Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory742.2 KiB
Average record size in memory76.0 B

Variable types

Categorical4
Text1
Numeric2
DateTime1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15972/S/1/datasetView.do

Alerts

기관 명 has constant value ""Constant
모델명 has constant value ""Constant
등 밝기(%) is highly imbalanced (97.7%)Imbalance
불량여부(정상:0, 불량:1) is highly imbalanced (91.7%)Imbalance
위도 is highly skewed (γ1 = -84.66008626)Skewed
경도 is highly skewed (γ1 = -57.71337867)Skewed

Reproduction

Analysis started2024-05-11 16:00:32.991638
Analysis finished2024-05-11 16:00:35.226138
Duration2.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관 명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노원구 10000
100.0%

Length

2024-05-12T01:00:35.419358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-12T01:00:35.704031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노원구 10000
100.0%

모델명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
GDS-100T
10000 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGDS-100T
2nd rowGDS-100T
3rd rowGDS-100T
4th rowGDS-100T
5th rowGDS-100T

Common Values

ValueCountFrequency (%)
GDS-100T 10000
100.0%

Length

2024-05-12T01:00:36.008043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-12T01:00:36.292701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
gds-100t 10000
100.0%

시리얼
Text

Distinct4195
Distinct (%)41.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-12T01:00:37.455215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length7
Mean length7.6714
Min length7

Characters and Unicode

Total characters76714
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique995 ?
Unique (%)10.0%

Sample

1st row15-9843
2nd row12-7974
3rd row12-4933
4th row25-8216
5th row25-2824
ValueCountFrequency (%)
13-0129 7
 
0.1%
15-4166 6
 
0.1%
15-4381 6
 
0.1%
15-6954 6
 
0.1%
15-4669 6
 
0.1%
12-0911 6
 
0.1%
2019-0001124 6
 
0.1%
16-7997 6
 
0.1%
12-3493 6
 
0.1%
12-8362 6
 
0.1%
Other values (4185) 9939
99.4%
2024-05-12T01:00:39.261928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13043
17.0%
2 10474
13.7%
- 10000
13.0%
0 9721
12.7%
5 6656
8.7%
9 4973
 
6.5%
6 4796
 
6.3%
3 4520
 
5.9%
4 4306
 
5.6%
7 4224
 
5.5%
Other values (3) 4001
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66678
86.9%
Dash Punctuation 10000
 
13.0%
Lowercase Letter 36
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13043
19.6%
2 10474
15.7%
0 9721
14.6%
5 6656
10.0%
9 4973
 
7.5%
6 4796
 
7.2%
3 4520
 
6.8%
4 4306
 
6.5%
7 4224
 
6.3%
8 3965
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
l 18
50.0%
r 18
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 76678
> 99.9%
Latin 36
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13043
17.0%
2 10474
13.7%
- 10000
13.0%
0 9721
12.7%
5 6656
8.7%
9 4973
 
6.5%
6 4796
 
6.3%
3 4520
 
5.9%
4 4306
 
5.6%
7 4224
 
5.5%
Latin
ValueCountFrequency (%)
l 18
50.0%
r 18
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76714
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13043
17.0%
2 10474
13.7%
- 10000
13.0%
0 9721
12.7%
5 6656
8.7%
9 4973
 
6.5%
6 4796
 
6.3%
3 4520
 
5.9%
4 4306
 
5.6%
7 4224
 
5.5%
Other values (3) 4001
 
5.2%

위도
Real number (ℝ)

SKEWED 

Distinct3995
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.645337
Minimum31.629479
Maximum37.684206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-12T01:00:39.667331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31.629479
5-th percentile37.6189
Q137.624495
median37.649296
Q337.664129
95-th percentile37.675639
Maximum37.684206
Range6.054727
Interquartile range (IQR)0.039634

Descriptive statistics

Standard deviation0.063597526
Coefficient of variation (CV)0.0016893866
Kurtosis8008.8753
Mean37.645337
Median Absolute Deviation (MAD)0.0210275
Skewness-84.660086
Sum376453.37
Variance0.0040446453
MonotonicityNot monotonic
2024-05-12T01:00:40.085855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.622302 10
 
0.1%
37.676022 9
 
0.1%
37.666952 9
 
0.1%
37.636382 9
 
0.1%
37.623573 9
 
0.1%
37.66144 9
 
0.1%
37.620298 8
 
0.1%
37.672039 8
 
0.1%
37.657269 8
 
0.1%
37.626434 8
 
0.1%
Other values (3985) 9913
99.1%
ValueCountFrequency (%)
31.629479 1
 
< 0.1%
37.61207 3
< 0.1%
37.614475 1
 
< 0.1%
37.614544 2
< 0.1%
37.614683 2
< 0.1%
37.614823 2
< 0.1%
37.614824 4
< 0.1%
37.615128 2
< 0.1%
37.615143 3
< 0.1%
37.615261 2
< 0.1%
ValueCountFrequency (%)
37.684206 1
 
< 0.1%
37.684121 2
< 0.1%
37.683963 1
 
< 0.1%
37.683925 1
 
< 0.1%
37.683732 3
< 0.1%
37.683705 2
< 0.1%
37.68347 3
< 0.1%
37.683428 4
< 0.1%
37.683425 3
< 0.1%
37.683146 2
< 0.1%

경도
Real number (ℝ)

SKEWED 

Distinct3930
Distinct (%)39.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.04272
Minimum37.624061
Maximum127.11178
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-12T01:00:40.505607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.624061
5-th percentile127.0516
Q1127.06003
median127.0708
Q3127.0773
95-th percentile127.08531
Maximum127.11178
Range89.48772
Interquartile range (IQR)0.017265

Descriptive statistics

Standard deviation1.5491251
Coefficient of variation (CV)0.012193734
Kurtosis3329.6664
Mean127.04272
Median Absolute Deviation (MAD)0.007911
Skewness-57.713379
Sum1270427.2
Variance2.3997885
MonotonicityNot monotonic
2024-05-12T01:00:40.926757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.058309 10
 
0.1%
127.057627 9
 
0.1%
127.068972 9
 
0.1%
127.07052 9
 
0.1%
127.069653 9
 
0.1%
127.056963 8
 
0.1%
127.070306 8
 
0.1%
127.076381 8
 
0.1%
127.052667 8
 
0.1%
127.058171 8
 
0.1%
Other values (3920) 9914
99.1%
ValueCountFrequency (%)
37.6240612 3
< 0.1%
127.040071 1
 
< 0.1%
127.041928 3
< 0.1%
127.04203 1
 
< 0.1%
127.042075 2
< 0.1%
127.042219 1
 
< 0.1%
127.042411 4
< 0.1%
127.042431 2
< 0.1%
127.042596 3
< 0.1%
127.042597 4
< 0.1%
ValueCountFrequency (%)
127.111781 2
< 0.1%
127.111452 3
< 0.1%
127.111332 4
< 0.1%
127.111225 3
< 0.1%
127.111159 2
< 0.1%
127.111155 3
< 0.1%
127.11091 3
< 0.1%
127.110735 1
 
< 0.1%
127.110713 1
 
< 0.1%
127.110352 1
 
< 0.1%

등 밝기(%)
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9977 
100
 
23

Length

Max length3
Median length1
Mean length1.0046
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9977
99.8%
100 23
 
0.2%

Length

2024-05-12T01:00:41.362277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-12T01:00:41.687495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9977
99.8%
100 23
 
0.2%

불량여부(정상:0, 불량:1)
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9896 
1
 
104

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9896
99.0%
1 104
 
1.0%

Length

2024-05-12T01:00:42.002087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-12T01:00:42.295597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9896
99.0%
1 104
 
1.0%

등록일자
Date

Distinct5624
Distinct (%)56.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-03-25 00:08:41
Maximum2024-03-25 10:14:31
2024-05-12T01:00:42.614152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T01:00:43.052662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-05-12T01:00:34.036654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T01:00:33.535609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T01:00:34.289238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T01:00:33.789803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-12T01:00:43.320951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도등 밝기(%)불량여부(정상:0, 불량:1)
위도1.0000.0000.0000.000
경도0.0001.0000.0000.000
등 밝기(%)0.0000.0001.0000.556
불량여부(정상:0, 불량:1)0.0000.0000.5561.000
2024-05-12T01:00:43.568373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
불량여부(정상:0, 불량:1)등 밝기(%)
불량여부(정상:0, 불량:1)1.0000.376
등 밝기(%)0.3761.000
2024-05-12T01:00:43.809991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도등 밝기(%)불량여부(정상:0, 불량:1)
위도1.000-0.1400.0000.000
경도-0.1401.0000.0000.000
등 밝기(%)0.0000.0001.0000.376
불량여부(정상:0, 불량:1)0.0000.0000.3761.000

Missing values

2024-05-12T01:00:34.627847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-12T01:00:35.045652image/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

기관 명모델명시리얼위도경도등 밝기(%)불량여부(정상:0, 불량:1)등록일자
10547노원구GDS-100T15-984337.672675127.050998002024-03-25 04:09:39
4673노원구GDS-100T12-797437.627061127.070509002024-03-25 01:45:40
8768노원구GDS-100T12-493337.620044127.062235002024-03-25 03:14:09
16511노원구GDS-100T25-821637.669749127.079294002024-03-25 06:10:13
16787노원구GDS-100T25-282437.66959127.079328002024-03-25 06:11:22
4078노원구GDS-100T10-538537.661156127.067846002024-03-25 00:19:43
20327노원구GDS-100T21-492537.629929127.043973002024-03-25 07:13:45
9723노원구GDS-100T12-926237.618901127.058445002024-03-25 03:18:03
13613노원구GDS-100T12-449137.660018127.074423002024-03-25 05:10:15
8515노원구GDS-100T11-982137.627372127.075061002024-03-25 03:13:08
기관 명모델명시리얼위도경도등 밝기(%)불량여부(정상:0, 불량:1)등록일자
21950노원구GDS-100T12-644637.682097127.05837110012024-03-25 08:08:08
195노원구GDS-100T2019-000073137.652849127.068412002024-03-25 00:09:11
24625노원구GDS-100T15-233037.632132127.065139002024-03-25 08:19:08
12949노원구GDS-100T11-872637.618446127.074091002024-03-25 04:19:25
179노원구GDS-100T12-083937.623492127.072847002024-03-25 00:09:08
10791노원구GDS-100Tlr-000501937.622019127.089003002024-03-25 04:10:39
8669노원구GDS-100T10-516037.661299127.068932002024-03-25 03:13:46
11901노원구GDS-100T21-745337.660026127.07149002024-03-25 04:15:09
9485노원구GDS-100T12-896437.622796127.078848002024-03-25 03:17:06
19367노원구GDS-100T15-724437.67402127.057748002024-03-25 07:09:47