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 (96.0%)Imbalance
불량여부(정상:0, 불량:1) is highly imbalanced (91.3%)Imbalance
위도 is highly skewed (γ1 = -64.54709986)Skewed
경도 is highly skewed (γ1 = -70.68677851)Skewed

Reproduction

Analysis started2024-05-04 00:43:55.335423
Analysis finished2024-05-04 00:43:58.600565
Duration3.27 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

2024-05-04T00:43:58.890538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:43:59.155479image/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

2024-05-04T00:43:59.534070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:43:59.867282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
gds-100t 10000
100.0%

시리얼
Text

Distinct4180
Distinct (%)41.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T00:44:00.546937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length7
Mean length7.6793
Min length7

Characters and Unicode

Total characters76793
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

Unique1035 ?
Unique (%)10.3%

Sample

1st row25-4874
2nd row16-6064
3rd row15-5409
4th row11-9938
5th row25-8503
ValueCountFrequency (%)
21-5411 7
 
0.1%
21-7363 7
 
0.1%
2019-0000520 7
 
0.1%
21-7867 7
 
0.1%
22-0469 7
 
0.1%
16-5298 7
 
0.1%
2019-0001267 6
 
0.1%
21-5008 6
 
0.1%
20-9857 6
 
0.1%
12-0550 6
 
0.1%
Other values (4170) 9934
99.3%
2024-05-04T00:44:01.779195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12815
16.7%
2 10604
13.8%
- 10000
13.0%
0 9850
12.8%
5 6607
8.6%
9 5113
 
6.7%
6 4683
 
6.1%
3 4419
 
5.8%
4 4405
 
5.7%
7 4249
 
5.5%
Other values (3) 4048
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66741
86.9%
Dash Punctuation 10000
 
13.0%
Lowercase Letter 52
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12815
19.2%
2 10604
15.9%
0 9850
14.8%
5 6607
9.9%
9 5113
 
7.7%
6 4683
 
7.0%
3 4419
 
6.6%
4 4405
 
6.6%
7 4249
 
6.4%
8 3996
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
l 26
50.0%
r 26
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 76741
99.9%
Latin 52
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12815
16.7%
2 10604
13.8%
- 10000
13.0%
0 9850
12.8%
5 6607
8.6%
9 5113
 
6.7%
6 4683
 
6.1%
3 4419
 
5.8%
4 4405
 
5.7%
7 4249
 
5.5%
Latin
ValueCountFrequency (%)
l 26
50.0%
r 26
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76793
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12815
16.7%
2 10604
13.8%
- 10000
13.0%
0 9850
12.8%
5 6607
8.6%
9 5113
 
6.7%
6 4683
 
6.1%
3 4419
 
5.8%
4 4405
 
5.7%
7 4249
 
5.5%
Other values (3) 4048
 
5.3%

위도
Real number (ℝ)

SKEWED 

Distinct3977
Distinct (%)39.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.645283
Minimum31.629479
Maximum37.929737
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T00:44:02.311576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31.629479
5-th percentile37.618942
Q137.624674
median37.650222
Q337.664578
95-th percentile37.675674
Maximum37.929737
Range6.300258
Interquartile range (IQR)0.03990425

Descriptive statistics

Standard deviation0.087709269
Coefficient of variation (CV)0.0023298874
Kurtosis4426.2586
Mean37.645283
Median Absolute Deviation (MAD)0.02083
Skewness-64.5471
Sum376452.83
Variance0.0076929158
MonotonicityNot monotonic
2024-05-04T00:44:02.907911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.624042 10
 
0.1%
37.622231 9
 
0.1%
37.677232 9
 
0.1%
37.661509 9
 
0.1%
37.627067 9
 
0.1%
37.663983 8
 
0.1%
37.670786 8
 
0.1%
37.656394 8
 
0.1%
37.671437 8
 
0.1%
37.666009 8
 
0.1%
Other values (3967) 9914
99.1%
ValueCountFrequency (%)
31.629479 2
< 0.1%
37.323564 1
< 0.1%
37.61207 2
< 0.1%
37.614475 1
< 0.1%
37.614544 2
< 0.1%
37.614683 2
< 0.1%
37.614823 2
< 0.1%
37.614824 2
< 0.1%
37.615128 2
< 0.1%
37.615261 1
< 0.1%
ValueCountFrequency (%)
37.929737 2
< 0.1%
37.68483 2
< 0.1%
37.684206 3
< 0.1%
37.684121 1
 
< 0.1%
37.683963 3
< 0.1%
37.683925 3
< 0.1%
37.683732 4
< 0.1%
37.683705 3
< 0.1%
37.68347 3
< 0.1%
37.683428 4
< 0.1%

경도
Real number (ℝ)

SKEWED 

Distinct3919
Distinct (%)39.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.05192
Minimum37.624061
Maximum127.70959
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T00:44:03.398384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.624061
5-th percentile127.05165
Q1127.06055
median127.07085
Q3127.07744
95-th percentile127.08541
Maximum127.70959
Range90.085534
Interquartile range (IQR)0.01688625

Descriptive statistics

Standard deviation1.2649698
Coefficient of variation (CV)0.0099563213
Kurtosis4996.2489
Mean127.05192
Median Absolute Deviation (MAD)0.007782
Skewness-70.686779
Sum1270519.2
Variance1.6001485
MonotonicityNot monotonic
2024-05-04T00:44:03.906571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.076381 11
 
0.1%
127.068842 10
 
0.1%
127.070369 10
 
0.1%
127.070028 10
 
0.1%
127.061836 9
 
0.1%
127.07677 9
 
0.1%
127.056859 9
 
0.1%
127.058627 9
 
0.1%
127.058309 9
 
0.1%
127.07561 9
 
0.1%
Other values (3909) 9905
99.1%
ValueCountFrequency (%)
37.6240612 2
< 0.1%
127.040071 1
 
< 0.1%
127.041928 3
< 0.1%
127.04203 2
< 0.1%
127.042075 2
< 0.1%
127.042219 2
< 0.1%
127.042411 1
 
< 0.1%
127.042431 3
< 0.1%
127.042596 2
< 0.1%
127.042597 2
< 0.1%
ValueCountFrequency (%)
127.709595 2
< 0.1%
127.111781 3
< 0.1%
127.111332 2
< 0.1%
127.111225 1
 
< 0.1%
127.111159 3
< 0.1%
127.111155 3
< 0.1%
127.11091 2
< 0.1%
127.110735 1
 
< 0.1%
127.110713 2
< 0.1%
127.110352 2
< 0.1%

등 밝기(%)
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9957 
100
 
43

Length

Max length3
Median length1
Mean length1.0086
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 9957
99.6%
100 43
 
0.4%

Length

2024-05-04T00:44:04.591535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:44:04.933877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9957
99.6%
100 43
 
0.4%

불량여부(정상:0, 불량:1)
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9890 
1
 
110

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 9890
98.9%
1 110
 
1.1%

Length

2024-05-04T00:44:05.316047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:44:05.682557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9890
98.9%
1 110
 
1.1%

등록일자
Date

Distinct5683
Distinct (%)56.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-01-22 00:09:41
Maximum2024-01-22 12:11:42
2024-05-04T00:44:06.040215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:44:06.434788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-05-04T00:43:57.313376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:43:56.552470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:43:57.614129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:43:56.962772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T00:44:06.657706image/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(%)0.0000.0001.0000.360
불량여부(정상:0, 불량:1)0.0000.0000.3601.000
2024-05-04T00:44:06.824831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등 밝기(%)불량여부(정상:0, 불량:1)
등 밝기(%)1.0000.235
불량여부(정상:0, 불량:1)0.2351.000
2024-05-04T00:44:07.004661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도등 밝기(%)불량여부(정상:0, 불량:1)
위도1.000-0.1210.0000.000
경도-0.1211.0000.0000.000
등 밝기(%)0.0000.0001.0000.235
불량여부(정상:0, 불량:1)0.0000.0000.2351.000

Missing values

2024-05-04T00:43:57.958546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T00:43:58.422329image/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
20119노원구GDS-100T25-487437.669835127.082512002024-01-22 08:11:11
19103노원구GDS-100T16-606437.658854127.068356002024-01-22 07:17:11
13206노원구GDS-100T15-540937.621243127.07846002024-01-22 05:13:47
751노원구GDS-100T11-993837.641124127.070384002024-01-22 00:11:35
11118노원구GDS-100T25-850337.650293127.081327002024-01-22 04:15:47
12926노원구GDS-100T13-083837.659814127.075179002024-01-22 05:12:38
21033노원구GDS-100T12-527537.616163127.063724002024-01-22 08:14:54
22385노원구GDS-100T15-693737.618929127.076465002024-01-22 09:10:57
10508노원구GDS-100T21-611437.624394127.080005002024-01-22 04:13:18
22164노원구GDS-100T2019-000421237.655984127.070512002024-01-22 08:19:28
기관 명모델명시리얼위도경도등 밝기(%)불량여부(정상:0, 불량:1)등록일자
24630노원구GDS-100T25-486637.668944127.082322002024-01-22 09:20:06
9951노원구GDS-100T2019-000072637.656823127.070465002024-01-22 04:11:07
6571노원구GDS-100T25-261837.670509127.084924002024-01-22 01:57:22
12057노원구GDS-100T10-512637.661481127.069967002024-01-22 04:19:35
15993노원구GDS-100T25-365137.671015127.075543002024-01-22 06:14:35
24127노원구GDS-100T21-678637.662386127.072766002024-01-22 09:18:02
18596노원구GDS-100T16-758337.650961127.085399002024-01-22 07:15:10
1230노원구GDS-100T21-524037.623202127.052899002024-01-22 00:12:52
23863노원구GDS-100T20-061637.644899127.0841002024-01-22 09:16:58
10664노원구GDS-100T2019-000120537.659296127.06781002024-01-22 04:13:55