Overview

Dataset statistics

Number of variables10
Number of observations73
Missing cells131
Missing cells (%)17.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 KiB
Average record size in memory86.8 B

Variable types

Numeric5
Categorical1
Text3
DateTime1

Dataset

Description전북특별자치도 소방서별 구급대 실적 (센터명, 지역대, 출동건수 등)제공우리기관에서는 더 이상 생성 불가 데이터입니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055614/fileData.do

Alerts

비고 has constant value ""Constant
연번 is highly overall correlated with 관서명High correlation
출동건수 is highly overall correlated with 이송건수 and 1 other fieldsHigh correlation
이송건수 is highly overall correlated with 출동건수 and 1 other fieldsHigh correlation
이송인원 is highly overall correlated with 출동건수 and 1 other fieldsHigh correlation
관서명 is highly overall correlated with 연번High correlation
지역대 has 48 (65.8%) missing valuesMissing
출동건수 has 1 (1.4%) missing valuesMissing
이송건수 has 1 (1.4%) missing valuesMissing
이송인원 has 1 (1.4%) missing valuesMissing
등록 has 4 (5.5%) missing valuesMissing
주행거리 has 4 (5.5%) missing valuesMissing
비고 has 72 (98.6%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 08:58:48.165626
Analysis finished2024-03-14 08:58:54.827644
Duration6.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct73
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37
Minimum1
Maximum73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size785.0 B
2024-03-14T17:58:54.955019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.6
Q119
median37
Q355
95-th percentile69.4
Maximum73
Range72
Interquartile range (IQR)36

Descriptive statistics

Standard deviation21.217131
Coefficient of variation (CV)0.57343598
Kurtosis-1.2
Mean37
Median Absolute Deviation (MAD)18
Skewness0
Sum2701
Variance450.16667
MonotonicityStrictly increasing
2024-03-14T17:58:55.296287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
56 1
 
1.4%
54 1
 
1.4%
53 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
Other values (63) 63
86.3%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
73 1
1.4%
72 1
1.4%
71 1
1.4%
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%

관서명
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)13.7%
Missing0
Missing (%)0.0%
Memory size712.0 B
전주덕진소방서
10 
무진장소방서
10 
전주완산소방서
군산소방서
익산소방서
Other values (5)
28 

Length

Max length7
Median length5
Mean length5.6575342
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전주덕진소방서 10
13.7%
무진장소방서 10
13.7%
전주완산소방서 9
12.3%
군산소방서 8
11.0%
익산소방서 8
11.0%
남원소방서 8
11.0%
정읍소방서 6
8.2%
고창소방서 5
6.8%
부안소방서 5
6.8%
김제소방서 4
 
5.5%

Length

2024-03-14T17:58:55.554404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:58:55.790576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전주덕진소방서 10
13.7%
무진장소방서 10
13.7%
전주완산소방서 9
12.3%
군산소방서 8
11.0%
익산소방서 8
11.0%
남원소방서 8
11.0%
정읍소방서 6
8.2%
고창소방서 5
6.8%
부안소방서 5
6.8%
김제소방서 4
 
5.5%
Distinct49
Distinct (%)67.1%
Missing0
Missing (%)0.0%
Memory size712.0 B
2024-03-14T17:58:56.700269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length9.0273973
Min length9

Characters and Unicode

Total characters659
Distinct characters76
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

Unique33 ?
Unique (%)45.2%

Sample

1st row금암119안전센터
2nd row팔복119안전센터
3rd row전미119안전센터
4th row삼례119안전센터
5th row봉동119안전센터
ValueCountFrequency (%)
효자119안전센터 4
 
5.5%
순창119안전센터 3
 
4.1%
진안119안전센터 3
 
4.1%
식정119안전센터 3
 
4.1%
고산119안전센터 3
 
4.1%
교동119안전센터 3
 
4.1%
부안119안전센터 3
 
4.1%
무장119안전센터 2
 
2.7%
함열119안전센터 2
 
2.7%
임실119안전센터 2
 
2.7%
Other values (39) 45
61.6%
2024-03-14T17:58:57.814911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 145
22.0%
79
12.0%
74
11.2%
73
11.1%
73
11.1%
9 72
10.9%
5
 
0.8%
5
 
0.8%
5
 
0.8%
5
 
0.8%
Other values (66) 123
18.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 440
66.8%
Decimal Number 219
33.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
79
18.0%
74
16.8%
73
16.6%
73
16.6%
5
 
1.1%
5
 
1.1%
5
 
1.1%
5
 
1.1%
5
 
1.1%
4
 
0.9%
Other values (62) 112
25.5%
Decimal Number
ValueCountFrequency (%)
1 145
66.2%
9 72
32.9%
2 1
 
0.5%
0 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 440
66.8%
Common 219
33.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
79
18.0%
74
16.8%
73
16.6%
73
16.6%
5
 
1.1%
5
 
1.1%
5
 
1.1%
5
 
1.1%
5
 
1.1%
4
 
0.9%
Other values (62) 112
25.5%
Common
ValueCountFrequency (%)
1 145
66.2%
9 72
32.9%
2 1
 
0.5%
0 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 440
66.8%
ASCII 219
33.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 145
66.2%
9 72
32.9%
2 1
 
0.5%
0 1
 
0.5%
Hangul
ValueCountFrequency (%)
79
18.0%
74
16.8%
73
16.6%
73
16.6%
5
 
1.1%
5
 
1.1%
5
 
1.1%
5
 
1.1%
5
 
1.1%
4
 
0.9%
Other values (62) 112
25.5%

지역대
Text

MISSING 

Distinct25
Distinct (%)100.0%
Missing48
Missing (%)65.8%
Memory size712.0 B
2024-03-14T17:58:58.534089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.04
Min length2

Characters and Unicode

Total characters51
Distinct characters39
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

Unique25 ?
Unique (%)100.0%

Sample

1st row소양
2nd row화산
3rd row운주
4th row선발
5th row후발
ValueCountFrequency (%)
소양 1
 
4.0%
쌍치 1
 
4.0%
구천동 1
 
4.0%
주천 1
 
4.0%
안천 1
 
4.0%
안성 1
 
4.0%
변산 1
 
4.0%
계화 1
 
4.0%
줄포 1
 
4.0%
해리 1
 
4.0%
Other values (15) 15
60.0%
2024-03-14T17:58:59.540887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
 
7.8%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
Other values (29) 29
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4
 
7.8%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
Other values (29) 29
56.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4
 
7.8%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
Other values (29) 29
56.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4
 
7.8%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
Other values (29) 29
56.9%

출동건수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct71
Distinct (%)98.6%
Missing1
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean1553.6389
Minimum44
Maximum7476
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size785.0 B
2024-03-14T17:58:59.772807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum44
5-th percentile337.1
Q1640
median1234.5
Q32322.75
95-th percentile3164.2
Maximum7476
Range7432
Interquartile range (IQR)1682.75

Descriptive statistics

Standard deviation1213.682
Coefficient of variation (CV)0.78118666
Kurtosis7.0095246
Mean1553.6389
Median Absolute Deviation (MAD)688
Skewness2.0058619
Sum111862
Variance1473024
MonotonicityNot monotonic
2024-03-14T17:59:00.211182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2470 2
 
2.7%
4836 1
 
1.4%
1100 1
 
1.4%
784 1
 
1.4%
1677 1
 
1.4%
1285 1
 
1.4%
1564 1
 
1.4%
2940 1
 
1.4%
610 1
 
1.4%
1073 1
 
1.4%
Other values (61) 61
83.6%
ValueCountFrequency (%)
44 1
1.4%
103 1
1.4%
293 1
1.4%
314 1
1.4%
356 1
1.4%
375 1
1.4%
403 1
1.4%
436 1
1.4%
490 1
1.4%
516 1
1.4%
ValueCountFrequency (%)
7476 1
1.4%
4836 1
1.4%
3504 1
1.4%
3250 1
1.4%
3094 1
1.4%
3008 1
1.4%
2940 1
1.4%
2885 1
1.4%
2813 1
1.4%
2774 1
1.4%

이송건수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct69
Distinct (%)95.8%
Missing1
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean1015.2778
Minimum31
Maximum4901
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size785.0 B
2024-03-14T17:59:00.633332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile193.65
Q1443.75
median757
Q31508.25
95-th percentile2141.7
Maximum4901
Range4870
Interquartile range (IQR)1064.5

Descriptive statistics

Standard deviation799.4436
Coefficient of variation (CV)0.78741366
Kurtosis6.8128106
Mean1015.2778
Median Absolute Deviation (MAD)417.5
Skewness1.968523
Sum73100
Variance639110.06
MonotonicityNot monotonic
2024-03-14T17:59:01.058419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1489 2
 
2.7%
740 2
 
2.7%
719 2
 
2.7%
3123 1
 
1.4%
386 1
 
1.4%
561 1
 
1.4%
1146 1
 
1.4%
775 1
 
1.4%
1088 1
 
1.4%
2085 1
 
1.4%
Other values (59) 59
80.8%
ValueCountFrequency (%)
31 1
1.4%
66 1
1.4%
174 1
1.4%
192 1
1.4%
195 1
1.4%
209 1
1.4%
228 1
1.4%
247 1
1.4%
296 1
1.4%
305 1
1.4%
ValueCountFrequency (%)
4901 1
1.4%
3123 1
1.4%
2244 1
1.4%
2211 1
1.4%
2085 1
1.4%
2018 1
1.4%
1956 1
1.4%
1934 1
1.4%
1764 1
1.4%
1757 1
1.4%

이송인원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct71
Distinct (%)98.6%
Missing1
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean1047.625
Minimum32
Maximum5020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size785.0 B
2024-03-14T17:59:01.401292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32
5-th percentile200.1
Q1459.5
median779.5
Q31550
95-th percentile2201.55
Maximum5020
Range4988
Interquartile range (IQR)1090.5

Descriptive statistics

Standard deviation818.10811
Coefficient of variation (CV)0.78091694
Kurtosis6.768637
Mean1047.625
Median Absolute Deviation (MAD)425.5
Skewness1.9549638
Sum75429
Variance669300.89
MonotonicityNot monotonic
2024-03-14T17:59:01.650382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
798 2
 
2.7%
3194 1
 
1.4%
1767 1
 
1.4%
1207 1
 
1.4%
1108 1
 
1.4%
2139 1
 
1.4%
404 1
 
1.4%
641 1
 
1.4%
728 1
 
1.4%
179 1
 
1.4%
Other values (61) 61
83.6%
ValueCountFrequency (%)
32 1
1.4%
68 1
1.4%
179 1
1.4%
199 1
1.4%
201 1
1.4%
212 1
1.4%
234 1
1.4%
259 1
1.4%
310 1
1.4%
318 1
1.4%
ValueCountFrequency (%)
5020 1
1.4%
3194 1
1.4%
2307 1
1.4%
2278 1
1.4%
2139 1
1.4%
2049 1
1.4%
2020 1
1.4%
1991 1
1.4%
1832 1
1.4%
1791 1
1.4%

등록
Date

MISSING 

Distinct27
Distinct (%)39.1%
Missing4
Missing (%)5.5%
Memory size712.0 B
Minimum2006-06-19 00:00:00
Maximum2013-07-24 00:00:00
2024-03-14T17:59:01.867898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:59:02.070262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

주행거리
Real number (ℝ)

MISSING 

Distinct69
Distinct (%)100.0%
Missing4
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean85443.072
Minimum8879
Maximum277000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size785.0 B
2024-03-14T17:59:02.580756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8879
5-th percentile11619.8
Q151319
median74142
Q3113492
95-th percentile187387
Maximum277000
Range268121
Interquartile range (IQR)62173

Descriptive statistics

Standard deviation54405.917
Coefficient of variation (CV)0.63675047
Kurtosis1.7296808
Mean85443.072
Median Absolute Deviation (MAD)27064
Skewness1.1442853
Sum5895572
Variance2.9600038 × 109
MonotonicityNot monotonic
2024-03-14T17:59:03.021504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
89700 1
 
1.4%
110427 1
 
1.4%
112560 1
 
1.4%
60186 1
 
1.4%
159588 1
 
1.4%
54223 1
 
1.4%
69300 1
 
1.4%
64134 1
 
1.4%
131107 1
 
1.4%
202059 1
 
1.4%
Other values (59) 59
80.8%
(Missing) 4
 
5.5%
ValueCountFrequency (%)
8879 1
1.4%
9412 1
1.4%
9700 1
1.4%
10693 1
1.4%
13010 1
1.4%
16317 1
1.4%
20410 1
1.4%
24531 1
1.4%
28640 1
1.4%
31557 1
1.4%
ValueCountFrequency (%)
277000 1
1.4%
227372 1
1.4%
213641 1
1.4%
202059 1
1.4%
165379 1
1.4%
164082 1
1.4%
159588 1
1.4%
159173 1
1.4%
147876 1
1.4%
135772 1
1.4%

비고
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing72
Missing (%)98.6%
Memory size712.0 B
2024-03-14T17:59:03.505040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters4
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

Unique1 ?
Unique (%)100.0%

Sample

1st row중환자용
ValueCountFrequency (%)
중환자용 1
100.0%
2024-03-14T17:59:04.340996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/