Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells2744
Missing cells (%)2.7%
Duplicate rows858
Duplicate rows (%)8.6%
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 858 (8.6%) 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 (94.7%)Imbalance
국적명 is highly imbalanced (98.6%)Imbalance
환자연령대 has 2744 (27.4%) missing valuesMissing
환자연령대 has 368 (3.7%) zerosZeros

Reproduction

Analysis started2024-03-12 23:27:34.486692
Analysis finished2024-03-12 23:27:35.509102
Duration1.02 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
2013
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2013
2nd row2013
3rd row2013
4th row2013
5th row2013

Common Values

ValueCountFrequency (%)
2013 10000
100.0%

Length

2024-03-13T08:27:35.554656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:27:35.621058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2013 10000
100.0%

시군명
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수원시
869 
성남시
756 
고양시
745 
안산시
 
622
부천시
 
615
Other values (27)
6393 

Length

Max length4
Median length3
Mean length3.1015
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row의정부시
2nd row오산시
3rd row안양시
4th row구리시
5th row김포시

Common Values

ValueCountFrequency (%)
수원시 869
 
8.7%
성남시 756
 
7.6%
고양시 745
 
7.4%
안산시 622
 
6.2%
부천시 615
 
6.2%
용인시 517
 
5.2%
남양주시 490
 
4.9%
안양시 426
 
4.3%
파주시 389
 
3.9%
의정부시 387
 
3.9%
Other values (22) 4184
41.8%

Length

2024-03-13T08:27:35.690605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 869
 
8.7%
성남시 756
 
7.6%
고양시 745
 
7.4%
안산시 622
 
6.2%
부천시 615
 
6.2%
용인시 517
 
5.2%
남양주시 490
 
4.9%
안양시 426
 
4.3%
파주시 389
 
3.9%
의정부시 387
 
3.9%
Other values (22) 4184
41.8%

출동소방서명
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수원소방서
869 
안산소방서
 
622
부천소방서
 
615
용인소방서
 
517
남양주소방서
 
490
Other values (30)
6887 

Length

Max length8
Median length5
Mean length5.1033
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row의정부소방서
2nd row오산소방서
3rd row안양소방서
4th row구리소방서
5th row김포소방서

Common Values

ValueCountFrequency (%)
수원소방서 869
 
8.7%
안산소방서 622
 
6.2%
부천소방서 615
 
6.2%
용인소방서 517
 
5.2%
남양주소방서 490
 
4.9%
성남소방서 450
 
4.5%
안양소방서 426
 
4.3%
일산소방서 425
 
4.2%
파주소방서 389
 
3.9%
의정부소방서 387
 
3.9%
Other values (25) 4810
48.1%

Length

2024-03-13T08:27:35.782863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원소방서 869
 
8.7%
안산소방서 622
 
6.2%
부천소방서 615
 
6.2%
용인소방서 517
 
5.2%
남양주소방서 490
 
4.9%
성남소방서 450
 
4.5%
안양소방서 426
 
4.3%
일산소방서 425
 
4.2%
파주소방서 389
 
3.9%
의정부소방서 387
 
3.9%
Other values (25) 4810
48.1%

출동안전센터명
Text

Distinct151
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T08:27:35.966460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.4192
Min length5

Characters and Unicode

Total characters84192
Distinct characters137
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 row119구조대
2nd row119구조대
3rd row귀인119안전센터
4th row교문119안전센터
5th row중앙119안전센터
ValueCountFrequency (%)
119구조대 1875
 
18.8%
중앙119안전센터 217
 
2.2%
사동119안전센터 208
 
2.1%
남부119안전센터 157
 
1.6%
정자119안전센터 156
 
1.6%
신장119안전센터 137
 
1.4%
구갈119안전센터 127
 
1.3%
안양119안전센터 126
 
1.3%
수지119안전센터 113
 
1.1%
매산119안전센터 112
 
1.1%
Other values (141) 6772
67.7%
2024-03-13T08:27:36.269406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19776
23.5%
9 9888
11.7%
안 8482
10.1%
전 8135
9.7%
센 8013
9.5%
터 8013
9.5%
구 2224
 
2.6%
대 2215
 
2.6%
조 1957
 
2.3%
동 614
 
0.7%
Other values (127) 14875
17.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54528
64.8%
Decimal Number 29664
35.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 8482
15.6%
전 8135
14.9%
센 8013
14.7%
터 8013
14.7%
구 2224
 
4.1%
대 2215
 
4.1%
조 1957
 
3.6%
동 614
 
1.1%
원 483
 
0.9%
중 464
 
0.9%
Other values (125) 13928
25.5%
Decimal Number
ValueCountFrequency (%)
1 19776
66.7%
9 9888
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54528
64.8%
Common 29664
35.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 8482
15.6%
전 8135
14.9%
센 8013
14.7%
터 8013
14.7%
구 2224
 
4.1%
대 2215
 
4.1%
조 1957
 
3.6%
동 614
 
1.1%
원 483
 
0.9%
중 464
 
0.9%
Other values (125) 13928
25.5%
Common
ValueCountFrequency (%)
1 19776
66.7%
9 9888
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54528
64.8%
ASCII 29664
35.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19776
66.7%
9 9888
33.3%
Hangul
ValueCountFrequency (%)
안 8482
15.6%
전 8135
14.9%
센 8013
14.7%
터 8013
14.7%
구 2224
 
4.1%
대 2215
 
4.1%
조 1957
 
3.6%
동 614
 
1.1%
원 483
 
0.9%
중 464
 
0.9%
Other values (125) 13928
25.5%

환자연령대
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.2%
Missing2744
Missing (%)27.4%
Infinite0
Infinite (%)0.0%
Mean47.858324
Minimum0
Maximum100
Zeros368
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T08:27:36.371208image/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 deviation22.699664
Coefficient of variation (CV)0.47430963
Kurtosis-0.62823015
Mean47.858324
Median Absolute Deviation (MAD)20
Skewness-0.28778064
Sum347260
Variance515.27476
MonotonicityNot monotonic
2024-03-13T08:27:36.465015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
50 1335
13.4%
40 1090
 
10.9%
70 1033
 
10.3%
60 882
 
8.8%
30 758
 
7.6%
80 754
 
7.5%
20 574
 
5.7%
0 368
 
3.7%
10 306
 
3.1%
90 152
 
1.5%
(Missing) 2744
27.4%
ValueCountFrequency (%)
0 368
 
3.7%
10 306
 
3.1%
20 574
5.7%
30 758
7.6%
40 1090
10.9%
50 1335
13.4%
60 882
8.8%
70 1033
10.3%
80 754
7.5%
90 152
 
1.5%
ValueCountFrequency (%)
100 4
 
< 0.1%
90 152
 
1.5%
80 754
7.5%
70 1033
10.3%
60 882
8.8%
50 1335
13.4%
40 1090
10.9%
30 758
7.6%
20 574
5.7%
10 306
 
3.1%

환자성별구분명
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
남
3959 
여
3320 
<NA>
2717 
미상
 
4

Length

Max length4
Median length1
Mean length1.8155
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남 3959
39.6%
여 3320
33.2%
<NA> 2717
27.2%
미상 4
 
< 0.1%

Length

2024-03-13T08:27:36.559149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:27:36.638916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 3959
39.6%
여 3320
33.2%
na 2717
27.2%
미상 4
 
< 0.1%

외국인여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9940 
True
 
60
ValueCountFrequency (%)
False 9940
99.4%
True 60
 
0.6%
2024-03-13T08:27:36.703499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

국적명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9950 
중국
 
23
미국
 
3
베트남
 
2
스리랑카
 
2
Other values (18)
 
20

Length

Max length8
Median length4
Mean length3.9943
Min length2

Unique

Unique16 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9950
99.5%
중국 23
 
0.2%
미국 3
 
< 0.1%
베트남 2
 
< 0.1%
스리랑카 2
 
< 0.1%
캄보디아 2
 
< 0.1%
태국 2
 
< 0.1%
캐나다 1
 
< 0.1%
일본 1
 
< 0.1%
필리핀 1
 
< 0.1%
Other values (13) 13
 
0.1%

Length

2024-03-13T08:27:36.782940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9950
99.5%
중국 23
 
0.2%
미국 3
 
< 0.1%
베트남 2
 
< 0.1%
스리랑카 2
 
< 0.1%
캄보디아 2
 
< 0.1%
태국 2
 
< 0.1%
나이지리아 1
 
< 0.1%
우즈베키스탄 1
 
< 0.1%
몽골 1
 
< 0.1%
Other values (13) 13
 
0.1%

구급발생장소유형
Categorical

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
가정
4516 
<NA>
1838 
일반도로
1043 
기타
919 
주택가
478 
Other values (15)
1206 

Length

Max length4
Median length2
Mean length2.7683
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row가정
2nd row일반도로
3rd row주택가
4th row일반도로
5th row가정

Common Values

ValueCountFrequency (%)
가정 4516
45.2%
<NA> 1838
18.4%
일반도로 1043
 
10.4%
기타 919
 
9.2%
주택가 478
 
4.8%
공공장소 394
 
3.9%
고속도로 124
 
1.2%
공장 123
 
1.2%
병원 99
 
1.0%
숙박시설 87
 
0.9%
Other values (10) 379
 
3.8%

Length

2024-03-13T08:27:36.889766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가정 4516
45.2%
na 1838
18.4%
일반도로 1043
 
10.4%
기타 919
 
9.2%
주택가 478
 
4.8%
공공장소 394
 
3.9%
고속도로 124
 
1.2%
공장 123
 
1.2%
병원 99
 
1.0%
숙박시설 87
 
0.9%
Other values (10) 379
 
3.8%

환자증상유형
Categorical

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
2855 
기타통증
2192 
기타
923 
복통
708 
요통
469 
Other values (27)
2853 

Length

Max length6
Median length4
Mean length3.4287
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2855
28.5%
기타통증 2192
21.9%
기타 923
 
9.2%
복통 708
 
7.1%
요통 469
 
4.7%
두통 416
 
4.2%
현기증 316
 
3.2%
그 밖의출혈 312
 
3.1%
전신쇠약 279
 
2.8%
의식장애 237
 
2.4%
Other values (22) 1293
12.9%

Length

2024-03-13T08:27:36.993588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2855
27.7%
기타통증 2192
21.3%
기타 923
 
9.0%
복통 708
 
6.9%
요통 469
 
4.5%
두통 416
 
4.0%
현기증 316
 
3.1%
그 312
 
3.0%
밖의출혈 312
 
3.0%
전신쇠약 279
 
2.7%
Other values (23) 1530
14.8%

Interactions

2024-03-13T08:27:35.231995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:27:37.072020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명출동소방서명환자연령대환자성별구분명외국인여부국적명구급발생장소유형환자증상유형
시군명1.0001.0000.1020.0100.0520.7820.3250.149
출동소방서명1.0001.0000.1120.0000.0510.7970.3360.165
환자연령대0.1020.1121.0000.1720.1070.0000.3450.443
환자성별구분명0.0100.0000.1721.0000.0000.0000.2210.166
외국인여부0.0520.0510.1070.0001.000NaN0.1190.000
국적명0.7820.7970.0000.000NaN1.0000.0000.667
구급발생장소유형0.3250.3360.3450.2210.1190.0001.0000.330
환자증상유형0.1490.1650.4430.1660.0000.6670.3301.000
2024-03-13T08:27:37.182582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
외국인여부환자성별구분명국적명구급발생장소유형시군명환자증상유형출동소방서명
외국인여부1.0000.0001.0000.1060.0410.0000.043
환자성별구분명0.0001.0000.0000.1190.0050.0830.000
국적명1.0000.0001.0000.0000.3140.2480.327
구급발생장소유형0.1060.1190.0001.0000.0920.0940.094
시군명0.0410.0050.3140.0921.0000.0341.000
환자증상유형0.0000.0830.2480.0940.0341.0000.037
출동소방서명0.0430.0000.3270.0941.0000.0371.000
2024-03-13T08:27:37.272409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
환자연령대시군명출동소방서명환자성별구분명외국인여부국적명구급발생장소유형환자증상유형
환자연령대1.0000.0350.0370.1040.0850.0000.1180.153
시군명0.0351.0001.0000.0050.0410.3140.0920.034
출동소방서명0.0371.0001.0000.0000.0430.3270.0940.037
환자성별구분명0.1040.0050.0001.0000.0000.0000.1190.083
외국인여부0.0850.0410.0430.0001.0001.0000.1060.000
국적명0.0000.3140.3270.0001.0001.0000.0000.248
구급발생장소유형0.1180.0920.0940.1190.1060.0001.0000.094
환자증상유형0.1530.0340.0370.0830.0000.2480.0941.000

Missing values

2024-03-13T08:27:35.336720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:27:35.452508image/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
859532013의정부시의정부소방서119구조대50남N<NA>가정전신쇠약
713532013오산시오산소방서119구조대10남N<NA>일반도로요통
543902013안양시안양소방서귀인119안전센터<NA><NA>N<NA>주택가<NA>
777392013구리시구리소방서교문119안전센터20남N<NA>일반도로기타통증
483312013김포시김포소방서중앙119안전센터70여N<NA>가정흉통
486762013수원시수원소방서지만119안전센터70남N<NA>가정요통
771372013양주시양주소방서회천119안전센터<NA><NA>N<NA><NA><NA>
689832013성남시성남소방서119구조대<NA>여N<NA>기타기타통증
257372013안양시안양소방서석수119안전센터70남N<NA>가정기타통증
31722013수원시수원소방서고색119안전센터<NA><NA>N<NA><NA><NA>
집계년도시군명출동소방서명출동안전센터명환자연령대환자성별구분명외국인여부국적명구급발생장소유형환자증상유형
562012013화성시화성소방서119구조대60남N<NA>가정기타통증
63752013용인시용인소방서구갈119안전센터0여N<NA>고속도로두통
187912013포천시포천소방서일동119안전센터80여N<NA>가정마비
143162013부천시부천소방서괴안119안전센터80여N<NA>일반도로호흡곤란
944372013연천군연천소방서연천119안전센터80여N<NA>가정호흡곤란
781862013평택시평택소방서119구조대<NA><NA>N<NA><NA><NA>
918062013남양주시남양주소방서진접119안전센터0남N<NA>가정고열
576082013김포시김포소방서중앙119안전센터80여N<NA>병원현기증
570472013과천시과천소방서과천119안전센터10남N<NA>가정기타통증
300552013안양시안양소방서부림119안전센터<NA><NA>N<NA>가정<NA>

Duplicate rows

Most frequently occurring

집계년도시군명출동소방서명출동안전센터명환자연령대환자성별구분명외국인여부국적명구급발생장소유형환자증상유형# duplicates
4862013안산시안산소방서사동119안전센터<NA><NA>N<NA><NA><NA>51
4612013안산시안산소방서119구조대<NA><NA>N<NA><NA><NA>34
122013고양시고양소방서119구조대<NA><NA>N<NA><NA><NA>31
502013고양시일산소방서주엽119안전센터<NA><NA>N<NA><NA><NA>30
7752013파주시파주소방서금촌119안전센터<NA><NA>N<NA><NA><NA>30
2692013부천시부천소방서중앙119안전센터<NA><NA>N<NA><NA><NA>29
5772013안양시안양소방서안양119안전센터<NA><NA>N<NA><NA><NA>29
3692013수원시수원소방서매산119안전센터<NA><NA>N<NA><NA><NA>28
6572013용인시용인소방서구갈119안전센터<NA><NA>N<NA><NA><NA>28
5172013안성시안성소방서119구조대<NA><NA>N<NA><NA><NA>26