Overview

Dataset statistics

Number of variables4
Number of observations133
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory36.0 B

Variable types

Numeric3
Text1

Dataset

Description인천광역시 UTIS시스템에 등록된 RSE 정보(RSE ID, 설치위치, 위도, 경도)를 제공하고 있는 데이터 입니다.
Author인천광역시
URLhttps://www.data.go.kr/data/15089909/fileData.do

Alerts

아이디(알에스이) has unique valuesUnique
설치위치 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:33:13.282725
Analysis finished2023-12-12 21:33:14.340940
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아이디(알에스이)
Real number (ℝ)

UNIQUE 

Distinct133
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4382553 × 1016
Minimum1.002161 × 1016
Maximum3.0021681 × 1016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T06:33:14.409643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.002161 × 1016
5-th percentile1.0021626 × 1016
Q11.002164 × 1016
median1.0021651 × 1016
Q31.002168 × 1016
95-th percentile3.0021681 × 1016
Maximum3.0021681 × 1016
Range2.0000071 × 1016
Interquartile range (IQR)4.03 × 1010

Descriptive statistics

Standard deviation8.2895921 × 1015
Coefficient of variation (CV)0.57636445
Kurtosis-0.093654824
Mean1.4382553 × 1016
Median Absolute Deviation (MAD)2.0449 × 1010
Skewness1.3812971
Sum1.9128795 × 1018
Variance6.8717338 × 1031
MonotonicityNot monotonic
2023-12-13T06:33:14.565534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10021660391000039 1
 
0.8%
10021650240000024 1
 
0.8%
10021650330000033 1
 
0.8%
10021650321000032 1
 
0.8%
10021650320000032 1
 
0.8%
10021650310000031 1
 
0.8%
10021650301000030 1
 
0.8%
10021650300000030 1
 
0.8%
10021650291000029 1
 
0.8%
10021650290000029 1
 
0.8%
Other values (123) 123
92.5%
ValueCountFrequency (%)
10021610010000001 1
0.8%
10021610019999999 1
0.8%
10021610020000002 1
0.8%
10021610021000002 1
0.8%
10021610030000003 1
0.8%
10021610031000003 1
0.8%
10021620120000012 1
0.8%
10021630040000004 1
0.8%
10021630050000005 1
0.8%
10021630051000005 1
0.8%
ValueCountFrequency (%)
30021680880001023 1
0.8%
30021680870001022 1
0.8%
30021680730001008 1
0.8%
30021680721001007 1
0.8%
30021680720001007 1
0.8%
30021680710001006 1
0.8%
30021680700001005 1
0.8%
30021680690001004 1
0.8%
30021680681001003 1
0.8%
30021680680001003 1
0.8%

설치위치
Text

UNIQUE 

Distinct133
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T06:33:14.861181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.556391
Min length3

Characters and Unicode

Total characters739
Distinct characters201
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique133 ?
Unique (%)100.0%

Sample

1st row부평4R
2nd row도화4R300m
3rd row먼우금4R
4th row신공항영업소
5th row문화회관4R
ValueCountFrequency (%)
부평4r 1
 
0.8%
문학산터널 1
 
0.8%
남동구청4r 1
 
0.8%
독곡4r 1
 
0.8%
장승배기4r 1
 
0.8%
장수지하차도4r 1
 
0.8%
만수4r300m 1
 
0.8%
만수4r 1
 
0.8%
간석4r500m 1
 
0.8%
간석4r 1
 
0.8%
Other values (123) 123
92.5%
2023-12-13T06:33:15.344570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 94
 
12.7%
4 80
 
10.8%
0 15
 
2.0%
동 13
 
1.8%
학 12
 
1.6%
수 11
 
1.5%
3 11
 
1.5%
C 11
 
1.5%
부 10
 
1.4%
장 10
 
1.4%
Other values (191) 472
63.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 450
60.9%
Uppercase Letter 134
 
18.1%
Decimal Number 121
 
16.4%
Lowercase Letter 15
 
2.0%
Other Punctuation 8
 
1.1%
Connector Punctuation 5
 
0.7%
Dash Punctuation 4
 
0.5%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 13
 
2.9%
학 12
 
2.7%
수 11
 
2.4%
부 10
 
2.2%
장 10
 
2.2%
구 9
 
2.0%
역 9
 
2.0%
인 9
 
2.0%
기 9
 
2.0%
천 8
 
1.8%
Other values (160) 350
77.8%
Uppercase Letter
ValueCountFrequency (%)
R 94
70.1%
C 11
 
8.2%
I 9
 
6.7%
T 5
 
3.7%
E 3
 
2.2%
A 2
 
1.5%
J 2
 
1.5%
S 2
 
1.5%
G 2
 
1.5%
P 1
 
0.7%
Other values (3) 3
 
2.2%
Decimal Number
ValueCountFrequency (%)
4 80
66.1%
0 15
 
12.4%
3 11
 
9.1%
5 10
 
8.3%
1 3
 
2.5%
2 2
 
1.7%
Lowercase Letter
ValueCountFrequency (%)
m 9
60.0%
t 2
 
13.3%
s 1
 
6.7%
e 1
 
6.7%
p 1
 
6.7%
j 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 7
87.5%
/ 1
 
12.5%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 450
60.9%
Latin 149
 
20.2%
Common 140
 
18.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 13
 
2.9%
학 12
 
2.7%
수 11
 
2.4%
부 10
 
2.2%
장 10
 
2.2%
구 9
 
2.0%
역 9
 
2.0%
인 9
 
2.0%
기 9
 
2.0%
천 8
 
1.8%
Other values (160) 350
77.8%
Latin
ValueCountFrequency (%)
R 94
63.1%
C 11
 
7.4%
I 9
 
6.0%
m 9
 
6.0%
T 5
 
3.4%
E 3
 
2.0%
A 2
 
1.3%
t 2
 
1.3%
J 2
 
1.3%
S 2
 
1.3%
Other values (9) 10
 
6.7%
Common
ValueCountFrequency (%)
4 80
57.1%
0 15
 
10.7%
3 11
 
7.9%
5 10
 
7.1%
. 7
 
5.0%
_ 5
 
3.6%
- 4
 
2.9%
1 3
 
2.1%
2 2
 
1.4%
/ 1
 
0.7%
Other values (2) 2
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 450
60.9%
ASCII 289
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R 94
32.5%
4 80
27.7%
0 15
 
5.2%
3 11
 
3.8%
C 11
 
3.8%
5 10
 
3.5%
I 9
 
3.1%
m 9
 
3.1%
. 7
 
2.4%
_ 5
 
1.7%
Other values (21) 38
13.1%
Hangul
ValueCountFrequency (%)
동 13
 
2.9%
학 12
 
2.7%
수 11
 
2.4%
부 10
 
2.2%
장 10
 
2.2%
구 9
 
2.0%
역 9
 
2.0%
인 9
 
2.0%
기 9
 
2.0%
천 8
 
1.8%
Other values (160) 350
77.8%

위도
Real number (ℝ)

Distinct131
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean125.74017
Minimum0
Maximum126.84493
Zeros1
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T06:33:15.806437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile126.63285
Q1126.66673
median126.69016
Q3126.72173
95-th percentile126.74564
Maximum126.84493
Range126.84493
Interquartile range (IQR)0.055001

Descriptive statistics

Standard deviation10.985716
Coefficient of variation (CV)0.087368386
Kurtosis132.99696
Mean125.74017
Median Absolute Deviation (MAD)0.028633
Skewness-11.532366
Sum16723.443
Variance120.68595
MonotonicityNot monotonic
2023-12-13T06:33:15.971726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.683069 2
 
1.5%
126.6892086 2
 
1.5%
126.733325 1
 
0.8%
126.7073753 1
 
0.8%
126.7089867 1
 
0.8%
126.7076489 1
 
0.8%
126.7199681 1
 
0.8%
126.7257813 1
 
0.8%
126.7361893 1
 
0.8%
126.7106418 1
 
0.8%
Other values (121) 121
91.0%
ValueCountFrequency (%)
0.0 1
0.8%
126.6250356 1
0.8%
126.6274719 1
0.8%
126.6309271 1
0.8%
126.6310216 1
0.8%
126.6311612 1
0.8%
126.6316274 1
0.8%
126.6336695 1
0.8%
126.6353372 1
0.8%
126.6354441 1
0.8%
ValueCountFrequency (%)
126.844933 1
0.8%
126.7533072 1
0.8%
126.7531028 1
0.8%
126.7525693 1
0.8%
126.7515057 1
0.8%
126.7470423 1
0.8%
126.745727 1
0.8%
126.7455835 1
0.8%
126.7401894 1
0.8%
126.739451 1
0.8%

경도
Real number (ℝ)

Distinct131
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.186865
Minimum0
Maximum37.575729
Zeros1
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T06:33:16.129423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile37.396583
Q137.438566
median37.460771
Q337.498801
95-th percentile37.551745
Maximum37.575729
Range37.575729
Interquartile range (IQR)0.0602352

Descriptive statistics

Standard deviation3.2492646
Coefficient of variation (CV)0.087376675
Kurtosis132.94535
Mean37.186865
Median Absolute Deviation (MAD)0.0273739
Skewness-11.529034
Sum4945.853
Variance10.55772
MonotonicityNot monotonic
2023-12-13T06:33:16.271238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4076845 2
 
1.5%
37.45768 2
 
1.5%
37.4548809 1
 
0.8%
37.4499085 1
 
0.8%
37.4570849 1
 
0.8%
37.4670194 1
 
0.8%
37.4609532 1
 
0.8%
37.4602046 1
 
0.8%
37.4527243 1
 
0.8%
37.4792053 1
 
0.8%
Other values (121) 121
91.0%
ValueCountFrequency (%)
0.0 1
0.8%
37.314449 1
0.8%
37.3875759 1
0.8%
37.3911499 1
0.8%
37.3922476 1
0.8%
37.3923292 1
0.8%
37.3959598 1
0.8%
37.3969987 1
0.8%
37.4001706 1
0.8%
37.4044995 1
0.8%
ValueCountFrequency (%)
37.5757293 1
0.8%
37.5709121 1
0.8%
37.5699385 1
0.8%
37.5696229 1
0.8%
37.5582209 1
0.8%
37.552873 1
0.8%
37.5524594 1
0.8%
37.551269 1
0.8%
37.5463355 1
0.8%
37.545554 1
0.8%

Interactions

2023-12-13T06:33:13.952678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:33:13.427604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:33:13.697422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:33:14.042587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:33:13.530396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:33:13.796448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:33:14.129250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:33:13.613672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:33:13.876687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:33:16.365316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아이디(알에스이)위도경도
아이디(알에스이)1.0000.0000.000
위도0.0001.0000.696
경도0.0000.6961.000
2023-12-13T06:33:16.450911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아이디(알에스이)위도경도
아이디(알에스이)1.0000.1870.412
위도0.1871.0000.181
경도0.4120.1811.000

Missing values

2023-12-13T06:33:14.236017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:33:14.313459image/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

아이디(알에스이)설치위치위도경도
010021660391000039부평4R126.71064237.479205
110021630131000013도화4R300m126.67289637.46104
230021640820001017먼우금4R126.67563537.413476
330021680880001023신공항영업소126.66363937.569623
410021650350000035문화회관4R126.70146537.450309
510021610010000001동인천역126.63092737.475244
610021660380000038부평역5R126.7233737.491242
710021660381000038시장오거리126.72657137.494329
810021660400000040부개4R126.73917537.486325
910021660401000040부개4R150m126.73815937.486879
아이디(알에스이)설치위치위도경도
12310021650610000061안말4R126.69227137.396999
12410021650611000061대한특수금속입구126.69463337.400171
12510021660650000065구산4R126.75330737.48356
12610021630751000075공설운동장측면126.64393637.464393
12710021650620000062벗말4R126.70327437.412677
12810021650621000062중소기업청4R126.70143737.409335
12910021650630000063남동I/C유출로126.71852737.434089
13010021650640000064서창JCT126.73665337.433397
13130021660010000003jmptest0.00.0
13210021610019999999ENARU-TEST126.84493337.314449