Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells2843
Missing cells (%)2.8%
Duplicate rows938
Duplicate rows (%)9.4%
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 938 (9.4%) 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 (92.9%)Imbalance
국적명 is highly imbalanced (98.1%)Imbalance
환자연령대 has 2843 (28.4%) missing valuesMissing
환자연령대 has 448 (4.5%) zerosZeros

Reproduction

Analysis started2024-03-12 23:27:22.363928
Analysis finished2024-03-12 23:27:23.437875
Duration1.07 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
2016
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2016
2nd row2016
3rd row2016
4th row2016
5th row2016

Common Values

ValueCountFrequency (%)
2016 10000
100.0%

Length

2024-03-13T08:27:23.485084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:27:23.553734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2016 10000
100.0%

시군명
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수원시
928 
성남시
795 
고양시
741 
용인시
644 
안산시
 
622
Other values (27)
6270 

Length

Max length4
Median length3
Mean length3.1045
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부천시
2nd row성남시
3rd row시흥시
4th row이천시
5th row구리시

Common Values

ValueCountFrequency (%)
수원시 928
 
9.3%
성남시 795
 
8.0%
고양시 741
 
7.4%
용인시 644
 
6.4%
안산시 622
 
6.2%
부천시 554
 
5.5%
남양주시 494
 
4.9%
의정부시 409
 
4.1%
화성시 401
 
4.0%
오산시 389
 
3.9%
Other values (22) 4023
40.2%

Length

2024-03-13T08:27:23.623090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 928
 
9.3%
성남시 795
 
8.0%
고양시 741
 
7.4%
용인시 644
 
6.4%
안산시 622
 
6.2%
부천시 554
 
5.5%
남양주시 494
 
4.9%
의정부시 409
 
4.1%
화성시 401
 
4.0%
오산시 389
 
3.9%
Other values (22) 4023
40.2%

출동소방서명
Categorical

HIGH CORRELATION 

Distinct44
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수원소방서
928 
용인소방서
 
641
안산소방서
 
569
부천소방서
 
554
남양주소방서
 
467
Other values (39)
6841 

Length

Max length9
Median length5
Mean length5.1545
Min length5

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row부천소방서
2nd row분당소방서
3rd row시흥소방서
4th row이천소방서
5th row구리소방서

Common Values

ValueCountFrequency (%)
수원소방서 928
 
9.3%
용인소방서 641
 
6.4%
안산소방서 569
 
5.7%
부천소방서 554
 
5.5%
남양주소방서 467
 
4.7%
의정부소방서 409
 
4.1%
일산소방서 403
 
4.0%
성남소방서 402
 
4.0%
화성소방서 401
 
4.0%
분당소방서 393
 
3.9%
Other values (34) 4833
48.3%

Length

2024-03-13T08:27:23.716803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원소방서 928
 
9.3%
용인소방서 641
 
6.4%
안산소방서 569
 
5.7%
부천소방서 554
 
5.5%
남양주소방서 467
 
4.7%
의정부소방서 409
 
4.1%
일산소방서 403
 
4.0%
성남소방서 402
 
4.0%
화성소방서 401
 
4.0%
분당소방서 393
 
3.9%
Other values (34) 4833
48.3%

출동안전센터명
Text

Distinct173
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T08:27:23.893949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.6055
Min length5

Characters and Unicode

Total characters86055
Distinct characters144
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

Unique3 ?
Unique (%)< 0.1%

Sample

1st row중앙119안전센터
2nd row판교119안전센터
3rd row은행119안전센터
4th row관고119안전센터
5th row교문119안전센터
ValueCountFrequency (%)
119구조대 902
 
9.0%
중앙119안전센터 411
 
4.1%
신장119안전센터 169
 
1.7%
정자119안전센터 155
 
1.6%
남부119안전센터 152
 
1.5%
구갈119안전센터 146
 
1.5%
상록수출동대 142
 
1.4%
매산119안전센터 141
 
1.4%
시흥119안전센터 133
 
1.3%
수지119안전센터 122
 
1.2%
Other values (163) 7527
75.3%
2024-03-13T08:27:24.181883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19300
22.4%
9 9650
11.2%
안 9059
10.5%
전 8713
10.1%
터 8594
10.0%
센 8594
10.0%
대 1623
 
1.9%
구 1360
 
1.6%
조 1017
 
1.2%
동 656
 
0.8%
Other values (134) 17489
20.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57105
66.4%
Decimal Number 28950
33.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 9059
15.9%
전 8713
15.3%
터 8594
15.0%
센 8594
15.0%
대 1623
 
2.8%
구 1360
 
2.4%
조 1017
 
1.8%
동 656
 
1.1%
중 634
 
1.1%
수 562
 
1.0%
Other values (132) 16293
28.5%
Decimal Number
ValueCountFrequency (%)
1 19300
66.7%
9 9650
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57105
66.4%
Common 28950
33.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 9059
15.9%
전 8713
15.3%
터 8594
15.0%
센 8594
15.0%
대 1623
 
2.8%
구 1360
 
2.4%
조 1017
 
1.8%
동 656
 
1.1%
중 634
 
1.1%
수 562
 
1.0%
Other values (132) 16293
28.5%
Common
ValueCountFrequency (%)
1 19300
66.7%
9 9650
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57105
66.4%
ASCII 28950
33.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19300
66.7%
9 9650
33.3%
Hangul
ValueCountFrequency (%)
안 9059
15.9%
전 8713
15.3%
터 8594
15.0%
센 8594
15.0%
대 1623
 
2.8%
구 1360
 
2.4%
조 1017
 
1.8%
동 656
 
1.1%
중 634
 
1.1%
수 562
 
1.0%
Other values (132) 16293
28.5%

환자연령대
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.2%
Missing2843
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean47.648456
Minimum0
Maximum100
Zeros448
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T08:27:24.286990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q130
median50
Q370
95-th percentile80
Maximum100
Range100
Interquartile range (IQR)40

Descriptive statistics

Standard deviation23.410103
Coefficient of variation (CV)0.49130874
Kurtosis-0.66886485
Mean47.648456
Median Absolute Deviation (MAD)20
Skewness-0.31665822
Sum341020
Variance548.03291
MonotonicityNot monotonic
2024-03-13T08:27:24.366843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
50 1288
12.9%
70 1027
 
10.3%
40 969
 
9.7%
60 907
 
9.1%
80 751
 
7.5%
30 725
 
7.2%
20 569
 
5.7%
0 448
 
4.5%
10 304
 
3.0%
90 160
 
1.6%
(Missing) 2843
28.4%
ValueCountFrequency (%)
0 448
 
4.5%
10 304
 
3.0%
20 569
5.7%
30 725
7.2%
40 969
9.7%
50 1288
12.9%
60 907
9.1%
70 1027
10.3%
80 751
7.5%
90 160
 
1.6%
ValueCountFrequency (%)
100 9
 
0.1%
90 160
 
1.6%
80 751
7.5%
70 1027
10.3%
60 907
9.1%
50 1288
12.9%
40 969
9.7%
30 725
7.2%
20 569
5.7%
10 304
 
3.0%

환자성별구분명
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
남
3948 
여
3291 
<NA>
2760 
미상
 
1

Length

Max length4
Median length1
Mean length1.8281
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
남 3948
39.5%
여 3291
32.9%
<NA> 2760
27.6%
미상 1
 
< 0.1%

Length

2024-03-13T08:27:24.458993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:27:24.556642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 3948
39.5%
여 3291
32.9%
na 2760
27.6%
미상 1
 
< 0.1%

외국인여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9914 
True
 
86
ValueCountFrequency (%)
False 9914
99.1%
True 86
 
0.9%
2024-03-13T08:27:24.637776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

국적명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9928 
중국
 
30
베트남
 
6
몽골
 
6
우즈베키스탄
 
4
Other values (19)
 
26

Length

Max length8
Median length4
Mean length3.9907
Min length2

Unique

Unique14 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9928
99.3%
중국 30
 
0.3%
베트남 6
 
0.1%
몽골 6
 
0.1%
우즈베키스탄 4
 
< 0.1%
미국 4
 
< 0.1%
러시아 2
 
< 0.1%
필리핀 2
 
< 0.1%
일본 2
 
< 0.1%
우즈벡 2
 
< 0.1%
Other values (14) 14
 
0.1%

Length

2024-03-13T08:27:24.723896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9928
99.3%
중국 30
 
0.3%
베트남 6
 
0.1%
몽골 6
 
0.1%
우즈베키스탄 4
 
< 0.1%
미국 4
 
< 0.1%
러시아 2
 
< 0.1%
필리핀 2
 
< 0.1%
일본 2
 
< 0.1%
우즈벡 2
 
< 0.1%
Other values (14) 14
 
0.1%

구급발생장소유형
Categorical

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
가정
4614 
<NA>
1574 
일반도로
1047 
기타
977 
주택가
525 
Other values (16)
1263 

Length

Max length4
Median length2
Mean length2.7444
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가정 4614
46.1%
<NA> 1574
 
15.7%
일반도로 1047
 
10.5%
기타 977
 
9.8%
주택가 525
 
5.2%
공공장소 503
 
5.0%
고속도로 148
 
1.5%
공장 106
 
1.1%
병원 80
 
0.8%
숙박시설 75
 
0.8%
Other values (11) 351
 
3.5%

Length

2024-03-13T08:27:24.822203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가정 4614
46.1%
na 1574
 
15.7%
일반도로 1047
 
10.5%
기타 977
 
9.8%
주택가 525
 
5.2%
공공장소 503
 
5.0%
고속도로 148
 
1.5%
공장 106
 
1.1%
병원 80
 
0.8%
숙박시설 75
 
0.8%
Other values (11) 351
 
3.5%

환자증상유형
Categorical

Distinct39
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
3131 
기타통증
1884 
기타
1172 
복통
686 
요통
449 
Other values (34)
2678 

Length

Max length6
Median length4
Mean length3.3519
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3131
31.3%
기타통증 1884
18.8%
기타 1172
 
11.7%
복통 686
 
6.9%
요통 449
 
4.5%
오심/구토 409
 
4.1%
고열 270
 
2.7%
열상 262
 
2.6%
두통 261
 
2.6%
전신쇠약 244
 
2.4%
Other values (29) 1232
 
12.3%

Length

2024-03-13T08:27:24.928653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3131
30.9%
기타통증 1884
18.6%
기타 1172
 
11.6%
복통 686
 
6.8%
요통 449
 
4.4%
오심/구토 409
 
4.0%
고열 270
 
2.7%
열상 262
 
2.6%
두통 261
 
2.6%
전신쇠약 244
 
2.4%
Other values (30) 1372
13.5%

Interactions

2024-03-13T08:27:23.171188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:27:24.998518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명출동소방서명환자연령대환자성별구분명외국인여부국적명구급발생장소유형환자증상유형
시군명1.0001.0000.1330.0000.0740.0000.2600.179
출동소방서명1.0001.0000.1410.0000.0650.4030.2800.239
환자연령대0.1330.1411.0000.1870.0880.0000.3330.452
환자성별구분명0.0000.0000.1871.0000.0000.2410.2150.183
외국인여부0.0740.0650.0880.0001.000NaN0.1090.056
국적명0.0000.4030.0000.241NaN1.0000.0000.000
구급발생장소유형0.2600.2800.3330.2150.1090.0001.0000.342
환자증상유형0.1790.2390.4520.1830.0560.0000.3421.000
2024-03-13T08:27:25.095443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
외국인여부환자성별구분명국적명구급발생장소유형시군명환자증상유형출동소방서명
외국인여부1.0000.0001.0000.0860.0590.0440.051
환자성별구분명0.0001.0000.1630.1150.0000.0910.000
국적명1.0000.1631.0000.0000.0000.0000.077
구급발생장소유형0.0860.1150.0001.0000.0700.0930.073
시군명0.0590.0000.0000.0701.0000.0390.999
환자증상유형0.0440.0910.0000.0930.0391.0000.049
출동소방서명0.0510.0000.0770.0730.9990.0491.000
2024-03-13T08:27:25.189890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
환자연령대시군명출동소방서명환자성별구분명외국인여부국적명구급발생장소유형환자증상유형
환자연령대1.0000.0450.0470.1120.0810.0000.1010.150
시군명0.0451.0000.9990.0000.0590.0000.0700.039
출동소방서명0.0470.9991.0000.0000.0510.0770.0730.049
환자성별구분명0.1120.0000.0001.0000.0000.1630.1150.091
외국인여부0.0810.0590.0510.0001.0001.0000.0860.044
국적명0.0000.0000.0770.1631.0001.0000.0000.000
구급발생장소유형0.1010.0700.0730.1150.0860.0001.0000.093
환자증상유형0.1500.0390.0490.0910.0440.0000.0931.000

Missing values

2024-03-13T08:27:23.266070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:27:23.379339image/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
271782016부천시부천소방서중앙119안전센터70남N<NA>가정전신쇠약
541122016성남시분당소방서판교119안전센터50남N<NA>일반도로기타통증
516222016시흥시시흥소방서은행119안전센터0여N<NA>가정고열
654082016이천시이천소방서관고119안전센터<NA><NA>N<NA><NA><NA>
698902016구리시구리소방서교문119안전센터70여N<NA>가정<NA>
310682016수원시수원소방서남부119안전센터50여N<NA>식당철과상
677662016남양주시남양주소방서진건119안전센터50여N<NA>가정요통
123652016광주시광주소방서초월119안전센터70남N<NA>가정복통
218272016광주시광주소방서오포119안전센터70남N<NA>가정오심/구토
264662016고양시일산소방서백석119안전센터<NA><NA>N<NA>공공장소<NA>
집계년도시군명출동소방서명출동안전센터명환자연령대환자성별구분명외국인여부국적명구급발생장소유형환자증상유형
357412016평택시평택소방서비전119안전센터70여N<NA>가정기타통증
53802016의정부시의정부소방서금오119안전센터80남N<NA>가정전신쇠약
351392016의정부시의정부소방서호원119안전센터40남N<NA>공공장소그 밖의출혈
401212016파주시파주소방서월롱119안전센터40여N<NA>가정기타통증
76222016수원시수원소방서영통119안전센터<NA><NA>N<NA>가정<NA>
332972016부천시부천소방서중앙119안전센터70여N<NA>일반도로기타통증
911742016시흥시시흥소방서은행119안전센터<NA><NA>N<NA>사무실<NA>
24002016고양시고양소방서119구조대<NA>남N<NA>주택가철과상
48332016고양시일산소방서119구조대20남N<NA>일반도로기타통증
827642016오산시송탄소방서진위119안전센터50여N<NA>가정오심/구토

Duplicate rows

Most frequently occurring

집계년도시군명출동소방서명출동안전센터명환자연령대환자성별구분명외국인여부국적명구급발생장소유형환자증상유형# duplicates
2782016부천시부천소방서중앙119안전센터<NA><NA>N<NA><NA><NA>35
7072016용인시용인소방서구갈119안전센터<NA><NA>N<NA><NA><NA>29
3832016수원시수원소방서매산119안전센터<NA><NA>N<NA><NA><NA>27
3692016수원시수원소방서남부119안전센터<NA><NA>N<NA><NA><NA>25
4642016시흥시시흥소방서시흥119안전센터<NA><NA>N<NA><NA><NA>23
8652016평택시평택소방서119구조대<NA><NA>N<NA><NA><NA>23
1042016광명시광명소방서소하119안전센터<NA><NA>N<NA><NA><NA>21
1722016김포시김포소방서중앙119안전센터<NA><NA>N<NA><NA><NA>21
3892016수원시수원소방서서둔119안전센터<NA><NA>N<NA><NA><NA>21
692016고양시일산소방서주엽119안전센터<NA><NA>N<NA><NA><NA>19