Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells2878
Missing cells (%)2.9%
Duplicate rows903
Duplicate rows (%)9.0%
Total size in memory878.9 KiB
Average record size in memory90.0 B

Variable types

Categorical7
Text1
Numeric1
Boolean1

Dataset

Description경기도의 구급활동 현황입니다. 출동소방서명, 신고시각, 접수경로, 현장거리, 환자연령 등의 정보를 제공합니다. ※ Sheet탭에서는 최신 1개년 데이터를 확인하실 수 있으며, 전체 데이터는 File탭에서 내려받을 수 있는 파일의 형태로 제공됩니다.
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=SE00GA6F273B8PIJ9N8412495661&infSeq=1

Alerts

집계년도 has constant value ""Constant
Dataset has 903 (9.0%) duplicate rowsDuplicates
외국인여부 is highly overall correlated with 국적명High correlation
국적명 is highly overall correlated with 외국인여부High correlation
시군명 is highly overall correlated with 출동소방서명High correlation
출동소방서명 is highly overall correlated with 시군명High correlation
외국인여부 is highly imbalanced (98.3%)Imbalance
국적명 is highly imbalanced (99.4%)Imbalance
환자연령대 has 2878 (28.8%) missing valuesMissing
환자연령대 has 325 (3.2%) zerosZeros

Reproduction

Analysis started2024-03-12 23:27:42.633969
Analysis finished2024-03-12 23:27:43.639104
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2011
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2011
2nd row2011
3rd row2011
4th row2011
5th row2011

Common Values

ValueCountFrequency (%)
2011 10000
100.0%

Length

2024-03-13T08:27:43.691770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:27:43.776794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2011 10000
100.0%

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수원시
876 
고양시
770 
성남시
748 
부천시
 
631
안산시
 
610
Other values (26)
6365 

Length

Max length4
Median length3
Mean length3.0962
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row화성시
2nd row광명시
3rd row안양시
4th row화성시
5th row양주시

Common Values

ValueCountFrequency (%)
수원시 876
 
8.8%
고양시 770
 
7.7%
성남시 748
 
7.5%
부천시 631
 
6.3%
안산시 610
 
6.1%
용인시 580
 
5.8%
안양시 465
 
4.7%
남양주시 459
 
4.6%
화성시 432
 
4.3%
파주시 389
 
3.9%
Other values (21) 4040
40.4%

Length

2024-03-13T08:27:43.854983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 876
 
8.8%
고양시 770
 
7.7%
성남시 748
 
7.5%
부천시 631
 
6.3%
안산시 610
 
6.1%
용인시 580
 
5.8%
안양시 465
 
4.7%
남양주시 459
 
4.6%
화성시 432
 
4.3%
파주시 389
 
3.9%
Other values (21) 4040
40.4%

출동소방서명
Categorical

HIGH CORRELATION 

Distinct34
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수원소방서
876 
부천소방서
 
631
안산소방서
 
610
용인소방서
 
580
안양소방서
 
465
Other values (29)
6838 

Length

Max length6
Median length5
Mean length5.0962
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row화성소방서
2nd row광명소방서
3rd row안양소방서
4th row화성소방서
5th row양주소방서

Common Values

ValueCountFrequency (%)
수원소방서 876
 
8.8%
부천소방서 631
 
6.3%
안산소방서 610
 
6.1%
용인소방서 580
 
5.8%
안양소방서 465
 
4.7%
남양주소방서 459
 
4.6%
성남소방서 453
 
4.5%
화성소방서 432
 
4.3%
일산소방서 420
 
4.2%
파주소방서 389
 
3.9%
Other values (24) 4685
46.9%

Length

2024-03-13T08:27:43.942790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원소방서 876
 
8.8%
부천소방서 631
 
6.3%
안산소방서 610
 
6.1%
용인소방서 580
 
5.8%
안양소방서 465
 
4.7%
남양주소방서 459
 
4.6%
성남소방서 453
 
4.5%
화성소방서 432
 
4.3%
일산소방서 420
 
4.2%
파주소방서 389
 
3.9%
Other values (24) 4685
46.9%

출동안전센터명
Text

Distinct168
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T08:27:44.119395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length9.0223
Min length5

Characters and Unicode

Total characters90223
Distinct characters145
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 row태안119안전센터
2nd row하안119안전센터
3rd row석수119안전센터
4th row동탄119안전센터
5th row양주119안전센터
ValueCountFrequency (%)
중앙119안전센터 228
 
2.3%
은행119안전센터 204
 
2.0%
신장119안전센터 202
 
2.0%
정자119안전센터 159
 
1.6%
둔야119안전센터 156
 
1.6%
소현119안전센터 142
 
1.4%
시흥119안전센터 133
 
1.3%
고잔119안전센터 129
 
1.3%
원당119안전센터 126
 
1.3%
정발산119안전센터 120
 
1.2%
Other values (158) 8401
84.0%
2024-03-13T08:27:44.439863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19856
22.0%
안 10383
11.5%
전 10028
11.1%
9 9928
11.0%
센 9925
11.0%
터 9925
11.0%
산 641
 
0.7%
신 613
 
0.7%
원 606
 
0.7%
수 564
 
0.6%
Other values (135) 17754
19.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60439
67.0%
Decimal Number 29784
33.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 10383
17.2%
전 10028
16.6%
센 9925
16.4%
터 9925
16.4%
산 641
 
1.1%
신 613
 
1.0%
원 606
 
1.0%
수 564
 
0.9%
동 477
 
0.8%
정 455
 
0.8%
Other values (133) 16822
27.8%
Decimal Number
ValueCountFrequency (%)
1 19856
66.7%
9 9928
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60439
67.0%
Common 29784
33.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 10383
17.2%
전 10028
16.6%
센 9925
16.4%
터 9925
16.4%
산 641
 
1.1%
신 613
 
1.0%
원 606
 
1.0%
수 564
 
0.9%
동 477
 
0.8%
정 455
 
0.8%
Other values (133) 16822
27.8%
Common
ValueCountFrequency (%)
1 19856
66.7%
9 9928
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60439
67.0%
ASCII 29784
33.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19856
66.7%
9 9928
33.3%
Hangul
ValueCountFrequency (%)
안 10383
17.2%
전 10028
16.6%
센 9925
16.4%
터 9925
16.4%
산 641
 
1.1%
신 613
 
1.0%
원 606
 
1.0%
수 564
 
0.9%
동 477
 
0.8%
정 455
 
0.8%
Other values (133) 16822
27.8%

환자연령대
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.2%
Missing2878
Missing (%)28.8%
Infinite0
Infinite (%)0.0%
Mean47.381354
Minimum0
Maximum100
Zeros325
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T08:27:44.534841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q130
median50
Q370
95-th percentile80
Maximum100
Range100
Interquartile range (IQR)40

Descriptive statistics

Standard deviation22.202368
Coefficient of variation (CV)0.46858872
Kurtosis-0.58903376
Mean47.381354
Median Absolute Deviation (MAD)20
Skewness-0.23675649
Sum337450
Variance492.94513
MonotonicityNot monotonic
2024-03-13T08:27:44.616933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
50 1369
13.7%
40 1119
 
11.2%
70 1006
 
10.1%
60 819
 
8.2%
30 813
 
8.1%
80 655
 
6.6%
20 566
 
5.7%
0 325
 
3.2%
10 300
 
3.0%
90 143
 
1.4%
(Missing) 2878
28.8%
ValueCountFrequency (%)
0 325
 
3.2%
10 300
 
3.0%
20 566
5.7%
30 813
8.1%
40 1119
11.2%
50 1369
13.7%
60 819
8.2%
70 1006
10.1%
80 655
6.6%
90 143
 
1.4%
ValueCountFrequency (%)
100 7
 
0.1%
90 143
 
1.4%
80 655
6.6%
70 1006
10.1%
60 819
8.2%
50 1369
13.7%
40 1119
11.2%
30 813
8.1%
20 566
5.7%
10 300
 
3.0%

환자성별구분명
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
남
3916 
여
3201 
<NA>
2876 
미상
 
7

Length

Max length4
Median length1
Mean length1.8635
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남 3916
39.2%
여 3201
32.0%
<NA> 2876
28.8%
미상 7
 
0.1%

Length

2024-03-13T08:27:44.712469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:27:44.805423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 3916
39.2%
여 3201
32.0%
na 2876
28.8%
미상 7
 
0.1%

외국인여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9984 
True
 
16
ValueCountFrequency (%)
False 9984
99.8%
True 16
 
0.2%
2024-03-13T08:27:44.890058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

국적명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9986 
중국
 
7
미국
 
3
인도네시아
 
1
베트남
 
1
Other values (2)
 
2

Length

Max length5
Median length4
Mean length3.9976
Min length2

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9986
99.9%
중국 7
 
0.1%
미국 3
 
< 0.1%
인도네시아 1
 
< 0.1%
베트남 1
 
< 0.1%
몽골 1
 
< 0.1%
일본 1
 
< 0.1%

Length

2024-03-13T08:27:44.976889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:27:45.081729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9986
99.9%
중국 7
 
0.1%
미국 3
 
< 0.1%
인도네시아 1
 
< 0.1%
베트남 1
 
< 0.1%
몽골 1
 
< 0.1%
일본 1
 
< 0.1%

구급발생장소유형
Categorical

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
가정
4407 
<NA>
2079 
일반도로
1107 
기타
1032 
공공장소
 
362
Other values (13)
1013 

Length

Max length4
Median length2
Mean length2.7901
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가정 4407
44.1%
<NA> 2079
20.8%
일반도로 1107
 
11.1%
기타 1032
 
10.3%
공공장소 362
 
3.6%
주택가 316
 
3.2%
병원 108
 
1.1%
공장 102
 
1.0%
고속도로 98
 
1.0%
숙박시설 71
 
0.7%
Other values (8) 318
 
3.2%

Length

2024-03-13T08:27:45.178844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가정 4407
44.1%
na 2079
20.8%
일반도로 1107
 
11.1%
기타 1032
 
10.3%
공공장소 362
 
3.6%
주택가 316
 
3.2%
병원 108
 
1.1%
공장 102
 
1.0%
고속도로 98
 
1.0%
숙박시설 71
 
0.7%
Other values (8) 318
 
3.2%

환자증상유형
Categorical

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
2876 
기타통증
2074 
기타
1099 
복통
719 
요통
509 
Other values (25)
2723 

Length

Max length5
Median length4
Mean length3.2896
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2876
28.8%
기타통증 2074
20.7%
기타 1099
 
11.0%
복통 719
 
7.2%
요통 509
 
5.1%
두통 435
 
4.3%
의식장애 402
 
4.0%
현기증 351
 
3.5%
호흡곤란 282
 
2.8%
흉통 210
 
2.1%
Other values (20) 1043
 
10.4%

Length

2024-03-13T08:27:45.275461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2876
28.8%
기타통증 2074
20.7%
기타 1099
 
11.0%
복통 719
 
7.2%
요통 509
 
5.1%
두통 435
 
4.3%
의식장애 402
 
4.0%
현기증 351
 
3.5%
호흡곤란 282
 
2.8%
흉통 210
 
2.1%
Other values (20) 1043
 
10.4%

Interactions

2024-03-13T08:27:43.362050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:27:45.355165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명출동소방서명환자연령대환자성별구분명외국인여부국적명구급발생장소유형환자증상유형
시군명1.0001.0000.1430.1010.0500.3600.2470.100
출동소방서명1.0001.0000.1480.1060.0500.3600.2960.107
환자연령대0.1430.1481.0000.1910.0340.7040.2990.428
환자성별구분명0.1010.1060.1911.0000.0000.0000.2270.194
외국인여부0.0500.0500.0340.0001.000NaN0.0320.000
국적명0.3600.3600.7040.000NaN1.0000.1900.547
구급발생장소유형0.2470.2960.2990.2270.0320.1901.0000.295
환자증상유형0.1000.1070.4280.1940.0000.5470.2951.000
2024-03-13T08:27:45.473470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
외국인여부환자성별구분명국적명구급발생장소유형시군명환자증상유형출동소방서명
외국인여부1.0000.0001.0000.0290.0430.0000.040
환자성별구분명0.0001.0000.0000.1250.0500.0990.052
국적명1.0000.0001.0000.0000.0000.1810.000
구급발생장소유형0.0290.1250.0001.0000.0710.0870.076
시군명0.0430.0500.0000.0711.0000.0231.000
환자증상유형0.0000.0990.1810.0870.0231.0000.024
출동소방서명0.0400.0520.0000.0761.0000.0241.000
2024-03-13T08:27:45.567759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
환자연령대시군명출동소방서명환자성별구분명외국인여부국적명구급발생장소유형환자증상유형
환자연령대1.0000.0490.0510.1160.0280.4010.1110.156
시군명0.0491.0001.0000.0500.0430.0000.0710.023
출동소방서명0.0511.0001.0000.0520.0400.0000.0760.024
환자성별구분명0.1160.0500.0521.0000.0000.0000.1250.099
외국인여부0.0280.0430.0400.0001.0001.0000.0290.000
국적명0.4010.0000.0000.0001.0001.0000.0000.181
구급발생장소유형0.1110.0710.0760.1250.0290.0001.0000.087
환자증상유형0.1560.0230.0240.0990.0000.1810.0871.000

Missing values

2024-03-13T08:27:43.453327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:27:43.581797image/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.

Sample

집계년도시군명출동소방서명출동안전센터명환자연령대환자성별구분명외국인여부국적명구급발생장소유형환자증상유형
328932011화성시화성소방서태안119안전센터50여N<NA>가정기타
115792011광명시광명소방서하안119안전센터0남N<NA>가정기타
667372011안양시안양소방서석수119안전센터<NA><NA>N<NA><NA><NA>
147212011화성시화성소방서동탄119안전센터40남N<NA>일반도로두통
999262011양주시양주소방서양주119안전센터0남N<NA>가정고열
444012011수원시수원소방서이의119안전센터0남N<NA>가정기타
157572011성남시분당소방서야탑119안전센터<NA><NA>N<NA><NA><NA>
44622011김포시김포소방서중앙119안전센터20여N<NA>일반도로기타통증
678312011부천시부천소방서중앙119안전센터50남N<NA>학교기타통증
898152011안산시안산소방서원시119안전센터<NA><NA>N<NA><NA><NA>
집계년도시군명출동소방서명출동안전센터명환자연령대환자성별구분명외국인여부국적명구급발생장소유형환자증상유형
148822011부천시부천소방서중동119안전센터30남N<NA>체육시설기타
580132011양주시양주소방서회천119안전센터<NA><NA>N<NA>주택가<NA>
241652011고양시일산소방서장항119안전센터<NA><NA>N<NA><NA><NA>
800572011안산시안산소방서고잔119안전센터<NA><NA>N<NA><NA><NA>
36272011구리시구리소방서교문119안전센터40여N<NA>가정요통
794462011양주시양주소방서백석119안전센터80여N<NA>가정기타
422372011용인시용인소방서백암119안전센터40남N<NA>일반도로기타통증
674342011고양시일산소방서정발산119안전센터<NA><NA>N<NA>주택가<NA>
740102011화성시화성소방서향남119안전센터<NA><NA>N<NA>일반도로<NA>
28432011안산시안산소방서성곡119안전센터60여N<NA>가정요통

Duplicate rows

Most frequently occurring

집계년도시군명출동소방서명출동안전센터명환자연령대환자성별구분명외국인여부국적명구급발생장소유형환자증상유형# duplicates
262011고양시고양소방서원당119안전센터<NA><NA>N<NA><NA><NA>44
6492011오산시송탄소방서신장119안전센터<NA><NA>N<NA><NA><NA>43
4692011안산시안산소방서고잔119안전센터<NA><NA>N<NA><NA><NA>41
7542011의정부시의정부소방서둔야119안전센터<NA><NA>N<NA><NA><NA>41
4882011안산시안산소방서상록수119안전센터<NA><NA>N<NA><NA><NA>39
5412011안성시안성소방서소현119안전센터<NA><NA>N<NA><NA><NA>36
372011고양시일산소방서백석119안전센터<NA><NA>N<NA><NA><NA>34
3322011성남시성남소방서수진119안전센터<NA><NA>N<NA><NA><NA>34
7682011의정부시의정부소방서파발119안전센터<NA><NA>N<NA><NA><NA>29
8202011평택시평택소방서신평119안전센터<NA><NA>N<NA><NA><NA>29