Overview

Dataset statistics

Number of variables22
Number of observations8547
Missing cells295
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory182.0 B

Variable types

Numeric6
Text8
Categorical7
Boolean1

Dataset

Description경남지역 소방용수시설 현황 자료로, 상세위치, 안전센터명, 보호틀 유무, 설치연도, 배관깊이(m), 출수압력(㎏/㎠), 배관지름(mm), 소방용수표지설치 여부 등에 대한 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15100830/fileData.do

Alerts

수리형식 is highly imbalanced (77.4%)Imbalance
시도명 is highly imbalanced (99.4%)Imbalance
보호틀유무 is highly imbalanced (54.5%)Imbalance
사용가능여부 is highly imbalanced (90.9%)Imbalance
설치주체 is highly imbalanced (76.2%)Imbalance
소재지도로명주소 has 117 (1.4%) missing valuesMissing
연번 has unique valuesUnique
배관깊이(미터) has 171 (2.0%) zerosZeros
배관지름(밀리미터) has 170 (2.0%) zerosZeros

Reproduction

Analysis started2023-12-12 21:23:57.392155
Analysis finished2023-12-12 21:23:59.168128
Duration1.78 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct8547
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4274
Minimum1
Maximum8547
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.2 KiB
2023-12-13T06:23:59.225645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile428.3
Q12137.5
median4274
Q36410.5
95-th percentile8119.7
Maximum8547
Range8546
Interquartile range (IQR)4273

Descriptive statistics

Standard deviation2467.4507
Coefficient of variation (CV)0.5773165
Kurtosis-1.2
Mean4274
Median Absolute Deviation (MAD)2137
Skewness0
Sum36529878
Variance6088313
MonotonicityStrictly increasing
2023-12-13T06:23:59.333672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
5695 1
 
< 0.1%
5709 1
 
< 0.1%
5708 1
 
< 0.1%
5707 1
 
< 0.1%
5706 1
 
< 0.1%
5705 1
 
< 0.1%
5704 1
 
< 0.1%
5703 1
 
< 0.1%
5702 1
 
< 0.1%
Other values (8537) 8537
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
8547 1
< 0.1%
8546 1
< 0.1%
8545 1
< 0.1%
8544 1
< 0.1%
8543 1
< 0.1%
8542 1
< 0.1%
8541 1
< 0.1%
8540 1
< 0.1%
8539 1
< 0.1%
8538 1
< 0.1%

시설번호(자체 관리번호)
Text

Distinct7763
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size66.9 KiB
2023-12-13T06:23:59.814530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length7.014976
Min length3

Characters and Unicode

Total characters59957
Distinct characters116
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7179 ?
Unique (%)84.0%

Sample

1st row상대-상-01
2nd row상대-상-02
3rd row상대-상-03
4th row상대-상-05
5th row상대-상-06
ValueCountFrequency (%)
1-c-1 4
 
< 0.1%
1-c-2 4
 
< 0.1%
1-a-100 4
 
< 0.1%
1-a-101 4
 
< 0.1%
2-a-14 3
 
< 0.1%
2-a-37 3
 
< 0.1%
2-a-38 3
 
< 0.1%
2-a-39 3
 
< 0.1%
2-a-40 3
 
< 0.1%
2-a-17 3
 
< 0.1%
Other values (7702) 8516
99.6%
2023-12-13T06:24:00.217382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 16957
28.3%
1 6145
 
10.2%
0 4649
 
7.8%
상 3978
 
6.6%
2 3207
 
5.3%
A 3001
 
5.0%
3 2657
 
4.4%
4 2120
 
3.5%
5 2032
 
3.4%
6 1605
 
2.7%
Other values (106) 13606
22.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26267
43.8%
Dash Punctuation 16957
28.3%
Other Letter 13324
22.2%
Uppercase Letter 3232
 
5.4%
Space Separator 177
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 3978
29.9%
지 574
 
4.3%
산 392
 
2.9%
하 355
 
2.7%
삼 346
 
2.6%
함 284
 
2.1%
안 271
 
2.0%
초 237
 
1.8%
가 232
 
1.7%
문 229
 
1.7%
Other values (90) 6426
48.2%
Decimal Number
ValueCountFrequency (%)
1 6145
23.4%
0 4649
17.7%
2 3207
12.2%
3 2657
10.1%
4 2120
 
8.1%
5 2032
 
7.7%
6 1605
 
6.1%
7 1467
 
5.6%
8 1244
 
4.7%
9 1141
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
A 3001
92.9%
B 151
 
4.7%
C 78
 
2.4%
D 2
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 16957
100.0%
Space Separator
ValueCountFrequency (%)
177
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43401
72.4%
Hangul 13324
 
22.2%
Latin 3232
 
5.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 3978
29.9%
지 574
 
4.3%
산 392
 
2.9%
하 355
 
2.7%
삼 346
 
2.6%
함 284
 
2.1%
안 271
 
2.0%
초 237
 
1.8%
가 232
 
1.7%
문 229
 
1.7%
Other values (90) 6426
48.2%
Common
ValueCountFrequency (%)
- 16957
39.1%
1 6145
 
14.2%
0 4649
 
10.7%
2 3207
 
7.4%
3 2657
 
6.1%
4 2120
 
4.9%
5 2032
 
4.7%
6 1605
 
3.7%
7 1467
 
3.4%
8 1244
 
2.9%
Other values (2) 1318
 
3.0%
Latin
ValueCountFrequency (%)
A 3001
92.9%
B 151
 
4.7%
C 78
 
2.4%
D 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46633
77.8%
Hangul 13324
 
22.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 16957
36.4%
1 6145
 
13.2%
0 4649
 
10.0%
2 3207
 
6.9%
A 3001
 
6.4%
3 2657
 
5.7%
4 2120
 
4.5%
5 2032
 
4.4%
6 1605
 
3.4%
7 1467
 
3.1%
Other values (6) 2793
 
6.0%
Hangul
ValueCountFrequency (%)
상 3978
29.9%
지 574
 
4.3%
산 392
 
2.9%
하 355
 
2.7%
삼 346
 
2.6%
함 284
 
2.1%
안 271
 
2.0%
초 237
 
1.8%
가 232
 
1.7%
문 229
 
1.7%
Other values (90) 6426
48.2%

수리형식
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.9 KiB
지상식
7914 
지하식
 
440
저수조
 
185
급수탑
 
8

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지상식 7914
92.6%
지하식 440
 
5.1%
저수조 185
 
2.2%
급수탑 8
 
0.1%

Length

2023-12-13T06:24:00.326938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:24:00.410393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지상식 7914
92.6%
지하식 440
 
5.1%
저수조 185
 
2.2%
급수탑 8
 
0.1%

시도명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.9 KiB
경상남도
8543 
경상남도
 
4

Length

Max length5
Median length4
Mean length4.000468
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 8543
> 99.9%
경상남도 4
 
< 0.1%

Length

2023-12-13T06:24:00.497882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:24:00.575850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 8547
100.0%

시군구명
Categorical

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.9 KiB
김해시
1427 
진주시
1083 
양산시
873 
통영시
618 
사천시
583 
Other values (13)
3963 

Length

Max length4
Median length3
Mean length3.023985
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
김해시 1427
16.7%
진주시 1083
12.7%
양산시 873
10.2%
통영시 618
 
7.2%
사천시 583
 
6.8%
거제시 573
 
6.7%
함안군 536
 
6.3%
밀양시 456
 
5.3%
고성군 430
 
5.0%
창녕군 404
 
4.7%
Other values (8) 1564
18.3%

Length

2023-12-13T06:24:00.658557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
김해시 1427
16.7%
진주시 1083
12.7%
양산시 873
10.2%
통영시 618
 
7.2%
사천시 583
 
6.8%
거제시 573
 
6.7%
함안군 536
 
6.3%
밀양시 456
 
5.3%
고성군 430
 
5.0%
창녕군 404
 
4.7%
Other values (7) 1564
18.3%

시군코드
Real number (ℝ)

Distinct24
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48445.719
Minimum48170
Maximum53700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.2 KiB
2023-12-13T06:24:00.743901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum48170
5-th percentile48170
Q148240
median48310
Q348740
95-th percentile48880
Maximum53700
Range5530
Interquartile range (IQR)500

Descriptive statistics

Standard deviation306.23516
Coefficient of variation (CV)0.0063212017
Kurtosis51.01894
Mean48445.719
Median Absolute Deviation (MAD)90
Skewness3.8036224
Sum4.1406556 × 108
Variance93779.975
MonotonicityNot monotonic
2023-12-13T06:24:00.828898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
48250 1427
16.7%
48170 1083
12.7%
48330 873
10.2%
48220 618
 
7.2%
48240 583
 
6.8%
48310 569
 
6.7%
48730 534
 
6.2%
48270 456
 
5.3%
48820 430
 
5.0%
48740 404
 
4.7%
Other values (14) 1570
18.4%
ValueCountFrequency (%)
48170 1083
12.7%
48220 618
7.2%
48240 583
6.8%
48250 1427
16.7%
48270 456
 
5.3%
48310 569
 
6.7%
48330 873
10.2%
48720 239
 
2.8%
48730 534
 
6.2%
48731 2
 
< 0.1%
ValueCountFrequency (%)
53700 4
 
< 0.1%
52153 1
 
< 0.1%
52151 1
 
< 0.1%
52150 1
 
< 0.1%
52140 1
 
< 0.1%
52138 1
 
< 0.1%
48890 295
3.5%
48880 235
2.7%
48870 296
3.5%
48860 188
2.2%

소재지도로명주소
Text

MISSING 

Distinct7909
Distinct (%)93.8%
Missing117
Missing (%)1.4%
Memory size66.9 KiB
2023-12-13T06:24:01.136846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length32
Mean length20.12325
Min length14

Characters and Unicode

Total characters169639
Distinct characters402
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

Unique7565 ?
Unique (%)89.7%

Sample

1st row경상남도 진주시 남강로 881번길 9
2nd row경상남도 진주시 동진로 105
3rd row경상남도 진주시 동진로 121
4th row경상남도 진주시 동진로 155
5th row경상남도 진주시 솔밭로 141
ValueCountFrequency (%)
경상남도 8429
 
21.3%
김해시 1417
 
3.6%
진주시 1082
 
2.7%
양산시 873
 
2.2%
통영시 598
 
1.5%
사천시 584
 
1.5%
거제시 518
 
1.3%
함안군 506
 
1.3%
밀양시 456
 
1.2%
고성군 428
 
1.1%
Other values (6270) 24640
62.3%
2023-12-13T06:24:01.602973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31815
18.8%
남 9428
 
5.6%
상 8819
 
5.2%
도 8738
 
5.2%
경 8483
 
5.0%
1 6129
 
3.6%
시 5638
 
3.3%
로 5336
 
3.1%
길 4619
 
2.7%
2 4038
 
2.4%
Other values (392) 76596
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 108412
63.9%
Space Separator 31815
 
18.8%
Decimal Number 27643
 
16.3%
Dash Punctuation 1749
 
1.0%
Open Punctuation 6
 
< 0.1%
Close Punctuation 6
 
< 0.1%
Lowercase Letter 4
 
< 0.1%
Uppercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 9428
 
8.7%
상 8819
 
8.1%
도 8738
 
8.1%
경 8483
 
7.8%
시 5638
 
5.2%
로 5336
 
4.9%
길 4619
 
4.3%
면 3709
 
3.4%
군 2998
 
2.8%
산 2519
 
2.3%
Other values (370) 48125
44.4%
Decimal Number
ValueCountFrequency (%)
1 6129
22.2%
2 4038
14.6%
3 3028
11.0%
4 2606
9.4%
5 2443
 
8.8%
6 2186
 
7.9%
7 1981
 
7.2%
9 1775
 
6.4%
8 1741
 
6.3%
0 1716
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
m 1
25.0%
f 1
25.0%
l 1
25.0%
r 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
H 1
50.0%
Space Separator
ValueCountFrequency (%)
31815
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1749
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 108412
63.9%
Common 61221
36.1%
Latin 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 9428
 
8.7%
상 8819
 
8.1%
도 8738
 
8.1%
경 8483
 
7.8%
시 5638
 
5.2%
로 5336
 
4.9%
길 4619
 
4.3%
면 3709
 
3.4%
군 2998
 
2.8%
산 2519
 
2.3%
Other values (370) 48125
44.4%
Common
ValueCountFrequency (%)
31815
52.0%
1 6129
 
10.0%
2 4038
 
6.6%
3 3028
 
4.9%
4 2606
 
4.3%
5 2443
 
4.0%
6 2186
 
3.6%
7 1981
 
3.2%
9 1775
 
2.9%
- 1749
 
2.9%
Other values (6) 3471
 
5.7%
Latin
ValueCountFrequency (%)
m 1
16.7%
G 1
16.7%
H 1
16.7%
f 1
16.7%
l 1
16.7%
r 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 108412
63.9%
ASCII 61227
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31815
52.0%
1 6129
 
10.0%
2 4038
 
6.6%
3 3028
 
4.9%
4 2606
 
4.3%
5 2443
 
4.0%
6 2186
 
3.6%
7 1981
 
3.2%
9 1775
 
2.9%
- 1749
 
2.9%
Other values (12) 3477
 
5.7%
Hangul
ValueCountFrequency (%)
남 9428
 
8.7%
상 8819
 
8.1%
도 8738
 
8.1%
경 8483
 
7.8%
시 5638
 
5.2%
로 5336
 
4.9%
길 4619
 
4.3%
면 3709
 
3.4%
군 2998
 
2.8%
산 2519
 
2.3%
Other values (370) 48125
44.4%

소재지지번주소
Text

Distinct8017
Distinct (%)93.8%
Missing1
Missing (%)< 0.1%
Memory size66.9 KiB
2023-12-13T06:24:01.956709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length34
Mean length20.518956
Min length12

Characters and Unicode

Total characters175355
Distinct characters359
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

Unique7616 ?
Unique (%)89.1%

Sample

1st row경상남도 진주시 상대동 730-53
2nd row경상남도 진주시 상대동 295-8
3rd row경상남도 진주시 상대동 291-23
4th row경상남도 진주시 상대동 284
5th row경상남도 진주시 상대동 288-11
ValueCountFrequency (%)
경상남도 8544
 
21.6%
김해시 1427
 
3.6%
진주시 1081
 
2.7%
양산시 871
 
2.2%
통영시 618
 
1.6%
사천시 582
 
1.5%
거제시 573
 
1.4%
함안군 513
 
1.3%
밀양시 455
 
1.1%
고성군 430
 
1.1%
Other values (7658) 24541
61.9%
2023-12-13T06:24:02.428514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31631
18.0%
남 9339
 
5.3%
상 9165
 
5.2%
도 8884
 
5.1%
경 8575
 
4.9%
1 7764
 
4.4%
- 6529
 
3.7%
시 5651
 
3.2%
리 5591
 
3.2%
2 4360
 
2.5%
Other values (349) 77866
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 102268
58.3%
Decimal Number 34914
 
19.9%
Space Separator 31631
 
18.0%
Dash Punctuation 6529
 
3.7%
Lowercase Letter 7
 
< 0.1%
Uppercase Letter 4
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 9339
 
9.1%
상 9165
 
9.0%
도 8884
 
8.7%
경 8575
 
8.4%
시 5651
 
5.5%
리 5591
 
5.5%
동 3979
 
3.9%
면 3793
 
3.7%
군 3035
 
3.0%
산 2039
 
2.0%
Other values (327) 42217
41.3%
Decimal Number
ValueCountFrequency (%)
1 7764
22.2%
2 4360
12.5%
3 3695
10.6%
5 3171
9.1%
4 3131
9.0%
6 2789
 
8.0%
7 2681
 
7.7%
8 2669
 
7.6%
0 2352
 
6.7%
9 2302
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
e 2
28.6%
f 2
28.6%
o 2
28.6%
d 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
S 1
25.0%
P 1
25.0%
N 1
25.0%
C 1
25.0%
Space Separator
ValueCountFrequency (%)
31631
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6529
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 102268
58.3%
Common 73076
41.7%
Latin 11
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 9339
 
9.1%
상 9165
 
9.0%
도 8884
 
8.7%
경 8575
 
8.4%
시 5651
 
5.5%
리 5591
 
5.5%
동 3979
 
3.9%
면 3793
 
3.7%
군 3035
 
3.0%
산 2039
 
2.0%
Other values (327) 42217
41.3%
Common
ValueCountFrequency (%)
31631
43.3%
1 7764
 
10.6%
- 6529
 
8.9%
2 4360
 
6.0%
3 3695
 
5.1%
5 3171
 
4.3%
4 3131
 
4.3%
6 2789
 
3.8%
7 2681
 
3.7%
8 2669
 
3.7%
Other values (4) 4656
 
6.4%
Latin
ValueCountFrequency (%)
e 2
18.2%
f 2
18.2%
o 2
18.2%
S 1
9.1%
P 1
9.1%
N 1
9.1%
d 1
9.1%
C 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 102268
58.3%
ASCII 73087
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31631
43.3%
1 7764
 
10.6%
- 6529
 
8.9%
2 4360
 
6.0%
3 3695
 
5.1%
5 3171
 
4.3%
4 3131
 
4.3%
6 2789
 
3.8%
7 2681
 
3.7%
8 2669
 
3.7%
Other values (12) 4667
 
6.4%
Hangul
ValueCountFrequency (%)
남 9339
 
9.1%
상 9165
 
9.0%
도 8884
 
8.7%
경 8575
 
8.4%
시 5651
 
5.5%
리 5591
 
5.5%
동 3979
 
3.9%
면 3793
 
3.7%
군 3035
 
3.0%
산 2039
 
2.0%
Other values (327) 42217
41.3%

위도
Text

Distinct8380
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size66.9 KiB
2023-12-13T06:24:02.715060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length8.9301509
Min length6

Characters and Unicode

Total characters76326
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8225 ?
Unique (%)96.2%

Sample

1st row35.180839
2nd row35.179397
3rd row35.179447
4th row35.179702
5th row35.181777
ValueCountFrequency (%)
35.319584 3
 
< 0.1%
35.275852 3
 
< 0.1%
35.476 3
 
< 0.1%
35.31042 3
 
< 0.1%
35.306638 3
 
< 0.1%
34.97813 3
 
< 0.1%
34.8809123 3
 
< 0.1%
35.307372 3
 
< 0.1%
34.829576 3
 
< 0.1%
35.259198 3
 
< 0.1%
Other values (8370) 8517
99.6%
2023-12-13T06:24:03.137482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 14318
18.8%
5 11286
14.8%
. 8546
11.2%
4 6920
9.1%
2 5857
7.7%
1 5848
7.7%
8 5363
 
7.0%
9 5047
 
6.6%
7 4764
 
6.2%
6 4751
 
6.2%
Other values (2) 3626
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67777
88.8%
Other Punctuation 8549
 
11.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 14318
21.1%
5 11286
16.7%
4 6920
10.2%
2 5857
8.6%
1 5848
8.6%
8 5363
 
7.9%
9 5047
 
7.4%
7 4764
 
7.0%
6 4751
 
7.0%
0 3623
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 8546
> 99.9%
' 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 76326
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 14318
18.8%
5 11286
14.8%
. 8546
11.2%
4 6920
9.1%
2 5857
7.7%
1 5848
7.7%
8 5363
 
7.0%
9 5047
 
6.6%
7 4764
 
6.2%
6 4751
 
6.2%
Other values (2) 3626
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76326
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 14318
18.8%
5 11286
14.8%
. 8546
11.2%
4 6920
9.1%
2 5857
7.7%
1 5848
7.7%
8 5363
 
7.0%
9 5047
 
6.6%
7 4764
 
6.2%
6 4751
 
6.2%
Other values (2) 3626
 
4.8%

경도
Text

Distinct8396
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size66.9 KiB
2023-12-13T06:24:03.530935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.9248859
Min length7

Characters and Unicode

Total characters84828
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8259 ?
Unique (%)96.6%

Sample

1st row128.101546
2nd row128.102865
3rd row128.104407
4th row128.107293
5th row128.106752
ValueCountFrequency (%)
128.762817 3
 
< 0.1%
127.892891 3
 
< 0.1%
127.795192 3
 
< 0.1%
128.3436 3
 
< 0.1%
128.735351 3
 
< 0.1%
127.626723 3
 
< 0.1%
128.742315 3
 
< 0.1%
128.07779 3
 
< 0.1%
128.874895 3
 
< 0.1%
128.419133 3
 
< 0.1%
Other values (8386) 8517
99.6%
2023-12-13T06:24:03.982252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14157
16.7%
2 13672
16.1%
8 12139
14.3%
. 8547
10.1%
7 6404
7.5%
9 5585
 
6.6%
4 5227
 
6.2%
3 5005
 
5.9%
0 4906
 
5.8%
6 4707
 
5.5%
Other values (2) 4479
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76279
89.9%
Other Punctuation 8549
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14157
18.6%
2 13672
17.9%
8 12139
15.9%
7 6404
8.4%
9 5585
 
7.3%
4 5227
 
6.9%
3 5005
 
6.6%
0 4906
 
6.4%
6 4707
 
6.2%
5 4477
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 8547
> 99.9%
' 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 84828
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14157
16.7%
2 13672
16.1%
8 12139
14.3%
. 8547
10.1%
7 6404
7.5%
9 5585
 
6.6%
4 5227
 
6.2%
3 5005
 
5.9%
0 4906
 
5.8%
6 4707
 
5.5%
Other values (2) 4479
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84828
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14157
16.7%
2 13672
16.1%
8 12139
14.3%
. 8547
10.1%
7 6404
7.5%
9 5585
 
6.6%
4 5227
 
6.2%
3 5005
 
5.9%
0 4906
 
5.8%
6 4707
 
5.5%
Other values (2) 4479
 
5.3%

상세위치
Text

Distinct7996
Distinct (%)93.6%
Missing1
Missing (%)< 0.1%
Memory size66.9 KiB
2023-12-13T06:24:04.288732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length42
Mean length9.6887433
Min length2

Characters and Unicode

Total characters82800
Distinct characters863
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

Unique7761 ?
Unique (%)90.8%

Sample

1st row구,법원뒷편 후문 80m
2nd row디럭스빌딩(한보프라자) 주차장 입구
3rd row가나신협앞 인도상
4th row진주시청 남서편 인도상 (진주시청 사거리)
5th row모란아파트 앞 인도상
ValueCountFrequency (%)
앞 2879
 
14.3%
옆 861
 
4.3%
입구 458
 
2.3%
맞은편 411
 
2.0%
주택 226
 
1.1%
인도상 222
 
1.1%
정문 180
 
0.9%
삼거리 161
 
0.8%
인근 150
 
0.7%
내 140
 
0.7%
Other values (9142) 14418
71.7%
2023-12-13T06:24:04.749281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11890
 
14.4%
앞 3139
 
3.8%
마 1428
 
1.7%
동 1220
 
1.5%
을 1191
 
1.4%
도 978
 
1.2%
회 963
 
1.2%
옆 946
 
1.1%
지 920
 
1.1%
리 920
 
1.1%
Other values (853) 59205
71.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65211
78.8%
Space Separator 11890
 
14.4%
Decimal Number 2898
 
3.5%
Uppercase Letter 1002
 
1.2%
Close Punctuation 490
 
0.6%
Open Punctuation 470
 
0.6%
Lowercase Letter 290
 
0.4%
Other Punctuation 236
 
0.3%
Other Symbol 169
 
0.2%
Dash Punctuation 123
 
0.1%
Other values (2) 21
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 3139
 
4.8%
마 1428
 
2.2%
동 1220
 
1.9%
을 1191
 
1.8%
도 978
 
1.5%
회 963
 
1.5%
옆 946
 
1.5%
지 920
 
1.4%
리 920
 
1.4%
주 909
 
1.4%
Other values (776) 52597
80.7%
Uppercase Letter
ValueCountFrequency (%)
S 132
13.2%
M 101
 
10.1%
C 89
 
8.9%
G 78
 
7.8%
T 61
 
6.1%
K 57
 
5.7%
P 55
 
5.5%
L 53
 
5.3%
H 53
 
5.3%
A 38
 
3.8%
Other values (15) 285
28.4%
Lowercase Letter
ValueCountFrequency (%)
m 153
52.8%
e 20
 
6.9%
c 15
 
5.2%
t 15
 
5.2%
k 13
 
4.5%
s 11
 
3.8%
r 9
 
3.1%
u 9
 
3.1%
l 6
 
2.1%
i 6
 
2.1%
Other values (12) 33
 
11.4%
Decimal Number
ValueCountFrequency (%)
1 847
29.2%
0 504
17.4%
2 431
14.9%
3 243
 
8.4%
5 224
 
7.7%
9 216
 
7.5%
4 144
 
5.0%
7 107
 
3.7%
6 98
 
3.4%
8 84
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 122
51.7%
. 63
26.7%
& 18
 
7.6%
: 16
 
6.8%
/ 9
 
3.8%
@ 4
 
1.7%
" 2
 
0.8%
＆ 1
 
0.4%
' 1
 
0.4%
Math Symbol
ValueCountFrequency (%)
~ 17
85.0%
< 1
 
5.0%
> 1
 
5.0%
+ 1
 
5.0%
Close Punctuation
ValueCountFrequency (%)
) 489
99.8%
] 1
 
0.2%
Space Separator
ValueCountFrequency (%)
11890
100.0%
Open Punctuation
ValueCountFrequency (%)
( 470
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 169
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 123
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 65379
79.0%
Common 16127
 
19.5%
Latin 1293
 
1.6%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 3139
 
4.8%
마 1428
 
2.2%
동 1220
 
1.9%
을 1191
 
1.8%
도 978
 
1.5%
회 963
 
1.5%
옆 946
 
1.4%
지 920
 
1.4%
리 920
 
1.4%
주 909
 
1.4%
Other values (776) 52765
80.7%
Latin
ValueCountFrequency (%)
m 153
 
11.8%
S 132
 
10.2%
M 101
 
7.8%
C 89
 
6.9%
G 78
 
6.0%
T 61
 
4.7%
K 57
 
4.4%
P 55
 
4.3%
L 53
 
4.1%
H 53
 
4.1%
Other values (38) 461
35.7%
Common
ValueCountFrequency (%)
11890
73.7%
1 847
 
5.3%
0 504
 
3.1%
) 489
 
3.0%
( 470
 
2.9%
2 431
 
2.7%
3 243
 
1.5%
5 224
 
1.4%
9 216
 
1.3%
4 144
 
0.9%
Other values (18) 669
 
4.1%
Han
ValueCountFrequency (%)
愛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 65210
78.8%
ASCII 17418
 
21.0%
None 170
 
0.2%
Number Forms 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11890
68.3%
1 847
 
4.9%
0 504
 
2.9%
) 489
 
2.8%
( 470
 
2.7%
2 431
 
2.5%
3 243
 
1.4%
5 224
 
1.3%
9 216
 
1.2%
m 153
 
0.9%
Other values (64) 1951
 
11.2%
Hangul
ValueCountFrequency (%)
앞 3139
 
4.8%
마 1428
 
2.2%
동 1220
 
1.9%
을 1191
 
1.8%
도 978
 
1.5%
회 963
 
1.5%
옆 946
 
1.5%
지 920
 
1.4%
리 920
 
1.4%
주 909
 
1.4%
Other values (775) 52596
80.7%
None
ValueCountFrequency (%)
㈜ 169
99.4%
＆ 1
 
0.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
CJK
ValueCountFrequency (%)
愛 1
100.0%

안전센터명
Text

Distinct84
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size66.9 KiB
2023-12-13T06:24:04.989150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.9138879
Min length4

Characters and Unicode

Total characters76187
Distinct characters90
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

Unique0 ?
Unique (%)0.0%

Sample

1st row상대119안전센터
2nd row상대119안전센터
3rd row상대119안전센터
4th row상대119안전센터
5th row상대119안전센터
ValueCountFrequency (%)
중앙119안전센터 263
 
3.1%
문산119안전센터 259
 
3.0%
고성119안전센터 232
 
2.7%
동금119안전센터 217
 
2.5%
창녕119안전센터 196
 
2.3%
대평119안전센터 194
 
2.3%
함양119안전센터 194
 
2.3%
가야119안전센터 192
 
2.2%
정촌119안전센터 190
 
2.2%
죽림119안전센터 187
 
2.2%
Other values (74) 6423
75.1%
2023-12-13T06:24:05.321950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16756
22.0%
전 8421
11.1%
9 8378
11.0%
안 8365
11.0%
센 8227
10.8%
터 8227
10.8%
동 803
 
1.1%
산 724
 
1.0%
대 661
 
0.9%
남 550
 
0.7%
Other values (80) 15075
19.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51053
67.0%
Decimal Number 25134
33.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 8421
16.5%
안 8365
16.4%
센 8227
16.1%
터 8227
16.1%
동 803
 
1.6%
산 724
 
1.4%
대 661
 
1.3%
남 550
 
1.1%
상 545
 
1.1%
북 478
 
0.9%
Other values (78) 14052
27.5%
Decimal Number
ValueCountFrequency (%)
1 16756
66.7%
9 8378
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51053
67.0%
Common 25134
33.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 8421
16.5%
안 8365
16.4%
센 8227
16.1%
터 8227
16.1%
동 803
 
1.6%
산 724
 
1.4%
대 661
 
1.3%
남 550
 
1.1%
상 545
 
1.1%
북 478
 
0.9%
Other values (78) 14052
27.5%
Common
ValueCountFrequency (%)
1 16756
66.7%
9 8378
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51053
67.0%
ASCII 25134
33.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16756
66.7%
9 8378
33.3%
Hangul
ValueCountFrequency (%)
전 8421
16.5%
안 8365
16.4%
센 8227
16.1%
터 8227
16.1%
동 803
 
1.6%
산 724
 
1.4%
대 661
 
1.3%
남 550
 
1.1%
상 545
 
1.1%
북 478
 
0.9%
Other values (78) 14052
27.5%

보호틀유무
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.9 KiB
N
5790 
Y
2755 
N
 
1
<NA>
 
1

Length

Max length4
Median length1
Mean length1.000468
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowN
2nd rowY
3rd rowY
4th rowY
5th rowY

Common Values

ValueCountFrequency (%)
N 5790
67.7%
Y 2755
32.2%
N 1
 
< 0.1%
<NA> 1
 
< 0.1%

Length

2023-12-13T06:24:05.441513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:24:05.542926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 5791
67.8%
y 2755
32.2%
na 1
 
< 0.1%

사용가능여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size8.5 KiB
True
8448 
False
 
99
ValueCountFrequency (%)
True 8448
98.8%
False 99
 
1.2%
2023-12-13T06:24:05.635940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

설치연도
Real number (ℝ)

Distinct56
Distinct (%)0.7%
Missing7
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean2007.8667
Minimum1900
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.2 KiB
2023-12-13T06:24:05.739104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1900
5-th percentile1988
Q12002
median2009
Q32015
95-th percentile2021
Maximum2023
Range123
Interquartile range (IQR)13

Descriptive statistics

Standard deviation9.9132574
Coefficient of variation (CV)0.0049372088
Kurtosis2.4144748
Mean2007.8667
Median Absolute Deviation (MAD)7
Skewness-1.0258361
Sum17147182
Variance98.272673
MonotonicityNot monotonic
2023-12-13T06:24:05.862701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2007 497
 
5.8%
2006 471
 
5.5%
2016 440
 
5.1%
2011 383
 
4.5%
2013 362
 
4.2%
2020 353
 
4.1%
2015 344
 
4.0%
2001 343
 
4.0%
2012 339
 
4.0%
2019 328
 
3.8%
Other values (46) 4680
54.8%
ValueCountFrequency (%)
1900 1
 
< 0.1%
1950 3
< 0.1%
1966 3
< 0.1%
1968 1
 
< 0.1%
1970 1
 
< 0.1%
1972 2
< 0.1%
1973 2
< 0.1%
1974 4
< 0.1%
1975 2
< 0.1%
1976 4
< 0.1%
ValueCountFrequency (%)
2023 73
 
0.9%
2022 158
 
1.8%
2021 294
3.4%
2020 353
4.1%
2019 328
3.8%
2018 296
3.5%
2017 186
2.2%
2016 440
5.1%
2015 344
4.0%
2014 320
3.7%

배관깊이(미터)
Real number (ℝ)

ZEROS 

Distinct30
Distinct (%)0.4%
Missing30
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean1.1531056
Minimum0
Maximum8.1
Zeros171
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size75.2 KiB
2023-12-13T06:24:06.007628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.5
Q10.5
median1
Q31
95-th percentile3
Maximum8.1
Range8.1
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation1.515099
Coefficient of variation (CV)1.3139291
Kurtosis14.8113
Mean1.1531056
Median Absolute Deviation (MAD)0.4
Skewness3.9236917
Sum9821
Variance2.2955249
MonotonicityNot monotonic
2023-12-13T06:24:06.142658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1.0 3394
39.7%
0.5 2829
33.1%
0.6 440
 
5.1%
8.1 334
 
3.9%
1.5 250
 
2.9%
0.0 171
 
2.0%
1.1 162
 
1.9%
0.8 134
 
1.6%
1.3 105
 
1.2%
0.7 97
 
1.1%
Other values (20) 601
 
7.0%
ValueCountFrequency (%)
0.0 171
 
2.0%
0.1 6
 
0.1%
0.2 14
 
0.2%
0.3 37
 
0.4%
0.4 65
 
0.8%
0.5 2829
33.1%
0.6 440
 
5.1%
0.7 97
 
1.1%
0.8 134
 
1.6%
0.9 66
 
0.8%
ValueCountFrequency (%)
8.1 334
3.9%
6.0 3
 
< 0.1%
5.5 14
 
0.2%
5.0 46
 
0.5%
4.5 9
 
0.1%
4.2 6
 
0.1%
4.0 7
 
0.1%
3.0 91
 
1.1%
2.5 1
 
< 0.1%
2.4 1
 
< 0.1%

출수압력
Real number (ℝ)

Distinct63
Distinct (%)0.7%
Missing82
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean3.7178854
Minimum0
Maximum10
Zeros61
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size75.2 KiB
2023-12-13T06:24:06.269579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.3
Q13
median3.5
Q34.6
95-th percentile5.5
Maximum10
Range10
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.1909846
Coefficient of variation (CV)0.32033924
Kurtosis2.0930789
Mean3.7178854
Median Absolute Deviation (MAD)0.5
Skewness0.81552199
Sum31471.9
Variance1.4184443
MonotonicityNot monotonic
2023-12-13T06:24:06.398231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.0 2423
28.3%
5.0 1561
18.3%
4.0 965
 
11.3%
3.5 952
 
11.1%
2.5 708
 
8.3%
4.5 262
 
3.1%
2.0 259
 
3.0%
6.0 163
 
1.9%
5.5 119
 
1.4%
3.2 114
 
1.3%
Other values (53) 939
 
11.0%
ValueCountFrequency (%)
0.0 61
 
0.7%
0.5 1
 
< 0.1%
1.0 12
 
0.1%
1.2 3
 
< 0.1%
1.3 2
 
< 0.1%
1.5 30
 
0.4%
1.6 2
 
< 0.1%
1.7 3
 
< 0.1%
1.8 2
 
< 0.1%
2.0 259
3.0%
ValueCountFrequency (%)
10.0 5
 
0.1%
9.5 3
 
< 0.1%
9.0 24
 
0.3%
8.5 3
 
< 0.1%
8.0 22
 
0.3%
7.8 1
 
< 0.1%
7.6 1
 
< 0.1%
7.5 17
 
0.2%
7.1 1
 
< 0.1%
7.0 103
1.2%

배관지름(밀리미터)
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)0.3%
Missing57
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean90.023675
Minimum0
Maximum600
Zeros170
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size75.2 KiB
2023-12-13T06:24:06.520254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile65
Q165
median100
Q3100
95-th percentile125
Maximum600
Range600
Interquartile range (IQR)35

Descriptive statistics

Standard deviation32.686934
Coefficient of variation (CV)0.36309264
Kurtosis55.514699
Mean90.023675
Median Absolute Deviation (MAD)0
Skewness4.3549673
Sum764301
Variance1068.4357
MonotonicityNot monotonic
2023-12-13T06:24:06.621089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
100 4811
56.3%
65 2174
25.4%
80 651
 
7.6%
150 173
 
2.0%
0 170
 
2.0%
50 119
 
1.4%
130 118
 
1.4%
200 87
 
1.0%
75 78
 
0.9%
60 26
 
0.3%
Other values (17) 83
 
1.0%
(Missing) 57
 
0.7%
ValueCountFrequency (%)
0 170
2.0%
13 1
 
< 0.1%
16 8
 
0.1%
20 2
 
< 0.1%
25 3
 
< 0.1%
30 1
 
< 0.1%
32 1
 
< 0.1%
40 10
 
0.1%
50 119
1.4%
60 26
 
0.3%
ValueCountFrequency (%)
600 6
 
0.1%
450 1
 
< 0.1%
400 5
 
0.1%
350 9
 
0.1%
300 10
 
0.1%
250 14
 
0.2%
200 87
1.0%
150 173
2.0%
130 118
1.4%
125 6
 
0.1%

관할소방서명
Categorical

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.9 KiB
진주소방서
1083 
양산소방서
873 
김해서부소방서
819 
통영소방서
618 
김해동부소방서
608 
Other values (14)
4546 

Length

Max length7
Median length5
Mean length5.3340353
Min length5

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
진주소방서 1083
12.7%
양산소방서 873
10.2%
김해서부소방서 819
9.6%
통영소방서 618
 
7.2%
김해동부소방서 608
 
7.1%
사천소방서 583
 
6.8%
거제소방서 573
 
6.7%
함안소방서 536
 
6.3%
밀양소방서 456
 
5.3%
고성소방서 430
 
5.0%
Other values (9) 1968
23.0%

Length

2023-12-13T06:24:06.741944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
진주소방서 1083
12.7%
양산소방서 873
10.2%
김해서부소방서 819
9.6%
통영소방서 618
 
7.2%
김해동부소방서 608
 
7.1%
사천소방서 583
 
6.8%
거제소방서 573
 
6.7%
함안소방서 536
 
6.3%
밀양소방서 456
 
5.3%
고성소방서 430
 
5.0%
Other values (8) 1968
23.0%

전화번호
Text

Distinct93
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size66.9 KiB
2023-12-13T06:24:06.915128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.004563
Min length12

Characters and Unicode

Total characters102603
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

Unique47 ?
Unique (%)0.5%

Sample

1st row055-760-9293
2nd row055-760-9293
3rd row055-760-9293
4th row055-760-9293
5th row055-760-9293
ValueCountFrequency (%)
055-760-9293 1083
 
12.7%
055-344-9295 819
 
9.6%
055-379-9284 748
 
8.8%
055-640-9295 618
 
7.2%
055-320-9294 608
 
7.1%
055-689-9265 573
 
6.7%
055-670-9295 430
 
5.0%
055-960-9283 296
 
3.5%
055-930-9293 295
 
3.5%
055-830-9295 229
 
2.7%
Other values (83) 2848
33.3%
2023-12-13T06:24:07.480963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 21993
21.4%
- 17094
16.7%
9 15977
15.6%
0 15193
14.8%
2 8352
 
8.1%
3 7339
 
7.2%
4 4752
 
4.6%
6 3996
 
3.9%
8 3546
 
3.5%
7 3449
 
3.4%
Other values (2) 912
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 85474
83.3%
Dash Punctuation 17094
 
16.7%
Space Separator 35
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 21993
25.7%
9 15977
18.7%
0 15193
17.8%
2 8352
 
9.8%
3 7339
 
8.6%
4 4752
 
5.6%
6 3996
 
4.7%
8 3546
 
4.1%
7 3449
 
4.0%
1 877
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 17094
100.0%
Space Separator
ValueCountFrequency (%)
35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 102603
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 21993
21.4%
- 17094
16.7%
9 15977
15.6%
0 15193
14.8%
2 8352
 
8.1%
3 7339
 
7.2%
4 4752
 
4.6%
6 3996
 
3.9%
8 3546
 
3.5%
7 3449
 
3.4%
Other values (2) 912
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 102603
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 21993
21.4%
- 17094
16.7%
9 15977
15.6%
0 15193
14.8%
2 8352
 
8.1%
3 7339
 
7.2%
4 4752
 
4.6%
6 3996
 
3.9%
8 3546
 
3.5%
7 3449
 
3.4%
Other values (2) 912
 
0.9%

소방용수표지설치
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.9 KiB
미설치
4767 
설치
3774 
미설치
 
6

Length

Max length4
Median length3
Mean length2.5591436
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미설치
2nd row설치
3rd row설치
4th row설치
5th row설치

Common Values

ValueCountFrequency (%)
미설치 4767
55.8%
설치 3774
44.2%
미설치 6
 
0.1%

Length

2023-12-13T06:24:07.636353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:24:07.741744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미설치 4773
55.8%
설치 3774
44.2%

설치주체
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.9 KiB
지자체
8213 
경상남도
 
334

Length

Max length4
Median length3
Mean length3.039078
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지자체 8213
96.1%
경상남도 334
 
3.9%

Length

2023-12-13T06:24:07.836695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:24:07.971383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지자체 8213
96.1%
경상남도 334
 
3.9%

Sample

연번시설번호(자체 관리번호)수리형식시도명시군구명시군코드소재지도로명주소소재지지번주소위도경도상세위치안전센터명보호틀유무사용가능여부설치연도배관깊이(미터)출수압력배관지름(밀리미터)관할소방서명전화번호소방용수표지설치설치주체
01상대-상-01지상식경상남도진주시48170경상남도 진주시 남강로 881번길 9경상남도 진주시 상대동 730-5335.180839128.101546구,법원뒷편 후문 80m상대119안전센터NY19791.03.565진주소방서055-760-9293미설치지자체
12상대-상-02지상식경상남도진주시48170경상남도 진주시 동진로 105경상남도 진주시 상대동 295-835.179397128.102865디럭스빌딩(한보프라자) 주차장 입구상대119안전센터YY19791.03.565진주소방서055-760-9293설치지자체
23상대-상-03지상식경상남도진주시48170경상남도 진주시 동진로 121경상남도 진주시 상대동 291-2335.179447128.104407가나신협앞 인도상상대119안전센터YY19791.03.565진주소방서055-760-9293설치지자체
34상대-상-05지상식경상남도진주시48170경상남도 진주시 동진로 155경상남도 진주시 상대동 28435.179702128.107293진주시청 남서편 인도상 (진주시청 사거리)상대119안전센터YY19791.03.565진주소방서055-760-9293설치지자체
45상대-상-06지상식경상남도진주시48170경상남도 진주시 솔밭로 141경상남도 진주시 상대동 288-1135.181777128.106752모란아파트 앞 인도상상대119안전센터YY19791.03.565진주소방서055-760-9293설치지자체
56상대-상-07지상식경상남도진주시48170경상남도 진주시 선학산길29번길 24-1경상남도 진주시 상대동 519-2135.186641128.10949우성아트빌 60m 지점상대119안전센터YY19811.03.565진주소방서055-760-9293미설치지자체
67상대-상-08지상식경상남도진주시48170경상남도 진주시 솔밭로 132번길 26경상남도 진주시 상대동 275-2435.181012128.109349자유시장북편 사거리 러브샵(의류) 앞상대119안전센터YY20191.03.565진주소방서055-760-9293설치지자체
78상대-상-10지상식경상남도진주시48170경상남도 진주시 동진로 189경상남도 진주시 상대동 299-335.179787128.112145상대동 행정복지센터 앞 (사거리)상대119안전센터YY19731.03.565진주소방서055-760-9293설치지자체
89상대-상-11지상식경상남도진주시48170경상남도 진주시 도동천로 117경상남도 진주시 상대동 246-435.181469128.112177진주동부농협 동명지점 앞 인도상상대119안전센터YY19791.03.565진주소방서055-760-9293설치지자체
910상대-상-13지상식경상남도진주시48170경상남도 진주시 돗골로 168경상남도 진주시 상대동 244-1835.183356128.112023동명아파트 입구 사거리 도로상상대119안전센터YY19791.03.565진주소방서055-760-9293설치지자체
연번시설번호(자체 관리번호)수리형식시도명시군구명시군코드소재지도로명주소소재지지번주소위도경도상세위치안전센터명보호틀유무사용가능여부설치연도배관깊이(미터)출수압력배관지름(밀리미터)관할소방서명전화번호소방용수표지설치설치주체
85378538부림-A-85지상식경상남도의령군48720경상남도 의령군 용덕면 덕암로 80경상남도 의령군 용덕면 죽전리 197-135.337222128.278764죽전리, 덕암노인회관 앞정곡119안전센터YY20150.52.080의령소방서055-570-9324설치지자체
85388539부림-A-86지상식경상남도의령군48720경상남도 의령군 용덕면 덕암로 90경상남도 의령군 용덕면 죽전리 158-135.335703128.280858죽전리, 성비마을 입구정곡119안전센터YY20150.53.080의령소방서055-570-9324설치지자체
85398540부림-A-87지상식경상남도의령군48720경상남도 의령군 용덕면 덕암로 120경상남도 의령군 용덕면 죽전리 426-335.337937128.277902죽전리, 상죽마을표지석 옆정곡119안전센터YY20150.53.080의령소방서055-570-9324설치지자체
85408541부림-A-88지상식경상남도의령군48720경상남도 의령군 용덕면 덕암로 148경상남도 의령군 용덕면 죽전리 414-135.339236128.276207죽전리 앞정곡119안전센터YY20150.53.080의령소방서055-570-9324설치지자체
85418542부림-A-89지상식경상남도의령군48720경상남도 의령군 용덕면 덕암로 270경상남도 의령군 용덕면 와요리 137-1335.348555128.269157와요리, 미곡마을 입구정곡119안전센터NY20150.53.080의령소방서055-570-9324미설치지자체
85428543부림-A-90지상식경상남도의령군48720경상남도 의령군 용덕면 덕암로10길 17-1경상남도 의령군 용덕면 이목리 86-335.376726128.268925이목리, 이목마을 회관 옆정곡119안전센터NY20080.52.080의령소방서055-570-9324미설치지자체
85438544부림-A-91지상식경상남도의령군48720경상남도 의령군 용덕면 덕암로 8길 6-1경상남도 의령군 용덕면 와요리 320-535.354482128.268529와요리, 와요마을 회관 옆정곡119안전센터NY20200.53.080의령소방서055-570-9324미설치지자체
85448545부림-B-1지하식경상남도의령군48720경상남도 의령군 부림면 대한로 1689경상남도 의령군 부림면 신반리 73835.464297128.317391신반리, 서동1구 마을회관 앞부림119안전센터NY20001.02.065의령소방서055-570-9324미설치지자체
85458546부림-B-2지하식경상남도의령군48720경상남도 의령군 부림면 신번로 157-1경상남도 의령군 부림면 신반리 545-4335.467415128.323943신반리, 꽃비카페 앞부림119안전센터NY20001.02.565의령소방서055-570-9324미설치지자체
85468547부림-C-1저수조경상남도의령군48720경상남도 의령군 부림면 신반리 대한로 1666경상남도 의령군 부림면 신반리 85835.463884128.314684신반리, 부림119안전센터부림119안전센터NY20040.5<NA><NA>의령소방서055-570-9324미설치지자체