Overview

Dataset statistics

Number of variables5
Number of observations258
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.0 KiB
Average record size in memory43.5 B

Variable types

Numeric3
Text2

Dataset

Description순번,서소코드,서소이름,위도,경도
Author서울종합방재센터 전산통신과
URLhttps://data.seoul.go.kr/dataList/OA-12518/S/1/datasetView.do

Alerts

순번 has unique valuesUnique
서소이름 has unique valuesUnique

Reproduction

Analysis started2023-12-11 10:13:30.062174
Analysis finished2023-12-11 10:13:31.255150
Duration1.19 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct258
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.5
Minimum1
Maximum258
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T19:13:31.328993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.85
Q165.25
median129.5
Q3193.75
95-th percentile245.15
Maximum258
Range257
Interquartile range (IQR)128.5

Descriptive statistics

Standard deviation74.622383
Coefficient of variation (CV)0.57623462
Kurtosis-1.2
Mean129.5
Median Absolute Deviation (MAD)64.5
Skewness0
Sum33411
Variance5568.5
MonotonicityNot monotonic
2023-12-11T19:13:31.511789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
118 1
 
0.4%
96 1
 
0.4%
97 1
 
0.4%
98 1
 
0.4%
99 1
 
0.4%
100 1
 
0.4%
7 1
 
0.4%
16 1
 
0.4%
26 1
 
0.4%
Other values (248) 248
96.1%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
258 1
0.4%
257 1
0.4%
256 1
0.4%
255 1
0.4%
254 1
0.4%
253 1
0.4%
252 1
0.4%
251 1
0.4%
250 1
0.4%
249 1
0.4%

서소코드
Text

Distinct168
Distinct (%)65.1%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-11T19:13:31.847853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters1290
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)64.3%

Sample

1st row77250
2nd row77280
3rd row75251
4th row81254
5th row92280
ValueCountFrequency (%)
kk119 78
30.2%
ic119 14
 
5.4%
74250 1
 
0.4%
79252 1
 
0.4%
77250 1
 
0.4%
80280 1
 
0.4%
85250 1
 
0.4%
85252 1
 
0.4%
85256 1
 
0.4%
76253 1
 
0.4%
Other values (158) 158
61.2%
2023-12-11T19:13:32.366268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 232
18.0%
2 203
15.7%
K 156
12.1%
5 142
11.0%
9 135
10.5%
8 110
8.5%
7 84
 
6.5%
3 67
 
5.2%
0 65
 
5.0%
6 40
 
3.1%
Other values (3) 56
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1106
85.7%
Uppercase Letter 184
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 232
21.0%
2 203
18.4%
5 142
12.8%
9 135
12.2%
8 110
9.9%
7 84
 
7.6%
3 67
 
6.1%
0 65
 
5.9%
6 40
 
3.6%
4 28
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
K 156
84.8%
I 14
 
7.6%
C 14
 
7.6%

Most occurring scripts

ValueCountFrequency (%)
Common 1106
85.7%
Latin 184
 
14.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 232
21.0%
2 203
18.4%
5 142
12.8%
9 135
12.2%
8 110
9.9%
7 84
 
7.6%
3 67
 
6.1%
0 65
 
5.9%
6 40
 
3.6%
4 28
 
2.5%
Latin
ValueCountFrequency (%)
K 156
84.8%
I 14
 
7.6%
C 14
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 232
18.0%
2 203
15.7%
K 156
12.1%
5 142
11.0%
9 135
10.5%
8 110
8.5%
7 84
 
6.5%
3 67
 
5.2%
0 65
 
5.0%
6 40
 
3.1%
Other values (3) 56
 
4.3%

서소이름
Text

UNIQUE 

Distinct258
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-11T19:13:32.654714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.2984496
Min length5

Characters and Unicode

Total characters2141
Distinct characters178
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique258 ?
Unique (%)100.0%

Sample

1st row종암119안전센터
2nd row성북119구조대
3rd row청량리119안전센터
4th row개화119안전센터
5th row서대문119구조대
ValueCountFrequency (%)
종암119안전센터 1
 
0.4%
구로119구조대 1
 
0.4%
반포119안전센터 1
 
0.4%
한강로119안전센터 1
 
0.4%
서초119구조대 1
 
0.4%
구로소방서 1
 
0.4%
고일119안전센터 1
 
0.4%
고척119안전센터 1
 
0.4%
신도림119안전센터 1
 
0.4%
대림119안전센터 1
 
0.4%
Other values (248) 248
96.1%
2023-12-11T19:13:33.081894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 462
21.6%
9 231
 
10.8%
안 125
 
5.8%
전 118
 
5.5%
센 115
 
5.4%
터 115
 
5.4%
- 92
 
4.3%
구 36
 
1.7%
서 36
 
1.7%
대 34
 
1.6%
Other values (168) 777
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1356
63.3%
Decimal Number 693
32.4%
Dash Punctuation 92
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 125
 
9.2%
전 118
 
8.7%
센 115
 
8.5%
터 115
 
8.5%
구 36
 
2.7%
서 36
 
2.7%
대 34
 
2.5%
양 34
 
2.5%
부 28
 
2.1%
방 28
 
2.1%
Other values (165) 687
50.7%
Decimal Number
ValueCountFrequency (%)
1 462
66.7%
9 231
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1356
63.3%
Common 785
36.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 125
 
9.2%
전 118
 
8.7%
센 115
 
8.5%
터 115
 
8.5%
구 36
 
2.7%
서 36
 
2.7%
대 34
 
2.5%
양 34
 
2.5%
부 28
 
2.1%
방 28
 
2.1%
Other values (165) 687
50.7%
Common
ValueCountFrequency (%)
1 462
58.9%
9 231
29.4%
- 92
 
11.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1356
63.3%
ASCII 785
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 462
58.9%
9 231
29.4%
- 92
 
11.7%
Hangul
ValueCountFrequency (%)
안 125
 
9.2%
전 118
 
8.7%
센 115
 
8.5%
터 115
 
8.5%
구 36
 
2.7%
서 36
 
2.7%
대 34
 
2.5%
양 34
 
2.5%
부 28
 
2.1%
방 28
 
2.1%
Other values (165) 687
50.7%

위도
Real number (ℝ)

Distinct252
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.548195
Minimum37.327795
Maximum37.901744
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T19:13:33.238250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.327795
5-th percentile37.392719
Q137.495879
median37.54328
Q337.602014
95-th percentile37.690907
Maximum37.901744
Range0.5739485
Interquartile range (IQR)0.10613498

Descriptive statistics

Standard deviation0.089553732
Coefficient of variation (CV)0.0023850343
Kurtosis1.3367088
Mean37.548195
Median Absolute Deviation (MAD)0.0490946
Skewness0.44776736
Sum9687.4343
Variance0.0080198709
MonotonicityNot monotonic
2023-12-11T19:13:33.433316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5580018 2
 
0.8%
37.638098 2
 
0.8%
37.4984222 2
 
0.8%
37.5649557 2
 
0.8%
37.4997892 2
 
0.8%
37.6639697 2
 
0.8%
37.5341185 1
 
0.4%
37.3519239 1
 
0.4%
37.4090702 1
 
0.4%
37.7110876 1
 
0.4%
Other values (242) 242
93.8%
ValueCountFrequency (%)
37.327795 1
0.4%
37.3356055 1
0.4%
37.3442446 1
0.4%
37.3495551 1
0.4%
37.3519239 1
0.4%
37.3563412 1
0.4%
37.3674044 1
0.4%
37.3723134 1
0.4%
37.3818589 1
0.4%
37.3819485 1
0.4%
ValueCountFrequency (%)
37.9017435 1
0.4%
37.8462209 1
0.4%
37.8235123 1
0.4%
37.8019985 1
0.4%
37.7958862 1
0.4%
37.7494209 1
0.4%
37.7398442 1
0.4%
37.7371907 1
0.4%
37.7276416 1
0.4%
37.7207892 1
0.4%

경도
Real number (ℝ)

Distinct251
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.96462
Minimum126.59668
Maximum127.3048
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T19:13:33.613577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.59668
5-th percentile126.72785
Q1126.87814
median126.97837
Q3127.06405
95-th percentile127.14863
Maximum127.3048
Range0.7081209
Interquartile range (IQR)0.18591373

Descriptive statistics

Standard deviation0.13277038
Coefficient of variation (CV)0.0010457274
Kurtosis-0.38931929
Mean126.96462
Median Absolute Deviation (MAD)0.08841235
Skewness-0.33617291
Sum32756.873
Variance0.017627975
MonotonicityNot monotonic
2023-12-11T19:13:33.762375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0711823 3
 
1.2%
126.8603443 2
 
0.8%
127.0154527 2
 
0.8%
127.0667838 2
 
0.8%
127.1425858 2
 
0.8%
126.9918713 2
 
0.8%
126.9716499 1
 
0.4%
127.0481594 1
 
0.4%
126.8931941 1
 
0.4%
127.0612331 1
 
0.4%
Other values (241) 241
93.4%
ValueCountFrequency (%)
126.5966767 1
0.4%
126.6223303 1
0.4%
126.6377807 1
0.4%
126.697229 1
0.4%
126.7022879 1
0.4%
126.7030508 1
0.4%
126.7063211 1
0.4%
126.7064474 1
0.4%
126.7085145 1
0.4%
126.7164588 1
0.4%
ValueCountFrequency (%)
127.3047976 1
0.4%
127.2322829 1
0.4%
127.2203846 1
0.4%
127.2161681 1
0.4%
127.2056557 1
0.4%
127.204397 1
0.4%
127.1904248 1
0.4%
127.1802101 1
0.4%
127.168971 1
0.4%
127.1675222 1
0.4%

Interactions

2023-12-11T19:13:30.817790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:13:30.255012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:13:30.538461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:13:30.907339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:13:30.341585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:13:30.638300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:13:31.021604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:13:30.446107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:13:30.726097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T19:13:33.864157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번위도경도
순번1.0000.5730.468
위도0.5731.0000.511
경도0.4680.5111.000
2023-12-11T19:13:33.948422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번위도경도
순번1.0000.0210.074
위도0.0211.0000.171
경도0.0740.1711.000

Missing values

2023-12-11T19:13:31.134009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T19:13:31.219254image/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

순번서소코드서소이름위도경도
0177250종암119안전센터37.602489127.031563
1277280성북119구조대37.602308127.03178
2375251청량리119안전센터37.587182127.0524
3481254개화119안전센터37.574919126.803238
4592280서대문119구조대37.571827126.93457
5692236서대문소방서37.573334126.93598
6891236동작소방서37.494631126.917764
7991250동작119안전센터37.494622126.917662
81091280동작119구조대37.49458126.917697
91173254금호119안전센터37.554023127.024337
순번서소코드서소이름위도경도
248254KK119남양주-와부11937.585819127.216168
249255KK119의왕-오전11937.356341126.968534
25025682236강동소방서37.52926127.124969
25125782252고덕119안전센터37.557221127.152074
25225890253중화119안전센터37.600476127.079319
25320188254운동장119안전센터37.513897127.071149
254211KK119양주-백석11937.795886126.989491
25522077236성북소방서37.602362127.031667
25622985253구로119안전센터37.494224126.882575
25723881251화곡119안전센터37.543647126.845254