Punctuation
ValueCountFrequency (%)
) 217
100.0%
Open Punctuation
ValueCountFrequency (%)
( 216
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91093
60.7%
Common 56348
37.6%
Latin 2568
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7626
 
8.4%
7517
 
8.3%
7473
 
8.2%
7436
 
8.2%
6354
 
7.0%
3663
 
4.0%
2677
 
2.9%
2675
 
2.9%
1672
 
1.8%
1556
 
1.7%
Other values (495) 42444
46.6%
Common
ValueCountFrequency (%)
27516
48.8%
1 5667
 
10.1%
2 3874
 
6.9%
3 2970
 
5.3%
4 2545
 
4.5%
5 2443
 
4.3%
6 2095
 
3.7%
7 1899
 
3.4%
0 1866
 
3.3%
8 1830
 
3.2%
Other values (9) 3643
 
6.5%
Latin
ValueCountFrequency (%)
N 2526
98.4%
G 6
 
0.2%
m 4
 
0.2%
S 4
 
0.2%
X 4
 
0.2%
L 4
 
0.2%
B 4
 
0.2%
K 3
 
0.1%
A 2
 
0.1%
P 2
 
0.1%
Other values (9) 9
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91092
60.7%
ASCII 58913
39.3%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27516
46.7%
1 5667
 
9.6%
2 3874
 
6.6%
3 2970
 
5.0%
4 2545
 
4.3%
N 2526
 
4.3%
5 2443
 
4.1%
6 2095
 
3.6%
7 1899
 
3.2%
0 1866
 
3.2%
Other values (27) 5512
 
9.4%
Hangul
ValueCountFrequency (%)
7626
 
8.4%
7517
 
8.3%
7473
 
8.2%
7436
 
8.2%
6354
 
7.0%
3663
 
4.0%
2677
 
2.9%
2675
 
2.9%
1672
 
1.8%
1556
 
1.7%
Other values (494) 42443
46.6%
None
ValueCountFrequency (%)
  3
75.0%
1
 
25.0%

위도
Text

Distinct9467
Distinct (%)94.9%
Missing27
Missing (%)0.3%
Memory size156.2 KiB
2023-12-11T06:17:16.657530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.929008
Min length1

Characters and Unicode

Total characters128941
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9108 ?
Unique (%)91.3%

Sample

1st rowN
2nd row37.3770386672
3rd row37.3306597164
4th row37.8099418543
5th row37.2066361255
ValueCountFrequency (%)
n 59
 
0.6%
37.0357005222 7
 
0.1%
37.3659453911 7
 
0.1%
37.1210044472 6
 
0.1%
37.4089699264 5
 
0.1%
37.8175900983 5
 
0.1%
37.7394019398 5
 
0.1%
37.6435589601 5
 
0.1%
37.3741912548 5
 
0.1%
37.8099418543 4
 
< 0.1%
Other values (9457) 9865
98.9%
2023-12-11T06:17:17.020286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 20792
16.1%
7 19149
14.9%
6 10494
8.1%
4 10387
8.1%
2 10208
7.9%
. 9914
7.7%
0 9833
7.6%
9 9695
7.5%
5 9556
7.4%
8 9430
7.3%
Other values (2) 9483
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 118968
92.3%
Other Punctuation 9914
 
7.7%
Uppercase Letter 59
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 20792
17.5%
7 19149
16.1%
6 10494
8.8%
4 10387
8.7%
2 10208
8.6%
0 9833
8.3%
9 9695
8.1%
5 9556
8.0%
8 9430
7.9%
1 9424
7.9%
Other Punctuation
ValueCountFrequency (%)
. 9914
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 128882
> 99.9%
Latin 59
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
3 20792
16.1%
7 19149
14.9%
6 10494
8.1%
4 10387
8.1%
2 10208
7.9%
. 9914
7.7%
0 9833
7.6%
9 9695
7.5%
5 9556
7.4%
8 9430
7.3%
Latin
ValueCountFrequency (%)
N 59
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 128941
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 20792
16.1%
7 19149
14.9%
6 10494
8.1%
4 10387
8.1%
2 10208
7.9%
. 9914
7.7%
0 9833
7.6%
9 9695
7.5%
5 9556
7.4%
8 9430
7.3%
Other values (2) 9483
7.4%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct9466
Distinct (%)95.5%
Missing86
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean126.99481
Minimum126.39155
Maximum127.75782
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:17:17.447995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.39155
5-th percentile126.67286
Q1126.81423
median127.01042
Q3127.12949
95-th percentile127.35321
Maximum127.75782
Range1.3662711
Interquartile range (IQR)0.31525148

Descriptive statistics

Standard deviation0.2150122
Coefficient of variation (CV)0.0016930787
Kurtosis0.078783549
Mean126.99481
Median Absolute Deviation (MAD)0.15426547
Skewness0.36956903
Sum1259026.5
Variance0.046230248
MonotonicityNot monotonic
2023-12-11T06:17:17.597428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7125607489 7
 
0.1%
127.0533464784 7
 
0.1%
127.0685272071 6
 
0.1%
127.1210706359 5
 
0.1%
126.973638935 5
 
0.1%
127.086981032 5
 
0.1%
126.8542393513 5
 
0.1%
127.0501169382 5
 
0.1%
126.7598272969 4
 
< 0.1%
126.9483708542 4
 
< 0.1%
Other values (9456) 9861
98.6%
(Missing) 86
 
0.9%
ValueCountFrequency (%)
126.3915488852 1
< 0.1%
126.5252557914 1
< 0.1%
126.5265135516 1
< 0.1%
126.5285706997 1
< 0.1%
126.5298389033 1
< 0.1%
126.5310068683 1
< 0.1%
126.5348761385 1
< 0.1%
126.5350723371 1
< 0.1%
126.5376474893 1
< 0.1%
126.5380024631 1
< 0.1%
ValueCountFrequency (%)
127.7578200046 1
< 0.1%
127.7552359639 1
< 0.1%
127.7523702338 1
< 0.1%
127.7194320555 1
< 0.1%
127.7167832707 1
< 0.1%
127.7167416078 1
< 0.1%
127.7127886122 1
< 0.1%
127.7108071818 1
< 0.1%
127.705292107 1
< 0.1%
127.7052463253 1
< 0.1%

상세위치
Text

MISSING 

Distinct8716
Distinct (%)88.8%
Missing182
Missing (%)1.8%
Memory size156.2 KiB
2023-12-11T06:17:17.875632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length44
Mean length9.5440008
Min length1

Characters and Unicode

Total characters93703
Distinct characters932
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8414 ?
Unique (%)85.7%

Sample

1st row금은모래공중화장실 옆
2nd row중앙천막 앞
3rd rowGS편의점 앞
4th rowLG 디스플레이 기숙사 F동 건너편
5th row아단빌 근처
ValueCountFrequency (%)
3870
 
16.4%
963
 
4.1%
인근 739
 
3.1%
맞은편 364
 
1.5%
입구 330
 
1.4%
파악중 316
 
1.3%
건너편 264
 
1.1%
정문 212
 
0.9%
도로 205
 
0.9%
삼거리 194
 
0.8%
Other values (9793) 16173
68.4%
2023-12-11T06:17:18.339489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14102
 
15.0%
4256
 
4.5%
1536
 
1.6%
1525
 
1.6%
1413
 
1.5%
1 1252
 
1.3%
1145
 
1.2%
1073
 
1.1%
1072
 
1.1%
1032
 
1.1%
Other values (922) 65297
69.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 72227
77.1%
Space Separator 14102
 
15.0%
Decimal Number 5141
 
5.5%
Uppercase Letter 981
 
1.0%
Lowercase Letter 420
 
0.4%
Close Punctuation 215
 
0.2%
Open Punctuation 213
 
0.2%
Dash Punctuation 210
 
0.2%
Other Punctuation 129
 
0.1%
Other Symbol 52
 
0.1%
Other values (2) 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4256
 
5.9%
1536
 
2.1%
1525
 
2.1%
1413
 
2.0%
1145
 
1.6%
1073
 
1.5%
1072
 
1.5%
1032
 
1.4%
1002
 
1.4%
983
 
1.4%
Other values (838) 57190
79.2%
Uppercase Letter
ValueCountFrequency (%)
C 116
11.8%
S 114
11.6%
G 95
 
9.7%
U 72
 
7.3%
M 61
 
6.2%
L 57
 
5.8%
B 52
 
5.3%
K 51
 
5.2%
I 49
 
5.0%
A 44
 
4.5%
Other values (16) 270
27.5%
Lowercase Letter
ValueCountFrequency (%)
m 117
27.9%
s 45
 
10.7%
c 45
 
10.7%
g 32
 
7.6%
e 31
 
7.4%
u 23
 
5.5%
k 18
 
4.3%
a 15
 
3.6%
t 13
 
3.1%
o 10
 
2.4%
Other values (14) 71
16.9%
Decimal Number
ValueCountFrequency (%)
1 1252
24.4%
0 841
16.4%
2 779
15.2%
3 527
10.3%
5 424
 
8.2%
4 377
 
7.3%
6 297
 
5.8%
7 223
 
4.3%
9 219
 
4.3%
8 202
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 63
48.8%
. 21
 
16.3%
& 14
 
10.9%
/ 10
 
7.8%
@ 8
 
6.2%
? 5
 
3.9%
: 4
 
3.1%
" 2
 
1.6%
' 2
 
1.6%
Close Punctuation
ValueCountFrequency (%)
) 213
99.1%
1
 
0.5%
1
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 211
99.1%
1
 
0.5%
1
 
0.5%
Math Symbol
ValueCountFrequency (%)
> 4
40.0%
~ 3
30.0%
+ 3
30.0%
Letter Number
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Space Separator
ValueCountFrequency (%)
14102
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 210
100.0%
Other Symbol
ValueCountFrequency (%)
52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 72277
77.1%
Common 20020
 
21.4%
Latin 1404
 
1.5%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4256
 
5.9%
1536
 
2.1%
1525
 
2.1%
1413
 
2.0%
1145
 
1.6%
1073
 
1.5%
1072
 
1.5%
1032
 
1.4%
1002
 
1.4%
983
 
1.4%
Other values (837) 57240
79.2%
Latin
ValueCountFrequency (%)
m 117
 
8.3%
C 116
 
8.3%
S 114
 
8.1%
G 95
 
6.8%
U 72
 
5.1%
M 61
 
4.3%
L 57
 
4.1%
B 52
 
3.7%
K 51
 
3.6%
I 49
 
3.5%
Other values (43) 620
44.2%
Common
ValueCountFrequency (%)
14102
70.4%
1 1252
 
6.3%
0 841
 
4.2%
2 779
 
3.9%
3 527
 
2.6%
5 424
 
2.1%
4 377
 
1.9%
6 297
 
1.5%
7 223
 
1.1%
9 219
 
1.1%
Other values (20) 979
 
4.9%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 72225
77.1%
ASCII 21417
 
22.9%
None 56
 
0.1%
Number Forms 3
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14102
65.8%
1 1252
 
5.8%
0 841
 
3.9%
2 779
 
3.6%
3 527
 
2.5%
5 424
 
2.0%
4 377
 
1.8%
6 297
 
1.4%
7 223
 
1.0%
9 219
 
1.0%
Other values (66) 2376
 
11.1%
Hangul
ValueCountFrequency (%)
4256
 
5.9%
1536
 
2.1%
1525
 
2.1%
1413
 
2.0%
1145
 
1.6%
1073
 
1.5%
1072
 
1.5%
1032
 
1.4%
1002
 
1.4%
983
 
1.4%
Other values (836) 57188
79.2%
None
ValueCountFrequency (%)
52
92.9%
1
 
1.8%
1
 
1.8%
1
 
1.8%
1
 
1.8%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Number Forms
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Distinct212
Distinct (%)2.1%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-11T06:17:18.579399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length9
Mean length8.8534853
Min length2

Characters and Unicode

Total characters88526
Distinct characters162
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

Unique6 ?
Unique (%)0.1%

Sample

1st row월송119안전센터
2nd row오포119안전센터
3rd row신길119안전센터
4th row월롱119안전센터
5th row목동119안전센터
ValueCountFrequency (%)
중앙119안전센터 281
 
2.8%
정왕119안전센터 169
 
1.7%
양촌119안전센터 151
 
1.5%
시흥119안전센터 147
 
1.5%
세교119안전센터 146
 
1.5%
통진119안전센터 129
 
1.3%
도기119안전센터 115
 
1.1%
송정119안전센터 115
 
1.1%
수지119안전센터 113
 
1.1%
비전119안전센터 113
 
1.1%
Other values (200) 8540
85.2%
2023-12-11T06:17:18.972247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19373
21.9%
10009
11.3%
9843
11.1%
9 9683
10.9%
9653
10.9%
9653
10.9%
593
 
0.7%
527
 
0.6%
526
 
0.6%
522
 
0.6%
Other values (152) 18144
20.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59392
67.1%
Decimal Number 29067
32.8%
Space Separator 67
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10009
16.9%
9843
16.6%
9653
16.3%
9653
16.3%
593
 
1.0%
527
 
0.9%
526
 
0.9%
522
 
0.9%
520
 
0.9%
495
 
0.8%
Other values (145) 17051
28.7%
Decimal Number
ValueCountFrequency (%)
1 19373
66.6%
9 9683
33.3%
2 7
 
< 0.1%
3 2
 
< 0.1%
7 1
 
< 0.1%
4 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
67
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59392
67.1%
Common 29134
32.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10009
16.9%
9843
16.6%
9653
16.3%
9653
16.3%
593
 
1.0%
527
 
0.9%
526
 
0.9%
522
 
0.9%
520
 
0.9%
495
 
0.8%
Other values (145) 17051
28.7%
Common
ValueCountFrequency (%)
1 19373
66.5%
9 9683
33.2%
67
 
0.2%
2 7
 
< 0.1%
3 2
 
< 0.1%
7 1
 
< 0.1%
4 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 59392
67.1%
ASCII 29134
32.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19373
66.5%
9 9683
33.2%
67
 
0.2%
2 7
 
< 0.1%
3 2
 
< 0.1%
7 1
 
< 0.1%
4 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
10009
16.9%
9843
16.6%
9653
16.3%
9653
16.3%
593
 
1.0%
527
 
0.9%
526
 
0.9%
522
 
0.9%
520
 
0.9%
495
 
0.8%
Other values (145) 17051
28.7%

보호틀유무
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
True
6937 
False
3063 
ValueCountFrequency (%)
True 6937
69.4%
False 3063
30.6%
2023-12-11T06:17:19.086504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

사용가능여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
True
9738 
False
 
262
ValueCountFrequency (%)
True 9738
97.4%
False 262
 
2.6%
2023-12-11T06:17:19.158691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

설치연도
Real number (ℝ)

MISSING 

Distinct50
Distinct (%)0.5%
Missing145
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean2009.1569
Minimum1900
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:17:19.283065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1900
5-th percentile1993
Q12002
median2010
Q32018
95-th percentile2021
Maximum2023
Range123
Interquartile range (IQR)16

Descriptive statistics

Standard deviation11.443393
Coefficient of variation (CV)0.0056956193
Kurtosis28.339486
Mean2009.1569
Median Absolute Deviation (MAD)8
Skewness-3.402261
Sum19800241
Variance130.95124
MonotonicityNot monotonic
2023-12-11T06:17:19.435201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2019 1320
 
13.2%
2017 621
 
6.2%
2018 521
 
5.2%
2022 452
 
4.5%
2009 446
 
4.5%
2016 423
 
4.2%
1999 383
 
3.8%
2008 374
 
3.7%
2000 367
 
3.7%
2005 349
 
3.5%
Other values (40) 4599
46.0%
ValueCountFrequency (%)
1900 36
0.4%
1962 2
 
< 0.1%
1976 8
 
0.1%
1977 1
 
< 0.1%
1978 2
 
< 0.1%
1979 3
 
< 0.1%
1980 9
 
0.1%
1981 4
 
< 0.1%
1982 7
 
0.1%
1983 10
 
0.1%
ValueCountFrequency (%)
2023 25
 
0.2%
2022 452
 
4.5%
2021 261
 
2.6%
2020 291
 
2.9%
2019 1320
13.2%
2018 521
 
5.2%
2017 621
6.2%
2016 423
 
4.2%
2015 178
 
1.8%
2014 199
 
2.0%

배관깊이
Real number (ℝ)

MISSING  ZEROS 

Distinct104
Distinct (%)1.1%
Missing371
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean4.4710718
Minimum0
Maximum1700
Zeros198
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:17:19.565398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.5
Q11
median1
Q31.2
95-th percentile2
Maximum1700
Range1700
Interquartile range (IQR)0.2

Descriptive statistics

Standard deviation58.60427
Coefficient of variation (CV)13.107432
Kurtosis406.62661
Mean4.4710718
Median Absolute Deviation (MAD)0.2
Skewness19.689919
Sum43051.95
Variance3434.4604
MonotonicityNot monotonic
2023-12-11T06:17:19.694158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 3780
37.8%
1.2 1059
 
10.6%
1.5 1034
 
10.3%
0.5 898
 
9.0%
2.0 579
 
5.8%
0.8 361
 
3.6%
0.6 292
 
2.9%
0.7 258
 
2.6%
0.0 198
 
2.0%
1.3 126
 
1.3%
Other values (94) 1044
 
10.4%
(Missing) 371
 
3.7%
ValueCountFrequency (%)
0.0 198
2.0%
0.1 15
 
0.1%
0.12 1
 
< 0.1%
0.15 2
 
< 0.1%
0.2 22
 
0.2%
0.25 2
 
< 0.1%
0.3 82
0.8%
0.35 5
 
0.1%
0.4 84
0.8%
0.41 2
 
< 0.1%
ValueCountFrequency (%)
1700.0 1
 
< 0.1%
1400.0 1
 
< 0.1%
1300.0 1
 
< 0.1%
1200.0 12
0.1%
1100.0 2
 
< 0.1%
1000.0 1
 
< 0.1%
900.0 2
 
< 0.1%
800.0 2
 
< 0.1%
750.0 1
 
< 0.1%
700.0 2
 
< 0.1%

출수압력
Real number (ℝ)

MISSING  ZEROS 

Distinct88
Distinct (%)0.9%
Missing475
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean4.2244094
Minimum0
Maximum65
Zeros121
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:17:19.853069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.5
Q13.4
median4.2
Q35
95-th percentile6
Maximum65
Range65
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.663281
Coefficient of variation (CV)0.393731
Kurtosis560.42047
Mean4.2244094
Median Absolute Deviation (MAD)0.8
Skewness15.19369
Sum40237.5
Variance2.7665035
MonotonicityNot monotonic
2023-12-11T06:17:19.986728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.0 2587
25.9%
4.0 1202
12.0%
3.0 1041
10.4%
3.5 609
 
6.1%
6.0 455
 
4.5%
4.5 449
 
4.5%
2.5 351
 
3.5%
3.3 176
 
1.8%
5.5 166
 
1.7%
3.2 156
 
1.6%
Other values (78) 2333
23.3%
(Missing) 475
 
4.8%
ValueCountFrequency (%)
0.0 121
1.2%
0.1 1
 
< 0.1%
0.2 2
 
< 0.1%
0.3 3
 
< 0.1%
0.5 69
0.7%
0.6 6
 
0.1%
0.65 1
 
< 0.1%
0.7 4
 
< 0.1%
0.75 1
 
< 0.1%
0.8 1
 
< 0.1%
ValueCountFrequency (%)
65.0 3
 
< 0.1%
11.0 1
 
< 0.1%
10.0 3
 
< 0.1%
9.0 3
 
< 0.1%
8.8 1
 
< 0.1%
8.7 1
 
< 0.1%
8.5 5
 
0.1%
8.3 1
 
< 0.1%
8.1 3
 
< 0.1%
8.0 40
0.4%

배관지름
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)0.3%
Missing337
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean112.60223
Minimum0
Maximum1500
Zeros66
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:17:20.107896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile65
Q165
median100
Q3100
95-th percentile200
Maximum1500
Range1500
Interquartile range (IQR)35

Descriptive statistics

Standard deviation72.352904
Coefficient of variation (CV)0.64255303
Kurtosis41.270188
Mean112.60223
Median Absolute Deviation (MAD)35
Skewness4.5282387
Sum1088075.4
Variance5234.9427
MonotonicityNot monotonic
2023-12-11T06:17:20.263902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
100.0 4329
43.3%
65.0 2816
28.2%
200.0 954
 
9.5%
150.0 645
 
6.5%
80.0 296
 
3.0%
300.0 214
 
2.1%
400.0 73
 
0.7%
0.0 66
 
0.7%
75.0 63
 
0.6%
250.0 58
 
0.6%
Other values (22) 149
 
1.5%
(Missing) 337
 
3.4%
ValueCountFrequency (%)
0.0 66
 
0.7%
0.35 1
 
< 0.1%
10.0 1
 
< 0.1%
25.0 14
 
0.1%
30.0 1
 
< 0.1%
40.0 1
 
< 0.1%
45.0 2
 
< 0.1%
50.0 23
 
0.2%
60.0 16
 
0.2%
65.0 2816
28.2%
ValueCountFrequency (%)
1500.0 1
 
< 0.1%
1100.0 1
 
< 0.1%
1000.0 5
 
0.1%
900.0 1
 
< 0.1%
800.0 2
 
< 0.1%
700.0 5
 
0.1%
600.0 24
 
0.2%
500.0 7
 
0.1%
450.0 4
 
< 0.1%
400.0 73
0.7%

관할기관명
Categorical

HIGH CORRELATION 

Distinct37
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
김포소방서
 
646
시흥소방서
 
558
용인소방서
 
530
부천소방서
 
494
평택소방서
 
478
Other values (32)
7294 

Length

Max length7
Median length5
Mean length5.146
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row여주소방서
2nd row광주소방서
3rd row안산소방서
4th row파주소방서
5th row화성소방서

Common Values

ValueCountFrequency (%)
김포소방서 646
 
6.5%
시흥소방서 558
 
5.6%
용인소방서 530
 
5.3%
부천소방서 494
 
4.9%
평택소방서 478
 
4.8%
안산소방서 476
 
4.8%
화성소방서 442
 
4.4%
파주소방서 428
 
4.3%
송탄소방서 378
 
3.8%
성남소방서 372
 
3.7%
Other values (27) 5198
52.0%

Length

2023-12-11T06:17:20.382938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
김포소방서 646
 
6.5%
시흥소방서 558
 
5.6%
용인소방서 530
 
5.3%
부천소방서 494
 
4.9%
평택소방서 478
 
4.8%
안산소방서 476
 
4.8%
화성소방서 442
 
4.4%
파주소방서 428
 
4.3%
송탄소방서 378
 
3.8%
성남소방서 372
 
3.7%
Other values (26) 5198
52.0%
Distinct297
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:17:20.615813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.2252
Min length11

Characters and Unicode

Total characters122252
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)0.6%

Sample

1st row031-887-7119
2nd row031-799-2524
3rd row031-470-7487
4th row031-956-9554
5th row031-8012-6463
ValueCountFrequency (%)
031-310-0413 558
 
5.6%
031-8021-0413 530
 
5.3%
032-650-4413 494
 
4.9%
031-685-8413 378
 
3.8%
031-849-8412 253
 
2.5%
031-678-4416 197
 
2.0%
031-645-5414 156
 
1.6%
031-980-4514 151
 
1.5%
031-931-0119 129
 
1.3%
031-570-6413 120
 
1.2%
Other values (287) 7034
70.3%
2023-12-11T06:17:20.986803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20782
17.0%
- 20000
16.4%
3 17518
14.3%
1 17279
14.1%
5 10452
8.5%
4 8929
7.3%
8 6888
 
5.6%
9 5727
 
4.7%
2 5633
 
4.6%
6 4536
 
3.7%
Other values (2) 4508
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 102218
83.6%
Dash Punctuation 20000
 
16.4%
Math Symbol 34
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20782
20.3%
3 17518
17.1%
1 17279
16.9%
5 10452
10.2%
4 8929
8.7%
8 6888
 
6.7%
9 5727
 
5.6%
2 5633
 
5.5%
6 4536
 
4.4%
7 4474
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 20000
100.0%
Math Symbol
ValueCountFrequency (%)
~ 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 122252
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20782
17.0%
- 20000
16.4%
3 17518
14.3%
1 17279
14.1%
5 10452
8.5%
4 8929
7.3%
8 6888
 
5.6%
9 5727
 
4.7%
2 5633
 
4.6%
6 4536
 
3.7%
Other values (2) 4508
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 122252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20782
17.0%
- 20000
16.4%
3 17518
14.3%
1 17279
14.1%
5 10452
8.5%
4 8929
7.3%
8 6888
 
5.6%
9 5727
 
4.7%
2 5633
 
4.6%
6 4536
 
3.7%
Other values (2) 4508
 
3.7%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-05-31 00:00:00
Maximum2023-05-31 00:00:00
2023-12-11T06:17:21.101498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:21.182694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T06:17:11.065636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:05.628958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:06.295436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:07.875643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:08.761281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:09.489083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:10.412318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:11.175006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:05.715440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:06.399903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:08.010023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:08.855572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:09.592316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:10.512776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:11.270884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:05.818979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:06.517037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:08.139139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:08.955074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:09.699003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:10.602657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:11.388878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:05.909709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:06.630428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:08.252273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:09.066150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:09.799759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:10.688143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:11.488038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:06.013062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:06.791671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:08.351596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:09.169041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:09.910863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:10.773512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:11.628304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:06.109358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:07.206620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:08.468903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:09.285875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:10.031454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:10.871340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:11.744516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:06.204741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:07.547720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:08.618021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:09.378679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:10.304376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:10.957295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:17:21.256393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설유형코드시도명시군구명시군구코드경도보호틀유무사용가능여부설치연도배관깊이출수압력배관지름관할기관명
시설유형코드1.0000.0000.5130.2520.1950.7230.0400.1780.0000.1210.0090.484
시도명0.0001.0000.3140.1680.1010.0410.0000.0320.0000.0000.0000.305
시군구명0.5130.3141.0001.0000.9460.4020.1610.4920.2740.4210.5770.999
시군구코드0.2520.1681.0001.0000.6700.2180.0730.2140.1670.1710.3471.000
경도0.1950.1010.9460.6701.0000.2860.0700.2140.0000.1080.1140.929
보호틀유무0.7230.0410.4020.2180.2861.0000.0580.2070.0000.0000.0470.377
사용가능여부0.0400.0000.1610.0730.0700.0581.0000.0360.0000.0240.0000.152
설치연도0.1780.0320.4920.2140.2140.2070.0361.0000.0490.0000.0530.439
배관깊이0.0000.0000.2740.1670.0000.0000.0000.0491.0000.0440.1170.282
출수압력0.1210.0000.4210.1710.1080.0000.0240.0000.0441.0000.0000.423
배관지름0.0090.0000.5770.3470.1140.0470.0000.0530.1170.0001.0000.587
관할기관명0.4840.3050.9991.0000.9290.3770.1520.4390.2820.4230.5871.000
2023-12-11T06:17:21.441887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관할기관명보호틀유무사용가능여부시도명
관할기관명1.0000.3180.1280.256
보호틀유무0.3181.0000.0370.026
사용가능여부0.1280.0371.0000.000
시도명0.2560.0260.0001.000
2023-12-11T06:17:21.535502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설유형코드시군구코드경도설치연도배관깊이출수압력배관지름시도명보호틀유무사용가능여부관할기관명
시설유형코드1.000-0.154-0.082-0.138-0.024-0.054-0.0680.0000.5350.0290.233
시군구코드-0.1541.0000.1070.2340.0220.0520.1150.1670.2180.0730.998
경도-0.0820.1071.000-0.0040.0860.1630.0110.0770.2190.0540.667
설치연도-0.1380.234-0.0041.0000.016-0.017-0.0410.0380.2520.0450.213
배관깊이-0.0240.0220.0860.0161.000-0.0140.1130.0000.0000.0000.102
출수압력-0.0540.0520.163-0.017-0.0141.000-0.0070.0000.0090.0380.214
배관지름-0.0680.1150.011-0.0410.113-0.0071.0000.0000.0470.0000.237
시도명0.0000.1670.0770.0380.0000.0000.0001.0000.0260.0000.256
보호틀유무0.5350.2180.2190.2520.0000.0090.0470.0261.0000.0370.318
사용가능여부0.0290.0730.0540.0450.0000.0380.0000.0000.0371.0000.128
관할기관명0.2330.9980.6670.2130.1020.2140.2370.2560.3180.1281.000

Missing values

2023-12-11T06:17:11.903695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:17:12.254337image/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.
2023-12-11T06:17:12.431484image/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

시설번호시설유형코드시도명시군구명시군구코드소재지지번주소소재지도로명주소위도경도상세위치안전센터명보호틀유무사용가능여부설치연도배관깊이출수압력배관지름관할기관명관할기관전화번호데이터기준일자
56여주191경기도여주시41670경기도 여주시 연양동 332원 부근NN<NA>금은모래공중화장실 옆월송119안전센터YY<NA>1.04.865.0여주소방서031-887-71192023-05-31
26601광주시청-3871경기도광주시41610경기도 광주시 양벌동 390-5N37.3770386672127.252973중앙천막 앞오포119안전센터NY20190.65.5100.0광주소방서031-799-25242023-05-31
6573신길-641경기도안산시 단원구41273경기도 안산시 단원구 원곡동 747-7경기도 안산시 단원구 원곡로3737.3306597164126.79282GS편의점 앞신길119안전센터YY20091.23.0150.0안산소방서031-470-74872023-05-31
12323경기-월롱-171경기도파주시41480경기도 파주시 월롱면 덕은리 1239경기도 파주시 엘씨디로 20137.8099418543126.759827LG 디스플레이 기숙사 F동 건너편월롱119안전센터NY20070.55.0100.0파주소방서031-956-95542023-05-31
9138화성목동-181경기도화성시41590화성시 중동 산 119-5N37.2066361255127.144684아단빌 근처목동119안전센터YY20201.05.0300.0화성소방서031-8012-64632023-05-31
83602451경기도시흥시41390경기도 시흥시 정왕동 1304N37.3315022007126.740665현도제강 도로변(하천방향)정왕119안전센터NY20190.73.065.0시흥소방서031-310-04132023-05-31
17819부천-0146경기도부천시41190경기도 부천시 심곡본동 547경기도 부천시 자유로 53-137.4837189995126.782173삼총사축산중동119안전센터NY2020<NA><NA><NA>부천소방서032-650-44132023-05-31
10906공흥-0081경기도양평군41830경기도 양평군 양평읍 공흥리 455경기도 양평군 양평읍 공흥리 45537.4901721515127.499061대은레미콘 앞공흥119안전센터YY20060.85.065.0양평소방서031-770-05062023-05-31
25136147호1경기도화성시41590경기도 화성시 능동 1151-1 모아미래도947동앞경기도 수원시 덕영대로 1483번길 737.1995269351127.057894새마을금고 정문 앞반송119안전센터YY20081.23.0200.0화성소방서031-8012-64132023-05-31
168시관리 고읍 5호1경기도양주시41630경기도 양주시 광사동 70-51경기도 양주시 광사로 131-2737.7850631661127.082037종가 안고읍119안전센터NY2016<NA>3.5150.0양주소방서031-849-84122023-05-31
시설번호시설유형코드시도명시군구명시군구코드소재지지번주소소재지도로명주소위도경도상세위치안전센터명보호틀유무사용가능여부설치연도배관깊이출수압력배관지름관할기관명관할기관전화번호데이터기준일자
18798화성시 비봉-05호1경기도화성시41590경기도 화성시 비봉면 양노리 701-15경기도 화성시 비봉면 현대기아로 84537.2230022333126.858357풍년 한식뷔페 앞남양119안전센터YY20151.54.5200.0화성소방서031-8012-65592023-05-31
11813포천112호1경기도포천시41650경기도 포천시 신읍동 46-18N37.8978275631127.200129포천행정복지센터 앞군내119안전센터YY20050.44.2200.0포천소방서031-538-55062023-05-31
26729관인16호1경기도포천시41650경기도 포천시 관인면 탄동리 644-8경기도 포천시 관인면 관인로 1838.1578731021127.25047관인지역대 앞영북119안전센터YY20041.53.0100.0포천소방서031-538-55272023-05-31
27428(시)수지067호1경기도용인시 수지구41465경기도 용인시 수지구 상현동 1139경기도 용인시 수지구 광교마을로 109(상현동)37.2967621322127.076562파악중수지119안전센터YY20191.04.0100.0용인소방서031-8021-04132023-05-31
13804-0201경기도수원시 영통구41117경기도 수원시 영통구 매탄동 196-65경기도 수원시 영통구 매여울로3637.2712915730127.04571미니스톱 앞원천119안전센터YY19960.74.580.0수원소방서031-8012-95392023-05-31
29133양촌-4231경기도김포시41570경기도 김포시 양촌읍 양곡리 1539N37.6516025651126.62889김포한강아이파크아파트 309동양촌119안전센터YY20101.05.0100.0김포소방서031-980-45142023-05-31
14874(시)구갈010호5경기도용인시 기흥구41463경기도 용인시 기흥구 구갈동 619N37.2738817492127.127244성지중학교 정문구갈119안전센터NY20191.55.0100.0용인소방서031-8021-04132023-05-31
1114274호1경기도화성시41590경기도 화성시 팔탄면 구장리 527-1경기도 화성시 팔탄면 구장길 1-337.1607292226126.904126농협후면팔탄119안전센터YY20041.55.0200.0화성소방서031-8012-64132023-05-31
20670시관리 옥정 117호1경기도양주시41630경기도 양주시 옥정동 935N37.8175900983127.086981대방1차아파트 앞옥정119안전센터YY20121.05.0600.0양주소방서031-849-84122023-05-31
24233원당 46호1경기도고양시41281경기도 고양시 덕양구 관산동 674-10경기도 고양시 덕양구 고골길137.7088232946126.854804고골교차로원당119안전센터NY20071.03.7400.0고양소방서031-931-01192023-05-31