Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells2923
Missing cells (%)2.9%
Duplicate rows939
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 939 (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 (97.1%)Imbalance
국적명 is highly imbalanced (99.2%)Imbalance
환자연령대 has 2923 (29.2%) missing valuesMissing
환자연령대 has 348 (3.5%) zerosZeros

Reproduction

Analysis started2024-03-12 23:27:46.775779
Analysis finished2024-03-12 23:27:48.021183
Duration1.25 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
2010
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2010
2nd row2010
3rd row2010
4th row2010
5th row2010

Common Values

ValueCountFrequency (%)
2010 10000
100.0%

Length

2024-03-13T08:27:48.067561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:27:48.134789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2010 10000
100.0%

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
성남시
819 
수원시
801 
고양시
764 
부천시
 
637
안산시
 
594
Other values (26)
6385 

Length

Max length4
Median length3
Mean length3.0933
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광명시
2nd row안산시
3rd row오산시
4th row동두천시
5th row수원시

Common Values

ValueCountFrequency (%)
성남시 819
 
8.2%
수원시 801
 
8.0%
고양시 764
 
7.6%
부천시 637
 
6.4%
안산시 594
 
5.9%
용인시 529
 
5.3%
안양시 436
 
4.4%
남양주시 415
 
4.2%
의정부시 393
 
3.9%
화성시 383
 
3.8%
Other values (21) 4229
42.3%

Length

2024-03-13T08:27:48.207339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성남시 819
 
8.2%
수원시 801
 
8.0%
고양시 764
 
7.6%
부천시 637
 
6.4%
안산시 594
 
5.9%
용인시 529
 
5.3%
안양시 436
 
4.4%
남양주시 415
 
4.2%
의정부시 393
 
3.9%
화성시 383
 
3.8%
Other values (21) 4229
42.3%

출동소방서명
Categorical

HIGH CORRELATION 

Distinct34
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수원소방서
801 
부천소방서
 
637
안산소방서
 
594
용인소방서
 
529
성남소방서
 
498
Other values (29)
6941 

Length

Max length6
Median length5
Mean length5.0933
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광명소방서
2nd row안산소방서
3rd row송탄소방서
4th row동두천소방서
5th row수원소방서

Common Values

ValueCountFrequency (%)
수원소방서 801
 
8.0%
부천소방서 637
 
6.4%
안산소방서 594
 
5.9%
용인소방서 529
 
5.3%
성남소방서 498
 
5.0%
안양소방서 436
 
4.4%
일산소방서 425
 
4.2%
남양주소방서 415
 
4.2%
의정부소방서 393
 
3.9%
화성소방서 383
 
3.8%
Other values (24) 4889
48.9%

Length

2024-03-13T08:27:48.295676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원소방서 801
 
8.0%
부천소방서 637
 
6.4%
안산소방서 594
 
5.9%
용인소방서 529
 
5.3%
성남소방서 498
 
5.0%
안양소방서 436
 
4.4%
일산소방서 425
 
4.2%
남양주소방서 415
 
4.2%
의정부소방서 393
 
3.9%
화성소방서 383
 
3.8%
Other values (24) 4889
48.9%

출동안전센터명
Text

Distinct168
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T08:27:48.471404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length9.0296
Min length5

Characters and Unicode

Total characters90296
Distinct characters150
Distinct categories4 ?
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 row철산119안전센터
2nd row월피119안전센터
3rd row신장119안전센터
4th row불현119안전센터
5th row권선119안전센터
ValueCountFrequency (%)
중앙119안전센터 237
 
2.4%
신장119안전센터 201
 
2.0%
은행119안전센터 193
 
1.9%
시흥119안전센터 172
 
1.7%
둔야119안전센터 158
 
1.6%
정자119안전센터 144
 
1.4%
원당119안전센터 143
 
1.4%
관고119안전센터 139
 
1.4%
수진119안전센터 131
 
1.3%
고잔119안전센터 127
 
1.3%
Other values (158) 8355
83.5%
2024-03-13T08:27:48.752021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19832
22.0%
안 10388
11.5%
전 10044
11.1%
9 9916
11.0%
센 9916
11.0%
터 9916
11.0%
원 618
 
0.7%
산 565
 
0.6%
신 553
 
0.6%
수 543
 
0.6%
Other values (140) 18005
19.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60530
67.0%
Decimal Number 29748
32.9%
Open Punctuation 9
 
< 0.1%
Close Punctuation 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 10388
17.2%
전 10044
16.6%
센 9916
16.4%
터 9916
16.4%
원 618
 
1.0%
산 565
 
0.9%
신 553
 
0.9%
수 543
 
0.9%
동 492
 
0.8%
고 487
 
0.8%
Other values (136) 17008
28.1%
Decimal Number
ValueCountFrequency (%)
1 19832
66.7%
9 9916
33.3%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60530
67.0%
Common 29766
33.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 10388
17.2%
전 10044
16.6%
센 9916
16.4%
터 9916
16.4%
원 618
 
1.0%
산 565
 
0.9%
신 553
 
0.9%
수 543
 
0.9%
동 492
 
0.8%
고 487
 
0.8%
Other values (136) 17008
28.1%
Common
ValueCountFrequency (%)
1 19832
66.6%
9 9916
33.3%
( 9
 
< 0.1%
) 9
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60530
67.0%
ASCII 29766
33.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19832
66.6%
9 9916
33.3%
( 9
 
< 0.1%
) 9
 
< 0.1%
Hangul
ValueCountFrequency (%)
안 10388
17.2%
전 10044
16.6%
센 9916
16.4%
터 9916
16.4%
원 618
 
1.0%
산 565
 
0.9%
신 553
 
0.9%
수 543
 
0.9%
동 492
 
0.8%
고 487
 
0.8%
Other values (136) 17008
28.1%

환자연령대
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.2%
Missing2923
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean46.805143
Minimum0
Maximum100
Zeros348
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T08:27:48.846153image/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 deviation22.47247
Coefficient of variation (CV)0.48012822
Kurtosis-0.68173743
Mean46.805143
Median Absolute Deviation (MAD)20
Skewness-0.2320586
Sum331240
Variance505.01191
MonotonicityNot monotonic
2024-03-13T08:27:48.926270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
40 1207
12.1%
50 1179
11.8%
70 1024
 
10.2%
60 807
 
8.1%
30 799
 
8.0%
80 693
 
6.9%
20 593
 
5.9%
0 348
 
3.5%
10 323
 
3.2%
90 99
 
1.0%
(Missing) 2923
29.2%
ValueCountFrequency (%)
0 348
 
3.5%
10 323
 
3.2%
20 593
5.9%
30 799
8.0%
40 1207
12.1%
50 1179
11.8%
60 807
8.1%
70 1024
10.2%
80 693
6.9%
90 99
 
1.0%
ValueCountFrequency (%)
100 5
 
0.1%
90 99
 
1.0%
80 693
6.9%
70 1024
10.2%
60 807
8.1%
50 1179
11.8%
40 1207
12.1%
30 799
8.0%
20 593
5.9%
10 323
 
3.2%

환자성별구분명
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
남
3891 
여
3177 
<NA>
2922 
미상
 
10

Length

Max length4
Median length1
Mean length1.8776
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남 3891
38.9%
여 3177
31.8%
<NA> 2922
29.2%
미상 10
 
0.1%

Length

2024-03-13T08:27:49.036347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:27:49.115613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 3891
38.9%
여 3177
31.8%
na 2922
29.2%
미상 10
 
0.1%

외국인여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9970 
True
 
30
ValueCountFrequency (%)
False 9970
99.7%
True 30
 
0.3%
2024-03-13T08:27:49.196487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

국적명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9982 
중국
 
5
베트남
 
3
몽골
 
3
방글라데시
 
2
Other values (3)
 
5

Length

Max length5
Median length4
Mean length3.9976
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9982
99.8%
중국 5
 
0.1%
베트남 3
 
< 0.1%
몽골 3
 
< 0.1%
방글라데시 2
 
< 0.1%
태국 2
 
< 0.1%
미국 2
 
< 0.1%
인도네시아 1
 
< 0.1%

Length

2024-03-13T08:27:49.290579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:27:49.382080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9982
99.8%
중국 5
 
< 0.1%
베트남 3
 
< 0.1%
몽골 3
 
< 0.1%
방글라데시 2
 
< 0.1%
태국 2
 
< 0.1%
미국 2
 
< 0.1%
인도네시아 1
 
< 0.1%

구급발생장소유형
Categorical

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
가정
4559 
<NA>
1789 
일반도로
1141 
기타
900 
공공장소
 
440
Other values (14)
1171 

Length

Max length4
Median length2
Mean length2.7825
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가정 4559
45.6%
<NA> 1789
 
17.9%
일반도로 1141
 
11.4%
기타 900
 
9.0%
공공장소 440
 
4.4%
주택가 359
 
3.6%
고속도로 166
 
1.7%
병원 115
 
1.1%
숙박시설 98
 
1.0%
공장 95
 
0.9%
Other values (9) 338
 
3.4%

Length

2024-03-13T08:27:49.476001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가정 4559
45.6%
na 1789
 
17.9%
일반도로 1141
 
11.4%
기타 900
 
9.0%
공공장소 440
 
4.4%
주택가 359
 
3.6%
고속도로 166
 
1.7%
병원 115
 
1.1%
숙박시설 98
 
1.0%
공장 95
 
0.9%
Other values (9) 338
 
3.4%

환자증상유형
Categorical

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
2918 
기타통증
1999 
기타
1223 
복통
654 
요통
499 
Other values (25)
2707 

Length

Max length5
Median length4
Mean length3.2678
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2918
29.2%
기타통증 1999
20.0%
기타 1223
12.2%
복통 654
 
6.5%
요통 499
 
5.0%
두통 450
 
4.5%
의식장애 385
 
3.9%
현기증 366
 
3.7%
호흡곤란 243
 
2.4%
흉통 229
 
2.3%
Other values (20) 1034
 
10.3%

Length

2024-03-13T08:27:49.570352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2918
29.2%
기타통증 1999
20.0%
기타 1223
12.2%
복통 654
 
6.5%
요통 499
 
5.0%
두통 450
 
4.5%
의식장애 385
 
3.9%
현기증 366
 
3.7%
호흡곤란 243
 
2.4%
흉통 229
 
2.3%
Other values (20) 1034
 
10.3%

Interactions

2024-03-13T08:27:47.756561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:27:49.636614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명출동소방서명환자연령대환자성별구분명외국인여부국적명구급발생장소유형환자증상유형
시군명1.0001.0000.1110.0970.0450.6310.2380.133
출동소방서명1.0001.0000.1120.1040.0460.6310.2610.144
환자연령대0.1110.1121.0000.2050.0650.0000.3090.383
환자성별구분명0.0970.1040.2051.0000.0000.0000.2740.202
외국인여부0.0450.0460.0650.0001.000NaN0.0710.128
국적명0.6310.6310.0000.000NaN1.0000.0000.000
구급발생장소유형0.2380.2610.3090.2740.0710.0001.0000.280
환자증상유형0.1330.1440.3830.2020.1280.0000.2801.000
2024-03-13T08:27:49.727825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
외국인여부환자성별구분명국적명구급발생장소유형시군명환자증상유형출동소방서명
외국인여부1.0000.0001.0000.0560.0380.1100.036
환자성별구분명0.0001.0000.0000.1300.0480.1030.051
국적명1.0000.0001.0000.0000.1660.0000.166
구급발생장소유형0.0560.1300.0001.0000.0670.0810.073
시군명0.0380.0480.1660.0671.0000.0311.000
환자증상유형0.1100.1030.0000.0810.0311.0000.033
출동소방서명0.0360.0510.1660.0731.0000.0331.000
2024-03-13T08:27:49.814439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
환자연령대시군명출동소방서명환자성별구분명외국인여부국적명구급발생장소유형환자증상유형
환자연령대1.0000.0380.0410.1240.0570.0000.1140.129
시군명0.0381.0001.0000.0480.0380.1660.0670.031
출동소방서명0.0411.0001.0000.0510.0360.1660.0730.033
환자성별구분명0.1240.0480.0511.0000.0000.0000.1300.103
외국인여부0.0570.0380.0360.0001.0001.0000.0560.110
국적명0.0000.1660.1660.0001.0001.0000.0000.000
구급발생장소유형0.1140.0670.0730.1300.0560.0001.0000.081
환자증상유형0.1290.0310.0330.1030.1100.0000.0811.000

Missing values

2024-03-13T08:27:47.846911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:27:47.963195image/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
669402010광명시광명소방서철산119안전센터30여N<NA>공공장소의식장애
103662010안산시안산소방서월피119안전센터30여N<NA>가정기타
750132010오산시송탄소방서신장119안전센터<NA><NA>N<NA><NA><NA>
296692010동두천시동두천소방서불현119안전센터<NA><NA>N<NA><NA><NA>
806102010수원시수원소방서권선119안전센터0남N<NA>가정발작
588152010고양시고양소방서행신119안전센터60여N<NA>가정복통
145482010의정부시의정부소방서둔야119안전센터50여N<NA>숙박시설기타
865722010이천시이천소방서대월119안전센터30남N<NA>기타기타통증
19812010동두천시동두천소방서불현119안전센터30여N<NA>가정요통
364352010부천시부천소방서내동119안전센터<NA><NA>N<NA><NA><NA>
집계년도시군명출동소방서명출동안전센터명환자연령대환자성별구분명외국인여부국적명구급발생장소유형환자증상유형
909422010성남시분당소방서서현119안전센터50남N<NA>식당기타통증
386822010안산시안산소방서선부119안전센터<NA><NA>N<NA>가정<NA>
919342010부천시부천소방서심곡119안전센터50남N<NA>가정흉통
522552010의왕시의왕소방서고천119안전센터<NA><NA>N<NA><NA><NA>
708682010여주시여주소방서여주119안전센터60여N<NA>가정기타
858072010용인시용인소방서역북119안전센터<NA><NA>N<NA><NA><NA>
653602010부천시부천소방서상동119안전센터<NA><NA>N<NA>주택가<NA>
622922010연천군연천소방서전곡119안전센터<NA><NA>N<NA>가정<NA>
153642010성남시성남소방서수진119안전센터<NA><NA>N<NA>가정<NA>
528792010고양시고양소방서원당119안전센터10남N<NA>일반도로기타

Duplicate rows

Most frequently occurring

집계년도시군명출동소방서명출동안전센터명환자연령대환자성별구분명외국인여부국적명구급발생장소유형환자증상유형# duplicates
3642010성남시성남소방서신흥119안전센터<NA><NA>N<NA><NA><NA>34
4792010시흥시시흥소방서시흥119안전센터<NA><NA>N<NA><NA><NA>30
5612010안성시안성소방서도기119안전센터<NA><NA>N<NA><NA><NA>29
5902010안양시안양소방서석수119안전센터<NA><NA>N<NA><NA><NA>29
3342010성남시성남소방서상대원119안전센터<NA><NA>N<NA><NA><NA>28
392010고양시고양소방서원당119안전센터<NA><NA>N<NA><NA><NA>27
5082010안산시안산소방서고잔119안전센터<NA><NA>N<NA><NA><NA>27
9382010화성시화성소방서향남119안전센터<NA><NA>N<NA><NA><NA>26
3722010성남시성남소방서은행119안전센터<NA><NA>N<NA><NA><NA>25
772010고양시일산소방서주엽119안전센터<NA><NA>N<NA><NA><NA>24