Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells732
Missing cells (%)1.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory644.5 KiB
Average record size in memory66.0 B

Variable types

Numeric1
Categorical5
Text1

Dataset

Description광산구 소방서 활동실적(출동구분, 행정동이름, 행정동코드 등) 현황을 제공합니다.
Author광주광역시 광산구
URLhttps://www.data.go.kr/data/15049613/fileData.do

Alerts

기준연도 has constant value ""Constant
시군구 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
출동구분 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
행정동 is highly overall correlated with 시도 and 1 other fieldsHigh correlation
시도 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
연번 is highly overall correlated with 출동구분 and 2 other fieldsHigh correlation
시도 is highly imbalanced (61.5%)Imbalance
시군구 is highly imbalanced (61.5%)Imbalance
법정동 has 732 (7.3%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:26:18.294022
Analysis finished2023-12-12 22:26:19.069760
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9635.2013
Minimum3
Maximum19220
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T07:26:19.134409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile953.95
Q14815.75
median9662
Q314420.25
95-th percentile18250.05
Maximum19220
Range19217
Interquartile range (IQR)9604.5

Descriptive statistics

Standard deviation5539.2268
Coefficient of variation (CV)0.57489477
Kurtosis-1.1958022
Mean9635.2013
Median Absolute Deviation (MAD)4804
Skewness-0.0078768217
Sum96352013
Variance30683034
MonotonicityNot monotonic
2023-12-13T07:26:19.261513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12643 1
 
< 0.1%
9854 1
 
< 0.1%
16289 1
 
< 0.1%
13344 1
 
< 0.1%
3085 1
 
< 0.1%
4146 1
 
< 0.1%
5123 1
 
< 0.1%
15645 1
 
< 0.1%
4281 1
 
< 0.1%
18060 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
3 1
< 0.1%
5 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
15 1
< 0.1%
19 1
< 0.1%
23 1
< 0.1%
26 1
< 0.1%
ValueCountFrequency (%)
19220 1
< 0.1%
19217 1
< 0.1%
19215 1
< 0.1%
19214 1
< 0.1%
19213 1
< 0.1%
19209 1
< 0.1%
19208 1
< 0.1%
19206 1
< 0.1%
19205 1
< 0.1%
19204 1
< 0.1%

기준연도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2017
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2017 10000
100.0%

Length

2023-12-13T07:26:19.410344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:26:19.489781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 10000
100.0%

출동구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
구급
8635 
생활안전
1365 

Length

Max length4
Median length2
Mean length2.273
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
구급 8635
86.4%
생활안전 1365
 
13.7%

Length

2023-12-13T07:26:19.574435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:26:19.672208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구급 8635
86.4%
생활안전 1365
 
13.7%

시도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
광주광역시
9248 
<NA>
 
752

Length

Max length5
Median length5
Mean length4.9248
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광주광역시 9248
92.5%
<NA> 752
 
7.5%

Length

2023-12-13T07:26:19.774051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:26:19.851338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광주광역시 9248
92.5%
na 752
 
7.5%

시군구
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
광산구
9248 
<NA>
 
752

Length

Max length4
Median length3
Mean length3.0752
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광산구 9248
92.5%
<NA> 752
 
7.5%

Length

2023-12-13T07:26:19.937089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:26:20.018386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광산구 9248
92.5%
na 752
 
7.5%

행정동
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수완동
1224 
우산동
1046 
첨단2동
825 
어룡동
794 
<NA>
752 
Other values (17)
5359 

Length

Max length4
Median length3
Mean length3.2811
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수완동 1224
12.2%
우산동 1046
 
10.5%
첨단2동 825
 
8.2%
어룡동 794
 
7.9%
<NA> 752
 
7.5%
하남동 629
 
6.3%
신창동 549
 
5.5%
운남동 482
 
4.8%
월곡2동 444
 
4.4%
평동 432
 
4.3%
Other values (12) 2823
28.2%

Length

2023-12-13T07:26:20.127996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수완동 1224
12.2%
우산동 1046
 
10.5%
첨단2동 825
 
8.2%
어룡동 794
 
7.9%
na 752
 
7.5%
하남동 629
 
6.3%
신창동 549
 
5.5%
운남동 482
 
4.8%
월곡2동 444
 
4.4%
평동 432
 
4.3%
Other values (12) 2823
28.2%

법정동
Text

MISSING 

Distinct78
Distinct (%)0.8%
Missing732
Missing (%)7.3%
Memory size156.2 KiB
2023-12-13T07:26:20.352557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9840311
Min length2

Characters and Unicode

Total characters27656
Distinct characters71
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row우산동
2nd row우산동
3rd row우산동
4th row고룡동
5th row신창동
ValueCountFrequency (%)
우산동 1027
 
11.1%
월계동 718
 
7.7%
신가동 705
 
7.6%
송정동 591
 
6.4%
월곡동 563
 
6.1%
수완동 544
 
5.9%
장덕동 510
 
5.5%
신창동 470
 
5.1%
운남동 466
 
5.0%
소촌동 387
 
4.2%
Other values (68) 3287
35.5%
2023-12-13T07:26:20.674724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 9317
33.7%
산 2104
 
7.6%
월 1604
 
5.8%
신 1332
 
4.8%
우 1027
 
3.7%
정 974
 
3.5%
수 756
 
2.7%
계 729
 
2.6%
가 705
 
2.5%
송 669
 
2.4%
Other values (61) 8439
30.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27656
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 9317
33.7%
산 2104
 
7.6%
월 1604
 
5.8%
신 1332
 
4.8%
우 1027
 
3.7%
정 974
 
3.5%
수 756
 
2.7%
계 729
 
2.6%
가 705
 
2.5%
송 669
 
2.4%
Other values (61) 8439
30.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27656
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 9317
33.7%
산 2104
 
7.6%
월 1604
 
5.8%
신 1332
 
4.8%
우 1027
 
3.7%
정 974
 
3.5%
수 756
 
2.7%
계 729
 
2.6%
가 705
 
2.5%
송 669
 
2.4%
Other values (61) 8439
30.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27656
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 9317
33.7%
산 2104
 
7.6%
월 1604
 
5.8%
신 1332
 
4.8%
우 1027
 
3.7%
정 974
 
3.5%
수 756
 
2.7%
계 729
 
2.6%
가 705
 
2.5%
송 669
 
2.4%
Other values (61) 8439
30.5%

Interactions

2023-12-13T07:26:18.793952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:26:20.759060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번출동구분행정동법정동
연번1.0000.9850.1780.260
출동구분0.9851.0000.1450.212
행정동0.1780.1451.0000.994
법정동0.2600.2120.9941.000
2023-12-13T07:26:20.849570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구출동구분행정동시도
시군구1.0001.0001.0001.000
출동구분1.0001.0000.1271.000
행정동1.0000.1271.0001.000
시도1.0001.0001.0001.000
2023-12-13T07:26:20.934175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번출동구분시도시군구행정동
연번1.0000.8941.0001.0000.066
출동구분0.8941.0001.0001.0000.127
시도1.0001.0001.0001.0001.000
시군구1.0001.0001.0001.0001.000
행정동0.0660.1271.0001.0001.000

Missing values

2023-12-13T07:26:18.904883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:26:19.010804image/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

연번기준연도출동구분시도시군구행정동법정동
12642126432017구급광주광역시광산구우산동우산동
471047112017구급<NA><NA><NA><NA>
13631136322017구급광주광역시광산구우산동우산동
694369442017구급광주광역시광산구우산동우산동
456145622017구급광주광역시광산구임곡동고룡동
694569462017구급광주광역시광산구신창동신창동
524052412017구급광주광역시광산구첨단2동월계동
17182171832017생활안전광주광역시광산구평동월전동
241524162017구급광주광역시광산구첨단2동월계동
15208152092017구급광주광역시광산구하남동산정동
연번기준연도출동구분시도시군구행정동법정동
346534662017구급광주광역시광산구수완동수완동
669266932017구급광주광역시광산구우산동우산동
14884148852017구급광주광역시광산구하남동장덕동
625962602017구급광주광역시광산구어룡동박호동
977797782017구급광주광역시광산구신가동신가동
983498352017구급광주광역시광산구첨단1동쌍암동
14761147622017구급광주광역시광산구첨단2동월계동
108710882017구급광주광역시광산구우산동우산동
18687186882017생활안전광주광역시광산구신창동수완동
12259122602017구급광주광역시광산구수완동장덕동