Overview

Dataset statistics

Number of variables6
Number of observations224
Missing cells2
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.8 KiB
Average record size in memory49.6 B

Variable types

Numeric1
Categorical1
Text4

Dataset

Description2019년 기준 전국 소방서 (순번,본부명,소방서명, 주소, 전화번호, 팩스) 현황 정보입니다.
Author소방청
URLhttps://www.data.go.kr/data/15048243/fileData.do

Alerts

순번 is highly overall correlated with 본부명High correlation
본부명 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:17:51.079269
Analysis finished2023-12-12 13:17:51.746709
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct224
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.5
Minimum1
Maximum224
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T22:17:51.824658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.15
Q156.75
median112.5
Q3168.25
95-th percentile212.85
Maximum224
Range223
Interquartile range (IQR)111.5

Descriptive statistics

Standard deviation64.807407
Coefficient of variation (CV)0.57606584
Kurtosis-1.2
Mean112.5
Median Absolute Deviation (MAD)56
Skewness0
Sum25200
Variance4200
MonotonicityStrictly increasing
2023-12-12T22:17:51.956772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
114 1
 
0.4%
144 1
 
0.4%
145 1
 
0.4%
146 1
 
0.4%
147 1
 
0.4%
148 1
 
0.4%
149 1
 
0.4%
150 1
 
0.4%
151 1
 
0.4%
Other values (214) 214
95.5%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
224 1
0.4%
223 1
0.4%
222 1
0.4%
221 1
0.4%
220 1
0.4%
219 1
0.4%
218 1
0.4%
217 1
0.4%
216 1
0.4%
215 1
0.4%

본부명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
서울소방재난본부
24 
경기재난안전본부
22 
경북소방본부
19 
경남소방본부
18 
강원소방본부
18 
Other values (14)
123 

Length

Max length10
Median length6
Mean length6.8571429
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울소방재난본부 24
10.7%
경기재난안전본부 22
9.8%
경북소방본부 19
 
8.5%
경남소방본부 18
 
8.0%
강원소방본부 18
 
8.0%
전남소방본부 17
 
7.6%
충남소방본부 16
 
7.1%
경기북부소방재난본부 13
 
5.8%
전북소방본부 12
 
5.4%
충북소방본부 12
 
5.4%
Other values (9) 53
23.7%

Length

2023-12-12T22:17:52.115626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울소방재난본부 24
10.7%
경기재난안전본부 22
9.8%
경북소방본부 19
 
8.5%
경남소방본부 18
 
8.0%
강원소방본부 18
 
8.0%
전남소방본부 17
 
7.6%
충남소방본부 16
 
7.1%
경기북부소방재난본부 13
 
5.8%
충북소방본부 12
 
5.4%
전북소방본부 12
 
5.4%
Other values (9) 53
23.7%

소방서
Text

Distinct204
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T22:17:52.479044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1517857
Min length5

Characters and Unicode

Total characters1154
Distinct characters137
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique197 ?
Unique (%)87.9%

Sample

1st row강남소방서
2nd row강동소방서
3rd row강북소방서
4th row강서소방서
5th row관악소방서
ValueCountFrequency (%)
동부소방서 5
 
2.2%
중부소방서 5
 
2.2%
서부소방서 5
 
2.2%
북부소방서 4
 
1.8%
강서소방서 3
 
1.3%
남부소방서 3
 
1.3%
고성소방서 2
 
0.9%
고창소방서 1
 
0.4%
부안소방서 1
 
0.4%
남원소방서 1
 
0.4%
Other values (194) 194
86.6%
2023-12-12T22:17:52.985193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
서 241
20.9%
소 224
19.4%
방 224
19.4%
부 35
 
3.0%
천 22
 
1.9%
산 21
 
1.8%
주 20
 
1.7%
동 19
 
1.6%
양 17
 
1.5%
성 17
 
1.5%
Other values (127) 314
27.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1154
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 241
20.9%
소 224
19.4%
방 224
19.4%
부 35
 
3.0%
천 22
 
1.9%
산 21
 
1.8%
주 20
 
1.7%
동 19
 
1.6%
양 17
 
1.5%
성 17
 
1.5%
Other values (127) 314
27.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1154
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 241
20.9%
소 224
19.4%
방 224
19.4%
부 35
 
3.0%
천 22
 
1.9%
산 21
 
1.8%
주 20
 
1.7%
동 19
 
1.6%
양 17
 
1.5%
성 17
 
1.5%
Other values (127) 314
27.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1154
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
서 241
20.9%
소 224
19.4%
방 224
19.4%
부 35
 
3.0%
천 22
 
1.9%
산 21
 
1.8%
주 20
 
1.7%
동 19
 
1.6%
양 17
 
1.5%
성 17
 
1.5%
Other values (127) 314
27.2%

주소
Text

UNIQUE 

Distinct224
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T22:17:53.372512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length19.946429
Min length13

Characters and Unicode

Total characters4468
Distinct characters245
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique224 ?
Unique (%)100.0%

Sample

1st row서울특별시 강남구 테헤란로 629(삼성동)
2nd row서울특별시 강동구 성내로 39(성내동)
3rd row서울특별시 강북구 한천로 911(번동)
4th row서울특별시 강서구 양천로 550(등촌동)
5th row서울특별시 관악구 관악로 97(봉천동)
ValueCountFrequency (%)
경기도 35
 
3.5%
서울특별시 24
 
2.4%
경상남도 21
 
2.1%
경상북도 19
 
1.9%
강원도 18
 
1.8%
전라남도 17
 
1.7%
충청남도 16
 
1.6%
충청북도 12
 
1.2%
전라북도 12
 
1.2%
부산광역시 11
 
1.1%
Other values (724) 822
81.6%
2023-12-12T22:17:53.827938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
793
 
17.7%
로 213
 
4.8%
도 166
 
3.7%
시 163
 
3.6%
1 144
 
3.2%
구 104
 
2.3%
2 94
 
2.1%
동 93
 
2.1%
남 86
 
1.9%
경 84
 
1.9%
Other values (235) 2528
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2870
64.2%
Space Separator 793
 
17.7%
Decimal Number 678
 
15.2%
Open Punctuation 58
 
1.3%
Close Punctuation 58
 
1.3%
Dash Punctuation 11
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 213
 
7.4%
도 166
 
5.8%
시 163
 
5.7%
구 104
 
3.6%
동 93
 
3.2%
남 86
 
3.0%
경 84
 
2.9%
군 73
 
2.5%
읍 65
 
2.3%
산 62
 
2.2%
Other values (221) 1761
61.4%
Decimal Number
ValueCountFrequency (%)
1 144
21.2%
2 94
13.9%
4 64
9.4%
7 60
8.8%
3 59
8.7%
6 56
 
8.3%
0 56
 
8.3%
8 49
 
7.2%
5 48
 
7.1%
9 48
 
7.1%
Space Separator
ValueCountFrequency (%)
793
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2870
64.2%
Common 1598
35.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 213
 
7.4%
도 166
 
5.8%
시 163
 
5.7%
구 104
 
3.6%
동 93
 
3.2%
남 86
 
3.0%
경 84
 
2.9%
군 73
 
2.5%
읍 65
 
2.3%
산 62
 
2.2%
Other values (221) 1761
61.4%
Common
ValueCountFrequency (%)
793
49.6%
1 144
 
9.0%
2 94
 
5.9%
4 64
 
4.0%
7 60
 
3.8%
3 59
 
3.7%
( 58
 
3.6%
) 58
 
3.6%
6 56
 
3.5%
0 56
 
3.5%
Other values (4) 156
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2870
64.2%
ASCII 1598
35.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
793
49.6%
1 144
 
9.0%
2 94
 
5.9%
4 64
 
4.0%
7 60
 
3.8%
3 59
 
3.7%
( 58
 
3.6%
) 58
 
3.6%
6 56
 
3.5%
0 56
 
3.5%
Other values (4) 156
 
9.8%
Hangul
ValueCountFrequency (%)
로 213
 
7.4%
도 166
 
5.8%
시 163
 
5.7%
구 104
 
3.6%
동 93
 
3.2%
남 86
 
3.0%
경 84
 
2.9%
군 73
 
2.5%
읍 65
 
2.3%
산 62
 
2.2%
Other values (221) 1761
61.4%

전화번호
Text

Distinct223
Distinct (%)100.0%
Missing1
Missing (%)0.4%
Memory size1.9 KiB
2023-12-12T22:17:54.044312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.982063
Min length11

Characters and Unicode

Total characters2672
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique223 ?
Unique (%)100.0%

Sample

1st row02-6981-7575
2nd row02-470-0119
3rd row02-6946-0200
4th row02-3663-0119
5th row02-6981-8310
ValueCountFrequency (%)
02-6981-7575 1
 
0.4%
063-450-0251 1
 
0.4%
063-540-4251 1
 
0.4%
041-689-0212 1
 
0.4%
041-955-0212 1
 
0.4%
041-538-0212 1
 
0.4%
041-330-4212 1
 
0.4%
041-570-0212 1
 
0.4%
041-360-0212 1
 
0.4%
041-940-7212 1
 
0.4%
Other values (213) 213
95.5%
2023-12-12T22:17:54.399763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 495
18.5%
- 445
16.7%
1 381
14.3%
2 273
10.2%
3 248
9.3%
5 188
 
7.0%
4 157
 
5.9%
9 148
 
5.5%
6 138
 
5.2%
7 107
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2227
83.3%
Dash Punctuation 445
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 495
22.2%
1 381
17.1%
2 273
12.3%
3 248
11.1%
5 188
 
8.4%
4 157
 
7.0%
9 148
 
6.6%
6 138
 
6.2%
7 107
 
4.8%
8 92
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 445
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2672
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 495
18.5%
- 445
16.7%
1 381
14.3%
2 273
10.2%
3 248
9.3%
5 188
 
7.0%
4 157
 
5.9%
9 148
 
5.5%
6 138
 
5.2%
7 107
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2672
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 495
18.5%
- 445
16.7%
1 381
14.3%
2 273
10.2%
3 248
9.3%
5 188
 
7.0%
4 157
 
5.9%
9 148
 
5.5%
6 138
 
5.2%
7 107
 
4.0%

FAX
Text

Distinct210
Distinct (%)94.2%
Missing1
Missing (%)0.4%
Memory size1.9 KiB
2023-12-12T22:17:54.636174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.856502
Min length2

Characters and Unicode

Total characters2644
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique197 ?
Unique (%)88.3%

Sample

1st row02-556-2119
2nd row02-489-2119
3rd row02-6946-0202
4th row02-3662-0590
5th row02-877-4119
ValueCountFrequency (%)
043-773-0119 2
 
0.9%
043-740-7019 2
 
0.9%
043-251-0115 2
 
0.9%
043-767-4119 2
 
0.9%
043-641-7139 2
 
0.9%
043-830-0123 2
 
0.9%
043-539-8129 2
 
0.9%
043-880-0199 2
 
0.9%
043-249-9265 2
 
0.9%
043-841-3119 2
 
0.9%
Other values (200) 203
91.0%
2023-12-12T22:17:55.073625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 449
17.0%
- 440
16.6%
1 340
12.9%
9 241
9.1%
2 239
9.0%
3 193
7.3%
5 178
 
6.7%
4 162
 
6.1%
8 136
 
5.1%
6 134
 
5.1%
Other values (4) 132
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2200
83.2%
Dash Punctuation 440
 
16.6%
Space Separator 2
 
0.1%
Other Letter 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 449
20.4%
1 340
15.5%
9 241
11.0%
2 239
10.9%
3 193
8.8%
5 178
 
8.1%
4 162
 
7.4%
8 136
 
6.2%
6 134
 
6.1%
7 128
 
5.8%
Other Letter
ValueCountFrequency (%)
없 1
50.0%
음 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 440
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2642
99.9%
Hangul 2
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 449
17.0%
- 440
16.7%
1 340
12.9%
9 241
9.1%
2 239
9.0%
3 193
7.3%
5 178
 
6.7%
4 162
 
6.1%
8 136
 
5.1%
6 134
 
5.1%
Other values (2) 130
 
4.9%
Hangul
ValueCountFrequency (%)
없 1
50.0%
음 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2642
99.9%
Hangul 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 449
17.0%
- 440
16.7%
1 340
12.9%
9 241
9.1%
2 239
9.0%
3 193
7.3%
5 178
 
6.7%
4 162
 
6.1%
8 136
 
5.1%
6 134
 
5.1%
Other values (2) 130
 
4.9%
Hangul
ValueCountFrequency (%)
없 1
50.0%
음 1
50.0%

Interactions

2023-12-12T22:17:51.372761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:17:55.181681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번본부명
순번1.0000.986
본부명0.9861.000
2023-12-12T22:17:55.261824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번본부명
순번1.0000.896
본부명0.8961.000

Missing values

2023-12-12T22:17:51.478747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:17:51.595944image/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.
2023-12-12T22:17:51.701659image/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

순번본부명소방서주소전화번호FAX
01서울소방재난본부강남소방서서울특별시 강남구 테헤란로 629(삼성동)02-6981-757502-556-2119
12서울소방재난본부강동소방서서울특별시 강동구 성내로 39(성내동)02-470-011902-489-2119
23서울소방재난본부강북소방서서울특별시 강북구 한천로 911(번동)02-6946-020002-6946-0202
34서울소방재난본부강서소방서서울특별시 강서구 양천로 550(등촌동)02-3663-011902-3662-0590
45서울소방재난본부관악소방서서울특별시 관악구 관악로 97(봉천동)02-6981-831002-877-4119
56서울소방재난본부광진소방서서울특별시 광진구 광나루로 480(구의동)02-457-011902-454-0338
67서울소방재난본부구로소방서서울특별시 구로구 경인로 408(고척동)02-2618-011902-2619-0121
78서울소방재난본부노원소방서서울특별시 노원구 한글비석로 1길 8(하계동)02-6981-691002-979-6119
89서울소방재난본부도봉소방서서울특별시 도봉구 도봉로 666(방학동)02-6981-811902-3493-1119
910서울소방재난본부동대문소방서서울특별시 동대문구 장한로 34(장안동)02-6942-131002-2242-0119
순번본부명소방서주소전화번호FAX
214215창원소방본부창원소방서경상남도 창원시 의창구 상남로 165055-211-9212055-211-9219
215216경남소방본부통영소방서경상남도 통영시 광도면 죽림4로 49055-640-9212055-640-9219
216217경남소방본부하동소방서경상남도 하동군 금성면 금성로 15055-880-9212055-880-9219
217218경남소방본부함안소방서경상남도 함안군 가야읍 선왕길 59055-580-9212055-580-9219
218219경남소방본부함양소방서경상남도 함양군 함양읍 고운로 161-41055-960-9212055-960-9219
219220경남소방본부합천소방서경상남도 합천군 합천읍 인덕로 2453055-930-9212055-930-9219
220221제주소방본부서귀포소방서제주특별자치도 서귀포시 서호남로 20(법환동)064-730-7133730-7129
221222제주소방본부동부소방서제주특별자치도 서귀포시 성산읍 일주동로 4120번길 7064-780-9133780-9129
222223제주소방본부제주소방서제주특별자치도 제주시 중앙로 342(이도이동)064-729-0134729-0110
223224제주소방본부서부소방서제주특별자치도 제주시 한림읍 한림중앙로 150064-795-0134795-0129