Overview

Dataset statistics

Number of variables31
Number of observations10000
Missing cells3480
Missing cells (%)1.1%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory2.5 MiB
Average record size in memory258.0 B

Variable types

Categorical17
Text4
DateTime8
Numeric1
Boolean1

Dataset

Description수도권(서울특별시, 경기도, 인천광역시)의 2018년의 구급활동현황에 대한 정보를 제공하는 데이터 제공항목 : 출동년월일, 출동시각, 현장도작시간, 현장과의 거리, 환자연령대, 성별, 긴급구조위치, 외국인유무, 환자증상 등의 정보를 제공합니다.
Author소방청
URLhttps://www.data.go.kr/data/15086458/fileData.do

Alerts

집계년도 has constant value ""Constant
긴급구조시 has constant value ""Constant
Dataset has 1 (< 0.1%) duplicate rowsDuplicates
접수경로 is highly imbalanced (68.3%)Imbalance
외국인유무 is highly imbalanced (91.1%)Imbalance
환자증상2 is highly imbalanced (63.3%)Imbalance
질병외_교통사고 is highly imbalanced (80.7%)Imbalance
질병외_사고부상 is highly imbalanced (75.6%)Imbalance
질병외_비외상성손상 is highly imbalanced (96.9%)Imbalance
구급대원1_자격 is highly imbalanced (59.3%)Imbalance
구급대원2_자격 is highly imbalanced (52.6%)Imbalance
현장도착년월일 has 1739 (17.4%) missing valuesMissing
현장도착시각 has 1739 (17.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 06:34:54.657595
Analysis finished2023-12-12 06:34:59.166174
Duration4.51 seconds
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
2018
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2018 10000
100.0%

Length

2023-12-12T15:34:59.241983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:34:59.342200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 10000
100.0%

시군명
Categorical

Distinct43
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
부천시
 
604
남양주시
 
504
화성시
 
501
평택시
 
447
의정부시
 
374
Other values (38)
7570 

Length

Max length8
Median length3
Mean length4.7182
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row김포시
2nd row남양주시
3rd row안산시 상록구
4th row부천시
5th row평택시

Common Values

ValueCountFrequency (%)
부천시 604
 
6.0%
남양주시 504
 
5.0%
화성시 501
 
5.0%
평택시 447
 
4.5%
의정부시 374
 
3.7%
파주시 363
 
3.6%
성남시 분당구 349
 
3.5%
시흥시 320
 
3.2%
안산시 단원구 320
 
3.2%
고양시 덕양구 311
 
3.1%
Other values (33) 5907
59.1%

Length

2023-12-12T15:34:59.448078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 885
 
6.3%
성남시 762
 
5.5%
고양시 654
 
4.7%
용인시 641
 
4.6%
부천시 604
 
4.3%
안산시 603
 
4.3%
남양주시 504
 
3.6%
화성시 501
 
3.6%
평택시 447
 
3.2%
안양시 413
 
3.0%
Other values (39) 7944
56.9%

출동소방서
Text

Distinct54
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T15:34:59.688781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.3875
Min length5

Characters and Unicode

Total characters53875
Distinct characters76
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 row김포소방서
2nd row남양주소방서
3rd row군포소방서
4th row부천소방서
5th row송탄소방서
ValueCountFrequency (%)
부천소방서 612
 
6.1%
용인소방서 583
 
5.8%
수원남부소방서 522
 
5.2%
안산소방서 504
 
5.0%
남양주소방서 463
 
4.6%
화성소방서 427
 
4.3%
수원소방서 425
 
4.2%
안양소방서 410
 
4.1%
성남소방서 404
 
4.0%
분당소방서 387
 
3.9%
Other values (44) 5263
52.6%
2023-12-12T15:35:00.140616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 9539
17.7%
방 9539
17.7%
서 9532
17.7%
안 1559
 
2.9%
남 1546
 
2.9%
부 1523
 
2.8%
양 1478
 
2.7%
주 1361
 
2.5%
천 1205
 
2.2%
성 1015
 
1.9%
Other values (66) 15578
28.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52492
97.4%
Decimal Number 1383
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 9539
18.2%
방 9539
18.2%
서 9532
18.2%
안 1559
 
3.0%
남 1546
 
2.9%
부 1523
 
2.9%
양 1478
 
2.8%
주 1361
 
2.6%
천 1205
 
2.3%
성 1015
 
1.9%
Other values (64) 14195
27.0%
Decimal Number
ValueCountFrequency (%)
1 922
66.7%
9 461
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52492
97.4%
Common 1383
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 9539
18.2%
방 9539
18.2%
서 9532
18.2%
안 1559
 
3.0%
남 1546
 
2.9%
부 1523
 
2.9%
양 1478
 
2.8%
주 1361
 
2.6%
천 1205
 
2.3%
성 1015
 
1.9%
Other values (64) 14195
27.0%
Common
ValueCountFrequency (%)
1 922
66.7%
9 461
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52492
97.4%
ASCII 1383
 
2.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 9539
18.2%
방 9539
18.2%
서 9532
18.2%
안 1559
 
3.0%
남 1546
 
2.9%
부 1523
 
2.9%
양 1478
 
2.8%
주 1361
 
2.6%
천 1205
 
2.3%
성 1015
 
1.9%
Other values (64) 14195
27.0%
ASCII
ValueCountFrequency (%)
1 922
66.7%
9 461
33.3%

출동안전센터_지역대
Text

Distinct192
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T15:35:00.408975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length8.5946
Min length5

Characters and Unicode

Total characters85946
Distinct characters155
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st row마산119안전센터
2nd row가운119안전센터
3rd row119구조대
4th row상동119안전센터
5th row청북119안전센터
ValueCountFrequency (%)
119구조대 734
 
7.3%
신장119안전센터 171
 
1.7%
흥선119안전센터 171
 
1.7%
매산119안전센터 161
 
1.6%
정자119안전센터 142
 
1.4%
남부119안전센터 137
 
1.4%
상록수출동대 133
 
1.3%
시흥119안전센터 130
 
1.3%
안양119안전센터 128
 
1.3%
구갈119안전센터 126
 
1.3%
Other values (182) 7967
79.7%
2023-12-12T15:35:01.150412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19140
22.3%
9 9570
11.1%
안 8947
10.4%
전 8711
10.1%
센 8554
10.0%
터 8554
10.0%
대 1722
 
2.0%
구 1162
 
1.4%
조 839
 
1.0%
동 666
 
0.8%
Other values (145) 18081
21.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57236
66.6%
Decimal Number 28710
33.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 8947
15.6%
전 8711
15.2%
센 8554
14.9%
터 8554
14.9%
대 1722
 
3.0%
구 1162
 
2.0%
조 839
 
1.5%
동 666
 
1.2%
수 573
 
1.0%
지 568
 
1.0%
Other values (143) 16940
29.6%
Decimal Number
ValueCountFrequency (%)
1 19140
66.7%
9 9570
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57236
66.6%
Common 28710
33.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 8947
15.6%
전 8711
15.2%
센 8554
14.9%
터 8554
14.9%
대 1722
 
3.0%
구 1162
 
2.0%
조 839
 
1.5%
동 666
 
1.2%
수 573
 
1.0%
지 568
 
1.0%
Other values (143) 16940
29.6%
Common
ValueCountFrequency (%)
1 19140
66.7%
9 9570
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57236
66.6%
ASCII 28710
33.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19140
66.7%
9 9570
33.3%
Hangul
ValueCountFrequency (%)
안 8947
15.6%
전 8711
15.2%
센 8554
14.9%
터 8554
14.9%
대 1722
 
3.0%
구 1162
 
2.0%
조 839
 
1.5%
동 666
 
1.2%
수 573
 
1.0%
지 568
 
1.0%
Other values (143) 16940
29.6%

신고년월일
Date

Distinct365
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-01-01 00:00:00
Maximum2018-12-31 00:00:00
2023-12-12T15:35:01.300837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:35:01.436285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

신고시각
Date

Distinct1438
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 23:59:00
2023-12-12T15:35:01.585382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:35:01.740411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

접수경로
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
휴대전화
8346 
일반전화
984 
기타
 
658
공중전화
 
6
무전기
 
4

Length

Max length4
Median length4
Mean length3.868
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
휴대전화 8346
83.5%
일반전화 984
 
9.8%
기타 658
 
6.6%
공중전화 6
 
0.1%
무전기 4
 
< 0.1%
<NA> 2
 
< 0.1%

Length

2023-12-12T15:35:01.934853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:35:02.083238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휴대전화 8346
83.5%
일반전화 984
 
9.8%
기타 658
 
6.6%
공중전화 6
 
0.1%
무전기 4
 
< 0.1%
na 2
 
< 0.1%

관할구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
센터
7983 
센터외
2017 

Length

Max length3
Median length2
Mean length2.2017
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row센터
2nd row센터
3rd row센터외
4th row센터
5th row센터외

Common Values

ValueCountFrequency (%)
센터 7983
79.8%
센터외 2017
 
20.2%

Length

2023-12-12T15:35:02.221300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:35:02.353743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
센터 7983
79.8%
센터외 2017
 
20.2%

출동년월일
Date

Distinct365
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-01-01 00:00:00
Maximum2018-12-31 00:00:00
2023-12-12T15:35:02.502886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:35:02.666823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

출동시각
Date

Distinct1436
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 23:59:00
2023-12-12T15:35:02.835320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:35:03.014397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

현장도착년월일
Date

MISSING 

Distinct365
Distinct (%)4.4%
Missing1739
Missing (%)17.4%
Memory size156.2 KiB
Minimum2018-01-01 00:00:00
Maximum2018-12-31 00:00:00
2023-12-12T15:35:03.168164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:35:03.340626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

현장도착시각
Date

MISSING 

Distinct1422
Distinct (%)17.2%
Missing1739
Missing (%)17.4%
Memory size156.2 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 23:59:00
2023-12-12T15:35:03.502969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:35:03.650812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

현장과의거리
Real number (ℝ)

Distinct200
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.02489
Minimum0
Maximum80
Zeros8
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:35:03.801821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.6
Q11.2
median2
Q33.7
95-th percentile8.3
Maximum80
Range80
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation3.316641
Coefficient of variation (CV)1.0964501
Kurtosis96.157802
Mean3.02489
Median Absolute Deviation (MAD)1
Skewness6.6122483
Sum30248.9
Variance11.000107
MonotonicityNot monotonic
2023-12-12T15:35:04.005589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 604
 
6.0%
1.1 448
 
4.5%
2.0 431
 
4.3%
1.5 383
 
3.8%
3.0 320
 
3.2%
1.4 307
 
3.1%
1.7 304
 
3.0%
0.8 284
 
2.8%
1.9 251
 
2.5%
1.6 251
 
2.5%
Other values (190) 6417
64.2%
ValueCountFrequency (%)
0.0 8
 
0.1%
0.1 36
 
0.4%
0.2 50
 
0.5%
0.3 88
 
0.9%
0.4 155
1.6%
0.5 128
1.3%
0.6 186
1.9%
0.7 184
1.8%
0.8 284
2.8%
0.9 234
2.3%
ValueCountFrequency (%)
80.0 1
< 0.1%
70.0 2
< 0.1%
60.0 1
< 0.1%
53.0 1
< 0.1%
52.2 1
< 0.1%
50.0 1
< 0.1%
45.0 1
< 0.1%
40.0 1
< 0.1%
35.4 1
< 0.1%
35.0 1
< 0.1%

귀소년월일
Date

Distinct365
Distinct (%)3.7%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
Minimum2018-01-01 00:00:00
Maximum2018-12-31 00:00:00
2023-12-12T15:35:04.171798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:35:04.319892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

귀소시각
Date

Distinct1429
Distinct (%)14.3%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 23:59:00
2023-12-12T15:35:04.475693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:35:04.638692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

환자연령대
Categorical

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
2748 
50대
1333 
70대
1015 
60대
1012 
40대
926 
Other values (6)
2966 

Length

Max length4
Median length3
Mean length3.2354
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20대
2nd row<NA>
3rd row<NA>
4th row50대
5th row70대

Common Values

ValueCountFrequency (%)
<NA> 2748
27.5%
50대 1333
13.3%
70대 1015
 
10.2%
60대 1012
 
10.1%
40대 926
 
9.3%
80대 827
 
8.3%
30대 665
 
6.7%
20대 558
 
5.6%
유아 394
 
3.9%
10대 323
 
3.2%

Length

2023-12-12T15:35:04.773377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2748
27.5%
50대 1333
13.3%
70대 1015
 
10.2%
60대 1012
 
10.1%
40대 926
 
9.3%
80대 827
 
8.3%
30대 665
 
6.7%
20대 558
 
5.6%
유아 394
 
3.9%
10대 323
 
3.2%

환자성별
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
남
4069 
여
3305 
<NA>
2626 

Length

Max length4
Median length1
Mean length1.7878
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남 4069
40.7%
여 3305
33.1%
<NA> 2626
26.3%

Length

2023-12-12T15:35:04.916093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:35:05.043009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 4069
40.7%
여 3305
33.1%
na 2626
26.3%

긴급구조시
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 10000
100.0%

Length

2023-12-12T15:35:05.159123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:35:05.263228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 10000
100.0%

긴급구조구
Categorical

Distinct43
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
부천시
 
604
남양주시
 
504
화성시
 
501
평택시
 
447
의정부시
 
374
Other values (38)
7570 

Length

Max length8
Median length3
Mean length4.7182
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row김포시
2nd row남양주시
3rd row안산시 상록구
4th row부천시
5th row평택시

Common Values

ValueCountFrequency (%)
부천시 604
 
6.0%
남양주시 504
 
5.0%
화성시 501
 
5.0%
평택시 447
 
4.5%
의정부시 374
 
3.7%
파주시 363
 
3.6%
성남시 분당구 349
 
3.5%
시흥시 320
 
3.2%
안산시 단원구 320
 
3.2%
고양시 덕양구 311
 
3.1%
Other values (33) 5907
59.1%

Length

2023-12-12T15:35:05.414265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 885
 
6.3%
성남시 762
 
5.5%
고양시 654
 
4.7%
용인시 641
 
4.6%
부천시 604
 
4.3%
안산시 603
 
4.3%
남양주시 504
 
3.6%
화성시 501
 
3.6%
평택시 447
 
3.2%
안양시 413
 
3.0%
Other values (39) 7944
56.9%

긴급구조동
Text

Distinct647
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T15:35:05.769976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.9921
Min length2

Characters and Unicode

Total characters29921
Distinct characters234
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

Unique69 ?
Unique (%)0.7%

Sample

1st row마산동
2nd row지금동
3rd row수암동
4th row상동
5th row포승읍
ValueCountFrequency (%)
정왕동 141
 
1.4%
안양동 135
 
1.4%
중동 129
 
1.3%
정자동 124
 
1.2%
의정부동 99
 
1.0%
화도읍 96
 
1.0%
고잔동 95
 
0.9%
상동 87
 
0.9%
산본동 84
 
0.8%
본오동 79
 
0.8%
Other values (637) 8931
89.3%
2023-12-12T15:35:06.331136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 7939
26.5%
읍 1213
 
4.1%
면 1078
 
3.6%
정 736
 
2.5%
산 585
 
2.0%
곡 445
 
1.5%
양 436
 
1.5%
원 432
 
1.4%
신 379
 
1.3%
안 350
 
1.2%
Other values (224) 16328
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29864
99.8%
Decimal Number 57
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 7939
26.6%
읍 1213
 
4.1%
면 1078
 
3.6%
정 736
 
2.5%
산 585
 
2.0%
곡 445
 
1.5%
양 436
 
1.5%
원 432
 
1.4%
신 379
 
1.3%
안 350
 
1.2%
Other values (221) 16271
54.5%
Decimal Number
ValueCountFrequency (%)
1 37
64.9%
2 14
 
24.6%
3 6
 
10.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29864
99.8%
Common 57
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 7939
26.6%
읍 1213
 
4.1%
면 1078
 
3.6%
정 736
 
2.5%
산 585
 
2.0%
곡 445
 
1.5%
양 436
 
1.5%
원 432
 
1.4%
신 379
 
1.3%
안 350
 
1.2%
Other values (221) 16271
54.5%
Common
ValueCountFrequency (%)
1 37
64.9%
2 14
 
24.6%
3 6
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29864
99.8%
ASCII 57
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 7939
26.6%
읍 1213
 
4.1%
면 1078
 
3.6%
정 736
 
2.5%
산 585
 
2.0%
곡 445
 
1.5%
양 436
 
1.5%
원 432
 
1.4%
신 379
 
1.3%
안 350
 
1.2%
Other values (221) 16271
54.5%
ASCII
ValueCountFrequency (%)
1 37
64.9%
2 14
 
24.6%
3 6
 
10.5%

긴급구조리
Text

Distinct1213
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T15:35:06.743989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.9949
Min length2

Characters and Unicode

Total characters29949
Distinct characters278
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

Unique345 ?
Unique (%)3.5%

Sample

1st row마산동
2nd row지금동
3rd row수암동
4th row상동
5th row홍원리
ValueCountFrequency (%)
정왕동 141
 
1.4%
안양동 135
 
1.4%
중동 129
 
1.3%
정자동 124
 
1.2%
의정부동 99
 
1.0%
고잔동 95
 
0.9%
상동 87
 
0.9%
산본동 84
 
0.8%
본오동 79
 
0.8%
사동 67
 
0.7%
Other values (1203) 8960
89.6%
2023-12-12T15:35:07.321090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 7936
26.5%
리 2284
 
7.6%
정 780
 
2.6%
산 674
 
2.3%
곡 596
 
2.0%
원 428
 
1.4%
신 424
 
1.4%
양 402
 
1.3%
안 340
 
1.1%
현 323
 
1.1%
Other values (268) 15762
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29892
99.8%
Decimal Number 57
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 7936
26.5%
리 2284
 
7.6%
정 780
 
2.6%
산 674
 
2.3%
곡 596
 
2.0%
원 428
 
1.4%
신 424
 
1.4%
양 402
 
1.3%
안 340
 
1.1%
현 323
 
1.1%
Other values (265) 15705
52.5%
Decimal Number
ValueCountFrequency (%)
1 37
64.9%
2 14
 
24.6%
3 6
 
10.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29892
99.8%
Common 57
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 7936
26.5%
리 2284
 
7.6%
정 780
 
2.6%
산 674
 
2.3%
곡 596
 
2.0%
원 428
 
1.4%
신 424
 
1.4%
양 402
 
1.3%
안 340
 
1.1%
현 323
 
1.1%
Other values (265) 15705
52.5%
Common
ValueCountFrequency (%)
1 37
64.9%
2 14
 
24.6%
3 6
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29892
99.8%
ASCII 57
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 7936
26.5%
리 2284
 
7.6%
정 780
 
2.6%
산 674
 
2.3%
곡 596
 
2.0%
원 428
 
1.4%
신 424
 
1.4%
양 402
 
1.3%
안 340
 
1.1%
현 323
 
1.1%
Other values (265) 15705
52.5%
ASCII
ValueCountFrequency (%)
1 37
64.9%
2 14
 
24.6%
3 6
 
10.5%

외국인유무
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9888 
True
 
112
ValueCountFrequency (%)
False 9888
98.9%
True 112
 
1.1%
2023-12-12T15:35:07.480228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

환자증상1
Categorical

Distinct43
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
3243 
기타통증
1608 
기타
838 
복통
707 
요통
430 
Other values (38)
3174 

Length

Max length6
Median length4
Mean length3.3557
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3243
32.4%
기타통증 1608
16.1%
기타 838
 
8.4%
복통 707
 
7.1%
요통 430
 
4.3%
오심/구토 415
 
4.2%
두통 387
 
3.9%
열상 321
 
3.2%
전신쇠약 312
 
3.1%
고열 247
 
2.5%
Other values (33) 1492
14.9%

Length

2023-12-12T15:35:07.592467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3243
32.0%
기타통증 1608
15.9%
기타 838
 
8.3%
복통 707
 
7.0%
요통 430
 
4.2%
오심/구토 415
 
4.1%
두통 387
 
3.8%
열상 321
 
3.2%
전신쇠약 312
 
3.1%
고열 247
 
2.4%
Other values (34) 1620
16.0%

환자증상2
Categorical

IMBALANCE 

Distinct42
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7227 
기타
 
486
오심/구토
 
336
전신쇠약
 
255
기타통증
 
232
Other values (37)
1464 

Length

Max length6
Median length4
Mean length3.8019
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> 7227
72.3%
기타 486
 
4.9%
오심/구토 336
 
3.4%
전신쇠약 255
 
2.5%
기타통증 232
 
2.3%
찰과상 215
 
2.1%
열상 180
 
1.8%
호흡정지 160
 
1.6%
어지러움 132
 
1.3%
그 밖의출혈 111
 
1.1%
Other values (32) 666
 
6.7%

Length

2023-12-12T15:35:07.752942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7227
71.5%
기타 486
 
4.8%
오심/구토 336
 
3.3%
전신쇠약 255
 
2.5%
기타통증 232
 
2.3%
찰과상 215
 
2.1%
열상 180
 
1.8%
호흡정지 160
 
1.6%
어지러움 132
 
1.3%
고열 111
 
1.1%
Other values (33) 777
 
7.7%

질병외_교통사고
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9228 
운전자
 
237
동승자
 
177
보행자
 
136
오토바이사고
 
105
Other values (3)
 
117

Length

Max length6
Median length4
Mean length3.9735
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9228
92.3%
운전자 237
 
2.4%
동승자 177
 
1.8%
보행자 136
 
1.4%
오토바이사고 105
 
1.1%
자전거사고 85
 
0.9%
기타탈것 27
 
0.3%
미상 5
 
0.1%

Length

2023-12-12T15:35:07.907176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:35:08.396873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9228
92.3%
운전자 237
 
2.4%
동승자 177
 
1.8%
보행자 136
 
1.4%
오토바이사고 105
 
1.1%
자전거사고 85
 
0.9%
기타탈것 27
 
0.3%
미상 5
 
< 0.1%

질병외_사고부상
Categorical

IMBALANCE 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8339 
낙상
 
807
기타(사고부상)
 
210
열상
 
174
상해
 
157
Other values (16)
 
313

Length

Max length8
Median length4
Mean length3.8263
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8339
83.4%
낙상 807
 
8.1%
기타(사고부상) 210
 
2.1%
열상 174
 
1.7%
상해 157
 
1.6%
추락 91
 
0.9%
기타 둔상 68
 
0.7%
동물/곤충 37
 
0.4%
기계 36
 
0.4%
중독 21
 
0.2%
Other values (11) 60
 
0.6%

Length

2023-12-12T15:35:08.523910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8339
82.8%
낙상 807
 
8.0%
기타(사고부상 210
 
2.1%
열상 174
 
1.7%
상해 157
 
1.6%
추락 91
 
0.9%
기타 68
 
0.7%
둔상 68
 
0.7%
동물/곤충 37
 
0.4%
기계 36
 
0.4%
Other values (12) 81
 
0.8%

질병외_비외상성손상
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9903 
중독
 
34
연기흡입
 
23
목맴/목졸림
 
18
(구)온열손상
 
6
Other values (5)
 
16

Length

Max length7
Median length4
Mean length3.9985
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> 9903
99.0%
중독 34
 
0.3%
연기흡입 23
 
0.2%
목맴/목졸림 18
 
0.2%
(구)온열손상 6
 
0.1%
기타(질병외) 5
 
0.1%
질식 4
 
< 0.1%
화학물질 3
 
< 0.1%
익수 3
 
< 0.1%
화상 1
 
< 0.1%

Length

2023-12-12T15:35:08.660842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:35:08.808511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9903
99.0%
중독 34
 
0.3%
연기흡입 23
 
0.2%
목맴/목졸림 18
 
0.2%
구)온열손상 6
 
0.1%
기타(질병외 5
 
< 0.1%
질식 4
 
< 0.1%
화학물질 3
 
< 0.1%
익수 3
 
< 0.1%
화상 1
 
< 0.1%

의식상태
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
A(Alert)
6346 
<NA>
3061 
U(Coma)
 
229
V:언어지시에 반응
 
199
P:통증.자극에 반응
 
165

Length

Max length11
Median length8
Mean length6.842
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA(Alert)
2nd row<NA>
3rd row<NA>
4th rowA(Alert)
5th row<NA>

Common Values

ValueCountFrequency (%)
A(Alert) 6346
63.5%
<NA> 3061
30.6%
U(Coma) 229
 
2.3%
V:언어지시에 반응 199
 
2.0%
P:통증.자극에 반응 165
 
1.7%

Length

2023-12-12T15:35:08.953847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:35:09.068436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a(alert 6346
61.2%
na 3061
29.5%
반응 364
 
3.5%
u(coma 229
 
2.2%
v:언어지시에 199
 
1.9%
p:통증.자극에 165
 
1.6%

구급대원1_자격
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
응급구조사(1급)
6977 
간호사
2936 
<NA>
 
81
응급구조사(2급)
 
5
기타
 
1

Length

Max length9
Median length9
Mean length7.1972
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row응급구조사(1급)
2nd row응급구조사(1급)
3rd row응급구조사(1급)
4th row응급구조사(1급)
5th row응급구조사(1급)

Common Values

ValueCountFrequency (%)
응급구조사(1급) 6977
69.8%
간호사 2936
29.4%
<NA> 81
 
0.8%
응급구조사(2급) 5
 
0.1%
기타 1
 
< 0.1%

Length

2023-12-12T15:35:09.192541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:35:09.315091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
응급구조사(1급 6977
69.8%
간호사 2936
29.4%
na 81
 
0.8%
응급구조사(2급 5
 
< 0.1%
기타 1
 
< 0.1%

구급대원2_자격
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7480 
응급구조사(1급)
1390 
간호사
 
521
기타
 
508
응급구조사(2급)
 
58

Length

Max length9
Median length4
Mean length4.5703
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7480
74.8%
응급구조사(1급) 1390
 
13.9%
간호사 521
 
5.2%
기타 508
 
5.1%
응급구조사(2급) 58
 
0.6%
구급교육 43
 
0.4%

Length

2023-12-12T15:35:09.491031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:35:09.643702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7480
74.8%
응급구조사(1급 1390
 
13.9%
간호사 521
 
5.2%
기타 508
 
5.1%
응급구조사(2급 58
 
0.6%
구급교육 43
 
0.4%

운전요원_자격
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
응급구조사(2급)
5215 
응급구조사(1급)
3589 
간호사
987 
구급교육
 
176
<NA>
 
32

Length

Max length9
Median length9
Mean length8.3031
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row응급구조사(2급)
2nd row응급구조사(2급)
3rd row응급구조사(1급)
4th row응급구조사(2급)
5th row응급구조사(1급)

Common Values

ValueCountFrequency (%)
응급구조사(2급) 5215
52.1%
응급구조사(1급) 3589
35.9%
간호사 987
 
9.9%
구급교육 176
 
1.8%
<NA> 32
 
0.3%
기타 1
 
< 0.1%

Length

2023-12-12T15:35:09.779898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:35:09.945770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
응급구조사(2급 5215
52.1%
응급구조사(1급 3589
35.9%
간호사 987
 
9.9%
구급교육 176
 
1.8%
na 32
 
0.3%
기타 1
 
< 0.1%

Sample

집계년도시군명출동소방서출동안전센터_지역대신고년월일신고시각접수경로관할구분출동년월일출동시각현장도착년월일현장도착시각현장과의거리귀소년월일귀소시각환자연령대환자성별긴급구조시긴급구조구긴급구조동긴급구조리외국인유무환자증상1환자증상2질병외_교통사고질병외_사고부상질병외_비외상성손상의식상태구급대원1_자격구급대원2_자격운전요원_자격
41302018김포시김포소방서마산119안전센터2018-04-3002:19휴대전화센터2018-04-3002:212018-04-3002:230.12018-04-3002:3520대남경기도김포시마산동마산동N기타통증<NA><NA><NA><NA>A(Alert)응급구조사(1급)<NA>응급구조사(2급)
130432018남양주시남양주소방서가운119안전센터2018-11-1600:50휴대전화센터2018-11-1601:01<NA><NA>0.52018-11-1601:08<NA><NA>경기도남양주시지금동지금동N<NA><NA><NA><NA><NA><NA>응급구조사(1급)<NA>응급구조사(2급)
251782018안산시 상록구군포소방서119구조대2018-02-2301:02휴대전화센터외2018-02-2301:062018-02-2301:144.92018-02-2301:41<NA><NA>경기도안산시 상록구수암동수암동N<NA><NA><NA><NA><NA><NA>응급구조사(1급)<NA>응급구조사(1급)
227372018부천시부천소방서상동119안전센터2018-03-2415:06휴대전화센터2018-03-2415:072018-03-2415:140.72018-03-2416:0250대남경기도부천시상동상동N기타<NA><NA><NA><NA>A(Alert)응급구조사(1급)<NA>응급구조사(2급)
165822018평택시송탄소방서청북119안전센터2018-07-2811:19휴대전화센터외2018-07-2811:212018-07-2811:476.02018-07-2812:2770대여경기도평택시포승읍홍원리N<NA><NA><NA><NA><NA><NA>응급구조사(1급)<NA>응급구조사(1급)
237752018수원시 팔달구수원소방서정자119안전센터2018-10-1322:44기타센터외2018-10-1322:442018-10-1322:531.92018-10-1323:3570대여경기도수원시 팔달구장안동장안동N기타통증<NA><NA>기타(사고부상)<NA>A(Alert)응급구조사(1급)<NA>응급구조사(2급)
20422018성남시 분당구성남소방서수진119안전센터2018-09-0212:34기타센터2018-09-0212:362018-09-0212:493.52018-09-0213:0940대남경기도성남시 분당구야탑동야탑동N<NA><NA><NA><NA><NA><NA>응급구조사(1급)<NA>간호사
144162018광명시광명소방서광남119안전센터2018-01-2713:29휴대전화센터2018-01-2713:32<NA><NA>2.12018-01-2713:34<NA><NA>경기도광명시광명동광명동N<NA><NA><NA><NA><NA><NA>응급구조사(1급)<NA>응급구조사(2급)
316212018안산시 단원구안산소방서선부119안전센터2018-08-0722:07휴대전화센터2018-08-0722:082018-08-0722:144.02018-08-0722:3730대남경기도안산시 단원구와동와동N기타통증골절<NA>낙상<NA>A(Alert)응급구조사(1급)기타응급구조사(2급)
245672018오산시오산소방서청학119안전센터2018-05-2812:10휴대전화센터2018-05-2812:11<NA><NA>0.92018-05-2812:27<NA><NA>경기도오산시오산동오산동N<NA><NA><NA><NA><NA><NA>응급구조사(1급)<NA>응급구조사(1급)
집계년도시군명출동소방서출동안전센터_지역대신고년월일신고시각접수경로관할구분출동년월일출동시각현장도착년월일현장도착시각현장과의거리귀소년월일귀소시각환자연령대환자성별긴급구조시긴급구조구긴급구조동긴급구조리외국인유무환자증상1환자증상2질병외_교통사고질병외_사고부상질병외_비외상성손상의식상태구급대원1_자격구급대원2_자격운전요원_자격
73242018오산시오산소방서청학119안전센터2018-09-0408:17휴대전화센터2018-09-0408:192018-09-0408:261.52018-09-0409:3730대여경기도오산시수청동수청동N기타<NA><NA><NA><NA>A(Alert)응급구조사(1급)<NA>응급구조사(1급)
57732018안양시 만안구안양소방서안양119안전센터2018-07-3110:04휴대전화센터2018-07-3110:05<NA><NA>4.02018-07-3110:16<NA><NA>경기도안양시 만안구석수동석수동N<NA><NA><NA><NA><NA><NA>응급구조사(1급)<NA>응급구조사(1급)
54992018파주시파주소방서탄현119안전센터2018-03-1713:57휴대전화센터외2018-03-1714:02<NA><NA>7.72018-03-1715:19<NA><NA>경기도파주시금촌동금촌동N<NA><NA><NA><NA><NA><NA>간호사<NA>응급구조사(2급)
130782018의왕시의왕소방서부곡119안전센터2018-11-0610:31휴대전화센터2018-11-0610:342018-11-0610:403.02018-11-0611:2750대남경기도의왕시월암동월암동N기타통증찰과상자전거사고<NA><NA>A(Alert)응급구조사(1급)<NA>응급구조사(2급)
57522018파주시일산소방서중산119안전센터2018-07-0816:35휴대전화센터외2018-07-0816:382018-07-0816:515.62018-07-0817:55<NA><NA>경기도파주시야당동야당동N<NA><NA><NA><NA><NA><NA>간호사<NA>응급구조사(2급)
331922018파주시일산소방서대화119안전센터2018-12-0918:05휴대전화센터외2018-12-0918:09<NA><NA>5.82018-12-0918:22<NA><NA>경기도파주시야당동야당동N<NA><NA><NA><NA><NA><NA>응급구조사(1급)<NA>간호사
336782018화성시화성소방서남양119안전센터2018-03-1119:23휴대전화센터2018-03-1119:252018-03-1119:362.82018-03-1120:1440대남경기도화성시마도면두곡리N기타통증기타<NA><NA><NA>A(Alert)응급구조사(1급)<NA>응급구조사(2급)
428462018광주시광주소방서오포119안전센터2018-12-0421:54휴대전화센터2018-12-0421:562018-12-0421:593.12018-12-0422:2820대남경기도광주시오포읍매산리N기타통증기타<NA><NA><NA>A(Alert)간호사<NA>간호사
34162018화성시화성소방서남양119안전센터2018-01-0219:58휴대전화센터2018-01-0220:002018-01-0220:031.02018-01-0220:5830대남경기도화성시남양읍남양리N기타통증<NA><NA>낙상<NA>A(Alert)응급구조사(1급)<NA>응급구조사(2급)
63362018부천시부천소방서중앙119안전센터2018-02-2214:18휴대전화센터외2018-02-2214:192018-02-2214:231.12018-02-2214:4850대여경기도부천시중동중동N의식장애<NA><NA><NA>중독V:언어지시에 반응응급구조사(1급)응급구조사(1급)응급구조사(1급)

Duplicate rows

Most frequently occurring

집계년도시군명출동소방서출동안전센터_지역대신고년월일신고시각접수경로관할구분출동년월일출동시각현장도착년월일현장도착시각현장과의거리귀소년월일귀소시각환자연령대환자성별긴급구조시긴급구조구긴급구조동긴급구조리외국인유무환자증상1환자증상2질병외_교통사고질병외_사고부상질병외_비외상성손상의식상태구급대원1_자격구급대원2_자격운전요원_자격# duplicates
02018고양시 일산서구일산소방서주엽119안전센터2018-03-2514:29휴대전화센터2018-03-2514:302018-03-2514:340.32018-03-2514:5940대남경기도고양시 일산서구주엽동주엽동N복통<NA><NA><NA><NA>A(Alert)간호사<NA>응급구조사(2급)2