Overview

Dataset statistics

Number of variables5
Number of observations210
Missing cells35
Missing cells (%)3.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.2 KiB
Average record size in memory44.6 B

Variable types

DateTime1
Numeric4

Dataset

Description대구광역시_소방 긴급구조 월간 화재활동 집계 * 본 자료는 긴급구조표준시스템에서 추출한 자료로 일부 데이터에 오류가 있을 수 있으며 참고용으로만 활용가능 * 오류 없는 정밀한 데이터를 확인하기 위해서는 관련부서로 문의 필요
URLhttps://www.data.go.kr/data/15117288/fileData.do

Alerts

신고접수건수 is highly overall correlated with 화재출동건수 and 1 other fieldsHigh correlation
화재출동건수 is highly overall correlated with 신고접수건수 and 2 other fieldsHigh correlation
화재처리건수 is highly overall correlated with 신고접수건수 and 2 other fieldsHigh correlation
구조인원수 is highly overall correlated with 화재출동건수 and 1 other fieldsHigh correlation
화재처리건수 has 26 (12.4%) missing valuesMissing
구조인원수 has 9 (4.3%) missing valuesMissing
신고접수건수 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:00:54.085011
Analysis finished2023-12-12 13:00:56.501017
Duration2.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년월
Date

Distinct193
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2005-01-01 00:00:00
Maximum2023-06-01 00:00:00
2023-12-12T22:00:56.577310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:00:56.739587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

신고접수건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct210
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76356.19
Minimum29528
Maximum846270
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T22:00:56.938628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum29528
5-th percentile32770
Q135696.75
median40456.5
Q351838.25
95-th percentile416125.85
Maximum846270
Range816742
Interquartile range (IQR)16141.5

Descriptive statistics

Standard deviation122579.05
Coefficient of variation (CV)1.6053584
Kurtosis15.598555
Mean76356.19
Median Absolute Deviation (MAD)5214.5
Skewness3.8891316
Sum16034800
Variance1.5025623 × 1010
MonotonicityNot monotonic
2023-12-12T22:00:57.130929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
73066 1
 
0.5%
41899 1
 
0.5%
62138 1
 
0.5%
39599 1
 
0.5%
41455 1
 
0.5%
31050 1
 
0.5%
40145 1
 
0.5%
33361 1
 
0.5%
34254 1
 
0.5%
36110 1
 
0.5%
Other values (200) 200
95.2%
ValueCountFrequency (%)
29528 1
0.5%
30955 1
0.5%
31050 1
0.5%
31720 1
0.5%
32021 1
0.5%
32123 1
0.5%
32322 1
0.5%
32350 1
0.5%
32473 1
0.5%
32514 1
0.5%
ValueCountFrequency (%)
846270 1
0.5%
746256 1
0.5%
605932 1
0.5%
499122 1
0.5%
490234 1
0.5%
486302 1
0.5%
486234 1
0.5%
476839 1
0.5%
442836 1
0.5%
436540 1
0.5%

화재출동건수
Real number (ℝ)

HIGH CORRELATION 

Distinct150
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean425.20476
Minimum15
Maximum4657
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T22:00:57.351428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile25
Q147
median320
Q3393.25
95-th percentile1072.4
Maximum4657
Range4642
Interquartile range (IQR)346.25

Descriptive statistics

Standard deviation787.36038
Coefficient of variation (CV)1.8517205
Kurtosis17.057096
Mean425.20476
Median Absolute Deviation (MAD)119
Skewness4.1573479
Sum89293
Variance619936.36
MonotonicityNot monotonic
2023-12-12T22:00:57.540222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46 5
 
2.4%
25 5
 
2.4%
31 4
 
1.9%
34 3
 
1.4%
39 3
 
1.4%
343 3
 
1.4%
44 3
 
1.4%
40 3
 
1.4%
315 3
 
1.4%
332 3
 
1.4%
Other values (140) 175
83.3%
ValueCountFrequency (%)
15 1
 
0.5%
18 2
 
1.0%
21 1
 
0.5%
22 2
 
1.0%
23 2
 
1.0%
25 5
2.4%
26 1
 
0.5%
27 1
 
0.5%
29 2
 
1.0%
30 1
 
0.5%
ValueCountFrequency (%)
4657 1
0.5%
4352 1
0.5%
4294 1
0.5%
4283 1
0.5%
4195 1
0.5%
3806 1
0.5%
3487 1
0.5%
3431 1
0.5%
3154 1
0.5%
1885 1
0.5%

화재처리건수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct115
Distinct (%)62.5%
Missing26
Missing (%)12.4%
Infinite0
Infinite (%)0.0%
Mean182.51087
Minimum14
Maximum1961
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T22:00:57.742095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile19
Q160
median121.5
Q3149.5
95-th percentile633.1
Maximum1961
Range1947
Interquartile range (IQR)89.5

Descriptive statistics

Standard deviation324.15228
Coefficient of variation (CV)1.7760711
Kurtosis17.203129
Mean182.51087
Median Absolute Deviation (MAD)40.5
Skewness4.1720803
Sum33582
Variance105074.7
MonotonicityNot monotonic
2023-12-12T22:00:57.925506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23 6
 
2.9%
98 4
 
1.9%
138 4
 
1.9%
180 4
 
1.9%
121 3
 
1.4%
32 3
 
1.4%
125 3
 
1.4%
19 3
 
1.4%
141 3
 
1.4%
21 3
 
1.4%
Other values (105) 148
70.5%
(Missing) 26
 
12.4%
ValueCountFrequency (%)
14 1
 
0.5%
15 2
 
1.0%
16 2
 
1.0%
17 1
 
0.5%
18 3
1.4%
19 3
1.4%
20 2
 
1.0%
21 3
1.4%
22 1
 
0.5%
23 6
2.9%
ValueCountFrequency (%)
1961 1
0.5%
1740 1
0.5%
1731 1
0.5%
1722 1
0.5%
1665 1
0.5%
1564 1
0.5%
1522 1
0.5%
1022 1
0.5%
671 1
0.5%
652 1
0.5%

구조인원수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct161
Distinct (%)80.1%
Missing9
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean553.41294
Minimum91
Maximum6609
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T22:00:58.090384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum91
5-th percentile138
Q1181
median290
Q3389
95-th percentile2113
Maximum6609
Range6518
Interquartile range (IQR)208

Descriptive statistics

Standard deviation971.58442
Coefficient of variation (CV)1.7556229
Kurtosis20.634245
Mean553.41294
Median Absolute Deviation (MAD)108
Skewness4.3379159
Sum111236
Variance943976.29
MonotonicityNot monotonic
2023-12-12T22:00:58.236020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
337 4
 
1.9%
212 3
 
1.4%
325 3
 
1.4%
298 3
 
1.4%
155 3
 
1.4%
202 3
 
1.4%
297 2
 
1.0%
194 2
 
1.0%
346 2
 
1.0%
352 2
 
1.0%
Other values (151) 174
82.9%
(Missing) 9
 
4.3%
ValueCountFrequency (%)
91 1
0.5%
95 1
0.5%
97 1
0.5%
121 1
0.5%
122 1
0.5%
123 1
0.5%
124 1
0.5%
127 2
1.0%
133 1
0.5%
138 1
0.5%
ValueCountFrequency (%)
6609 1
0.5%
6504 1
0.5%
5682 1
0.5%
4942 1
0.5%
4675 1
0.5%
3013 1
0.5%
2915 1
0.5%
2624 1
0.5%
2584 1
0.5%
2493 1
0.5%

Interactions

2023-12-12T22:00:55.735574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:00:54.216606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:00:54.664681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:00:55.024980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:00:55.832418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:00:54.330122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:00:54.755999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:00:55.139313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:00:55.922184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:00:54.448405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:00:54.843680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:00:55.230230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:00:56.059140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:00:54.572937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:00:54.937772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:00:55.339562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:00:58.346122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신고접수건수화재출동건수화재처리건수구조인원수
신고접수건수1.0000.9020.9160.822
화재출동건수0.9021.0000.9570.897
화재처리건수0.9160.9571.0000.937
구조인원수0.8220.8970.9371.000
2023-12-12T22:00:58.471663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신고접수건수화재출동건수화재처리건수구조인원수
신고접수건수1.0000.5580.5700.435
화재출동건수0.5581.0000.7530.691
화재처리건수0.5700.7531.0000.540
구조인원수0.4350.6910.5401.000

Missing values

2023-12-12T22:00:56.217860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:00:56.333549image/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.
2023-12-12T22:00:56.438145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

집계년월신고접수건수화재출동건수화재처리건수구조인원수
02012-01-0173066417181208
12016-06-0135500254124392
22011-09-0183359366129371
32011-12-0175430405179220
42011-11-0173492293106184
52011-10-0177989354136202
62011-08-0183707298126345
72011-07-0181137341119270
82011-06-0171885347149205
92011-05-0168848381177212
집계년월신고접수건수화재출동건수화재처리건수구조인원수
2002020-01-0139351394110308
2012020-05-0142707418100341
2022020-07-014767545687416
2032022-01-0136106375133337
2042022-12-0140226388112<NA>
2052023-05-015216852598<NA>
2062023-01-0137997412111<NA>
2072022-01-011676611463441337
2082023-04-0142608494121<NA>
2092023-02-0131720373123<NA>