Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells3046
Missing cells (%)3.0%
Duplicate rows936
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 936 (9.4%) duplicate rowsDuplicates
외국인여부 is highly overall correlated with 국적명High correlation
국적명 is highly overall correlated with 외국인여부 and 1 other fieldsHigh correlation
시군명 is highly overall correlated with 출동소방서명High correlation
출동소방서명 is highly overall correlated with 시군명High correlation
환자증상유형 is highly overall correlated with 국적명High correlation
외국인여부 is highly imbalanced (97.0%)Imbalance
국적명 is highly imbalanced (98.9%)Imbalance
환자연령 has 3046 (30.5%) missing valuesMissing
환자연령 has 391 (3.9%) zerosZeros

Reproduction

Analysis started2024-03-12 23:27:38.700503
Analysis finished2024-03-12 23:27:39.697315
Duration1 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
2012
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2012
2nd row2012
3rd row2012
4th row2012
5th row2012

Common Values

ValueCountFrequency (%)
2012 10000
100.0%

Length

2024-03-13T08:27:39.756806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:27:39.827751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2012 10000
100.0%

시군명
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수원시
812 
성남시
741 
고양시
713 
안산시
681 
용인시
 
610
Other values (27)
6443 

Length

Max length4
Median length3
Mean length3.1024
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row안산시
2nd row수원시
3rd row광주시
4th row수원시
5th row남양주시

Common Values

ValueCountFrequency (%)
수원시 812
 
8.1%
성남시 741
 
7.4%
고양시 713
 
7.1%
안산시 681
 
6.8%
용인시 610
 
6.1%
부천시 605
 
6.0%
남양주시 505
 
5.1%
안양시 435
 
4.3%
화성시 417
 
4.2%
의정부시 374
 
3.7%
Other values (22) 4107
41.1%

Length

2024-03-13T08:27:39.897542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 812
 
8.1%
성남시 741
 
7.4%
고양시 713
 
7.1%
안산시 681
 
6.8%
용인시 610
 
6.1%
부천시 605
 
6.0%
남양주시 505
 
5.1%
안양시 435
 
4.3%
화성시 417
 
4.2%
의정부시 374
 
3.7%
Other values (22) 4107
41.1%

출동소방서명
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수원소방서
812 
안산소방서
681 
용인소방서
 
610
부천소방서
 
605
남양주소방서
 
505
Other values (30)
6787 

Length

Max length8
Median length5
Mean length5.1048
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row안산소방서
2nd row수원소방서
3rd row광주소방서
4th row수원소방서
5th row남양주소방서

Common Values

ValueCountFrequency (%)
수원소방서 812
 
8.1%
안산소방서 681
 
6.8%
용인소방서 610
 
6.1%
부천소방서 605
 
6.0%
남양주소방서 505
 
5.1%
안양소방서 435
 
4.3%
성남소방서 424
 
4.2%
화성소방서 417
 
4.2%
일산소방서 397
 
4.0%
의정부소방서 374
 
3.7%
Other values (25) 4740
47.4%

Length

2024-03-13T08:27:39.984229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원소방서 812
 
8.1%
안산소방서 681
 
6.8%
용인소방서 610
 
6.1%
부천소방서 605
 
6.0%
남양주소방서 505
 
5.1%
안양소방서 435
 
4.3%
성남소방서 424
 
4.2%
화성소방서 417
 
4.2%
일산소방서 397
 
4.0%
의정부소방서 374
 
3.7%
Other values (25) 4740
47.4%

출동안전센터명
Text

Distinct161
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T08:27:40.166983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.8196
Min length5

Characters and Unicode

Total characters88196
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 row고잔119안전센터
2nd row지만119안전센터
3rd row경안119안전센터
4th row원천119안전센터
5th row별내119안전센터
ValueCountFrequency (%)
119구조대 531
 
5.3%
사동119안전센터 219
 
2.2%
중앙119안전센터 216
 
2.2%
신장119안전센터 164
 
1.6%
은행119안전센터 163
 
1.6%
남부119안전센터 162
 
1.6%
정자119안전센터 157
 
1.6%
고잔119안전센터 140
 
1.4%
평내119안전센터 135
 
1.4%
둔야119안전센터 133
 
1.3%
Other values (151) 7980
79.8%
2024-03-13T08:27:40.441900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19790
22.4%
9 9895
11.2%
안 9848
11.2%
전 9553
10.8%
센 9364
10.6%
터 9364
10.6%
대 784
 
0.9%
구 769
 
0.9%
원 598
 
0.7%
동 596
 
0.7%
Other values (135) 17635
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58511
66.3%
Decimal Number 29685
33.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 9848
16.8%
전 9553
16.3%
센 9364
16.0%
터 9364
16.0%
대 784
 
1.3%
구 769
 
1.3%
원 598
 
1.0%
동 596
 
1.0%
조 559
 
1.0%
부 497
 
0.8%
Other values (133) 16579
28.3%
Decimal Number
ValueCountFrequency (%)
1 19790
66.7%
9 9895
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58511
66.3%
Common 29685
33.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 9848
16.8%
전 9553
16.3%
센 9364
16.0%
터 9364
16.0%
대 784
 
1.3%
구 769
 
1.3%
원 598
 
1.0%
동 596
 
1.0%
조 559
 
1.0%
부 497
 
0.8%
Other values (133) 16579
28.3%
Common
ValueCountFrequency (%)
1 19790
66.7%
9 9895
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58511
66.3%
ASCII 29685
33.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19790
66.7%
9 9895
33.3%
Hangul
ValueCountFrequency (%)
안 9848
16.8%
전 9553
16.3%
센 9364
16.0%
터 9364
16.0%
대 784
 
1.3%
구 769
 
1.3%
원 598
 
1.0%
동 596
 
1.0%
조 559
 
1.0%
부 497
 
0.8%
Other values (133) 16579
28.3%

환자연령
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.2%
Missing3046
Missing (%)30.5%
Infinite0
Infinite (%)0.0%
Mean47.425942
Minimum0
Maximum100
Zeros391
Zeros (%)3.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T08:27:40.555444image/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 deviation23.29571
Coefficient of variation (CV)0.49120185
Kurtosis-0.70856351
Mean47.425942
Median Absolute Deviation (MAD)20
Skewness-0.25564292
Sum329800
Variance542.69011
MonotonicityNot monotonic
2024-03-13T08:27:40.639543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
50 1207
 
12.1%
40 1019
 
10.2%
70 1006
 
10.1%
60 793
 
7.9%
30 750
 
7.5%
80 720
 
7.2%
20 577
 
5.8%
0 391
 
3.9%
10 315
 
3.1%
90 170
 
1.7%
(Missing) 3046
30.5%
ValueCountFrequency (%)
0 391
 
3.9%
10 315
 
3.1%
20 577
5.8%
30 750
7.5%
40 1019
10.2%
50 1207
12.1%
60 793
7.9%
70 1006
10.1%
80 720
7.2%
90 170
 
1.7%
ValueCountFrequency (%)
100 6
 
0.1%
90 170
 
1.7%
80 720
7.2%
70 1006
10.1%
60 793
7.9%
50 1207
12.1%
40 1019
10.2%
30 750
7.5%
20 577
5.8%
10 315
 
3.1%

환자성별구분명
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
남
3812 
여
3138 
<NA>
3045 
미상
 
5

Length

Max length4
Median length1
Mean length1.914
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남 3812
38.1%
여 3138
31.4%
<NA> 3045
30.4%
미상 5
 
0.1%

Length

2024-03-13T08:27:40.733120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:27:40.816132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 3812
38.1%
여 3138
31.4%
na 3045
30.4%
미상 5
 
< 0.1%

외국인여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9969 
True
 
31
ValueCountFrequency (%)
False 9969
99.7%
True 31
 
0.3%
2024-03-13T08:27:40.881578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

국적명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9971 
중국
 
12
베트남
 
4
몽골
 
3
일본
 
2
Other values (6)
 
8

Length

Max length6
Median length4
Mean length3.9956
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> 9971
99.7%
중국 12
 
0.1%
베트남 4
 
< 0.1%
몽골 3
 
< 0.1%
일본 2
 
< 0.1%
네팔 2
 
< 0.1%
태국 2
 
< 0.1%
인도네시아 1
 
< 0.1%
우즈벡 1
 
< 0.1%
파키스탄 1
 
< 0.1%

Length

2024-03-13T08:27:40.961780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9971
99.7%
중국 12
 
0.1%
베트남 4
 
< 0.1%
몽골 3
 
< 0.1%
일본 2
 
< 0.1%
네팔 2
 
< 0.1%
태국 2
 
< 0.1%
인도네시아 1
 
< 0.1%
우즈벡 1
 
< 0.1%
파키스탄 1
 
< 0.1%

구급발생장소유형
Categorical

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
가정
4317 
<NA>
2268 
일반도로
1077 
기타
974 
공공장소
 
353
Other values (14)
1011 

Length

Max length4
Median length2
Mean length2.8272
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
가정 4317
43.2%
<NA> 2268
22.7%
일반도로 1077
 
10.8%
기타 974
 
9.7%
공공장소 353
 
3.5%
주택가 317
 
3.2%
고속도로 135
 
1.4%
병원 98
 
1.0%
공장 91
 
0.9%
식당 72
 
0.7%
Other values (9) 298
 
3.0%

Length

2024-03-13T08:27:41.059972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가정 4317
43.2%
na 2268
22.7%
일반도로 1077
 
10.8%
기타 974
 
9.7%
공공장소 353
 
3.5%
주택가 317
 
3.2%
고속도로 135
 
1.4%
병원 98
 
1.0%
공장 91
 
0.9%
식당 72
 
0.7%
Other values (9) 298
 
3.0%

환자증상유형
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
3046 
기타통증
2284 
기타
1217 
복통
668 
두통
450 
Other values (25)
2335 

Length

Max length5
Median length4
Mean length3.3219
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3046
30.5%
기타통증 2284
22.8%
기타 1217
 
12.2%
복통 668
 
6.7%
두통 450
 
4.5%
요통 430
 
4.3%
현기증 344
 
3.4%
의식장애 219
 
2.2%
고열 200
 
2.0%
오심/구토 194
 
1.9%
Other values (20) 948
 
9.5%

Length

2024-03-13T08:27:41.154505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3046
30.5%
기타통증 2284
22.8%
기타 1217
 
12.2%
복통 668
 
6.7%
두통 450
 
4.5%
요통 430
 
4.3%
현기증 344
 
3.4%
의식장애 219
 
2.2%
고열 200
 
2.0%
오심/구토 194
 
1.9%
Other values (20) 948
 
9.5%

Interactions

2024-03-13T08:27:39.430896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:27:41.225881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명출동소방서명환자연령환자성별구분명외국인여부국적명구급발생장소유형환자증상유형
시군명1.0001.0000.1390.0750.0830.0000.3540.137
출동소방서명1.0001.0000.1480.0640.0770.0000.3610.142
환자연령0.1390.1481.0000.1860.0500.6340.3320.424
환자성별구분명0.0750.0640.1861.0000.0000.0000.2700.189
외국인여부0.0830.0770.0500.0001.000NaN0.0590.000
국적명0.0000.0000.6340.000NaN1.0000.3190.918
구급발생장소유형0.3540.3610.3320.2700.0590.3191.0000.311
환자증상유형0.1370.1420.4240.1890.0000.9180.3111.000
2024-03-13T08:27:41.320447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
외국인여부환자성별구분명국적명구급발생장소유형시군명환자증상유형출동소방서명
외국인여부1.0000.0001.0000.0460.0660.0000.065
환자성별구분명0.0001.0000.0000.1280.0370.0960.031
국적명1.0000.0001.0000.0910.0000.5240.000
구급발생장소유형0.0460.1280.0911.0000.1030.0910.104
시군명0.0660.0370.0000.1031.0000.0321.000
환자증상유형0.0000.0960.5240.0910.0321.0000.032
출동소방서명0.0650.0310.0000.1041.0000.0321.000
2024-03-13T08:27:41.405449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
환자연령시군명출동소방서명환자성별구분명외국인여부국적명구급발생장소유형환자증상유형
환자연령1.0000.0490.0510.1140.0640.0740.1170.144
시군명0.0491.0001.0000.0370.0660.0000.1030.032
출동소방서명0.0511.0001.0000.0310.0650.0000.1040.032
환자성별구분명0.1140.0370.0311.0000.0000.0000.1280.096
외국인여부0.0640.0660.0650.0001.0001.0000.0460.000
국적명0.0740.0000.0000.0001.0001.0000.0910.524
구급발생장소유형0.1170.1030.1040.1280.0460.0911.0000.091
환자증상유형0.1440.0320.0320.0960.0000.5240.0911.000

Missing values

2024-03-13T08:27:39.523859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:27:39.637423image/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

집계년도시군명출동소방서명출동안전센터명환자연령환자성별구분명외국인여부국적명구급발생장소유형환자증상유형
576462012안산시안산소방서고잔119안전센터40남N<NA>기타기타통증
806402012수원시수원소방서지만119안전센터60여N<NA>일반도로요통
839732012광주시광주소방서경안119안전센터50남N<NA>기타기타통증
63992012수원시수원소방서원천119안전센터<NA><NA>N<NA><NA><NA>
303522012남양주시남양주소방서별내119안전센터<NA><NA>N<NA>가정<NA>
817322012수원시수원소방서파장119안전센터20여N<NA>가정복통
309222012부천시부천소방서중앙119안전센터20여N<NA>일반도로기타통증
146962012부천시부천소방서서부119안전센터40여N<NA>가정기타통증
105442012남양주시남양주소방서평내119안전센터30남N<NA>일반도로기타통증
883312012시흥시시흥소방서연성119안전센터80남N<NA>가정복통
집계년도시군명출동소방서명출동안전센터명환자연령환자성별구분명외국인여부국적명구급발생장소유형환자증상유형
798192012용인시용인소방서포곡119안전센터60남N<NA>기타기타
572122012김포시김포소방서고촌119안전센터<NA><NA>N<NA><NA><NA>
817572012화성시화성소방서향남119안전센터50남N<NA>일반도로기타통증
978392012성남시성남소방서수진119안전센터30남N<NA>일반도로기타통증
151652012고양시일산소방서주엽119안전센터50여N<NA>기타기타통증
876022012이천시이천소방서관고119안전센터80여N<NA>가정기타통증
582752012고양시고양소방서원당119안전센터20여N<NA>기타기타
653032012김포시김포소방서중앙119안전센터40남N<NA>가정토혈
94892012용인시용인소방서구갈119안전센터70남N<NA>가정현기증
796652012의정부시의정부소방서둔야119안전센터10남N<NA>학교기타통증

Duplicate rows

Most frequently occurring

집계년도시군명출동소방서명출동안전센터명환자연령환자성별구분명외국인여부국적명구급발생장소유형환자증상유형# duplicates
5202012안산시안산소방서사동119안전센터<NA><NA>N<NA><NA><NA>57
6862012용인시용인소방서구갈119안전센터<NA><NA>N<NA><NA><NA>41
5712012안성시안성소방서도기119안전센터<NA><NA>N<NA><NA><NA>39
3942012수원시수원소방서매산119안전센터<NA><NA>N<NA><NA><NA>36
4932012안산시안산소방서고잔119안전센터<NA><NA>N<NA><NA><NA>36
6782012오산시오산소방서청학119안전센터<NA><NA>N<NA><NA><NA>36
7562012의정부시의정부소방서둔야119안전센터<NA><NA>N<NA><NA><NA>36
3912012수원시수원소방서남부119안전센터<NA><NA>N<NA><NA><NA>33
352012고양시고양소방서행신119안전센터<NA><NA>N<NA><NA><NA>32
612012고양시일산소방서장항119안전센터<NA><NA>N<NA><NA><NA>31