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 (94.2%)Imbalance
불량여부(정상:0, 불량:1) is highly imbalanced (93.8%)Imbalance
위도 is highly skewed (γ1 = -54.04213392)Skewed
경도 is highly skewed (γ1 = -57.70745708)Skewed

Reproduction

Analysis started2024-05-04 00:43:01.265017
Analysis finished2024-05-04 00:43:04.801268
Duration3.54 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

2024-05-04T00:43:04.996896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:43:05.383557image/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

2024-05-04T00:43:05.805098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:43:06.211334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
gds-100t 10000
100.0%

시리얼
Text

Distinct4202
Distinct (%)42.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T00:43:07.079300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length7
Mean length7.7154
Min length7

Characters and Unicode

Total characters77154
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

Unique979 ?
Unique (%)9.8%

Sample

1st row15-7846
2nd row24-9638
3rd row15-4785
4th row21-3952
5th row21-8694
ValueCountFrequency (%)
15-2473 6
 
0.1%
25-2500 6
 
0.1%
2019-0002391 6
 
0.1%
20-7716 6
 
0.1%
11-8482 6
 
0.1%
21-7310 6
 
0.1%
15-3742 6
 
0.1%
2019-0002287 6
 
0.1%
2019-0001280 6
 
0.1%
16-6739 6
 
0.1%
Other values (4192) 9940
99.4%
2024-05-04T00:43:08.446784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12983
16.8%
2 10656
13.8%
0 10243
13.3%
- 10000
13.0%
5 6505
8.4%
9 5219
6.8%
6 4645
 
6.0%
3 4547
 
5.9%
4 4283
 
5.6%
7 4119
 
5.3%
Other values (3) 3954
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67108
87.0%
Dash Punctuation 10000
 
13.0%
Lowercase Letter 46
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12983
19.3%
2 10656
15.9%
0 10243
15.3%
5 6505
9.7%
9 5219
7.8%
6 4645
 
6.9%
3 4547
 
6.8%
4 4283
 
6.4%
7 4119
 
6.1%
8 3908
 
5.8%
Lowercase Letter
ValueCountFrequency (%)
l 23
50.0%
r 23
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 77108
99.9%
Latin 46
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12983
16.8%
2 10656
13.8%
0 10243
13.3%
- 10000
13.0%
5 6505
8.4%
9 5219
6.8%
6 4645
 
6.0%
3 4547
 
5.9%
4 4283
 
5.6%
7 4119
 
5.3%
Latin
ValueCountFrequency (%)
l 23
50.0%
r 23
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 77154
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12983
16.8%
2 10656
13.8%
0 10243
13.3%
- 10000
13.0%
5 6505
8.4%
9 5219
6.8%
6 4645
 
6.0%
3 4547
 
5.9%
4 4283
 
5.6%
7 4119
 
5.3%
Other values (3) 3954
 
5.1%

위도
Real number (ℝ)

SKEWED 

Distinct4005
Distinct (%)40.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.644135
Minimum31.629479
Maximum37.929737
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T00:43:08.947011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31.629479
5-th percentile37.618726
Q137.624613
median37.649047
Q337.664124
95-th percentile37.675477
Maximum37.929737
Range6.300258
Interquartile range (IQR)0.03951075

Descriptive statistics

Standard deviation0.10650724
Coefficient of variation (CV)0.0028293182
Kurtosis3050.2229
Mean37.644135
Median Absolute Deviation (MAD)0.021025
Skewness-54.042134
Sum376441.35
Variance0.011343791
MonotonicityNot monotonic
2024-05-04T00:43:09.444242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.658965 11
 
0.1%
37.634583 9
 
0.1%
37.624869 9
 
0.1%
37.673364 9
 
0.1%
37.656394 9
 
0.1%
37.627229 8
 
0.1%
37.671843 8
 
0.1%
37.621239 8
 
0.1%
37.624762 8
 
0.1%
37.676001 8
 
0.1%
Other values (3995) 9913
99.1%
ValueCountFrequency (%)
31.629479 3
< 0.1%
37.323564 3
< 0.1%
37.61207 3
< 0.1%
37.614475 4
< 0.1%
37.614544 3
< 0.1%
37.614683 2
< 0.1%
37.614823 2
< 0.1%
37.614824 2
< 0.1%
37.615128 1
 
< 0.1%
37.615143 3
< 0.1%
ValueCountFrequency (%)
37.929737 4
< 0.1%
37.68483 1
 
< 0.1%
37.684206 2
< 0.1%
37.684121 4
< 0.1%
37.683963 4
< 0.1%
37.683925 2
< 0.1%
37.683732 3
< 0.1%
37.683705 1
 
< 0.1%
37.68347 3
< 0.1%
37.683428 2
< 0.1%

경도
Real number (ℝ)

SKEWED 

Distinct3952
Distinct (%)39.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.04295
Minimum37.624061
Maximum127.70959
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T00:43:09.885087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.624061
5-th percentile127.05155
Q1127.06016
median127.07071
Q3127.07735
95-th percentile127.08529
Maximum127.70959
Range90.085534
Interquartile range (IQR)0.017182

Descriptive statistics

Standard deviation1.5491818
Coefficient of variation (CV)0.012194158
Kurtosis3329.2129
Mean127.04295
Median Absolute Deviation (MAD)0.007945
Skewness-57.707457
Sum1270429.5
Variance2.3999641
MonotonicityNot monotonic
2024-05-04T00:43:10.325240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.069653 12
 
0.1%
127.059021 11
 
0.1%
127.070635 10
 
0.1%
127.076381 10
 
0.1%
127.076014 9
 
0.1%
127.082619 9
 
0.1%
127.0694 9
 
0.1%
127.075412 8
 
0.1%
127.056543 8
 
0.1%
127.082116 8
 
0.1%
Other values (3942) 9906
99.1%
ValueCountFrequency (%)
37.6240612 3
< 0.1%
127.040071 1
 
< 0.1%
127.041928 1
 
< 0.1%
127.04203 3
< 0.1%
127.042075 4
< 0.1%
127.042219 2
< 0.1%
127.042411 3
< 0.1%
127.042431 2
< 0.1%
127.042596 4
< 0.1%
127.042597 1
 
< 0.1%
ValueCountFrequency (%)
127.709595 4
< 0.1%
127.111781 2
< 0.1%
127.111452 2
< 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%

등 밝기(%)
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
100
9933 
0
 
67

Length

Max length3
Median length3
Mean length2.9866
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row100
2nd row100
3rd row100
4th row100
5th row100

Common Values

ValueCountFrequency (%)
100 9933
99.3%
0 67
 
0.7%

Length

2024-05-04T00:43:10.836858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:43:11.203531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
100 9933
99.3%
0 67
 
0.7%

불량여부(정상:0, 불량:1)
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9927 
1
 
73

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 9927
99.3%
1 73
 
0.7%

Length

2024-05-04T00:43:11.552389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:43:12.040105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9927
99.3%
1 73
 
0.7%

등록일자
Date

Distinct5474
Distinct (%)54.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-01-08 00:09:42
Maximum2024-01-08 11:17:05
2024-05-04T00:43:12.660977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:43:13.321947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-05-04T00:43:02.789109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:43:02.222687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:43:03.091387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:43:02.513824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T00:43:13.682275image/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(%)0.0000.0001.0000.645
불량여부(정상:0, 불량:1)0.0000.0000.6451.000
2024-05-04T00:43:14.159179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등 밝기(%)불량여부(정상:0, 불량:1)
등 밝기(%)1.0000.446
불량여부(정상:0, 불량:1)0.4461.000
2024-05-04T00:43:14.541726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도등 밝기(%)불량여부(정상:0, 불량:1)
위도1.000-0.0870.0000.000
경도-0.0871.0000.0000.000
등 밝기(%)0.0000.0001.0000.446
불량여부(정상:0, 불량:1)0.0000.0000.4461.000

Missing values

2024-05-04T00:43:03.816475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T00:43:04.550445image/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
15175노원구GDS-100T15-784637.622047127.07973110002024-01-08 06:12:51
4473노원구GDS-100T24-963837.667085127.07698510002024-01-08 01:49:04
23266노원구GDS-100T15-478537.632771127.056510002024-01-08 09:17:42
16534노원구GDS-100T21-395237.62847127.05584610002024-01-08 06:18:42
21417노원구GDS-100T21-869437.664674127.0672310002024-01-08 08:18:41
21907노원구GDS-100T25-722537.628663127.05704410012024-01-08 09:12:04
20364노원구GDS-100T17-055537.675037127.05237310002024-01-08 08:14:15
20103노원구GDS-100T22-519337.673226127.05213810002024-01-08 08:13:10
10338노원구GDS-100T13-095437.661179127.07592510002024-01-08 04:13:46
8656노원구GDS-100T25-130437.669799127.07947210002024-01-08 03:17:18
기관 명모델명시리얼위도경도등 밝기(%)불량여부(정상:0, 불량:1)등록일자
7738노원구GDS-100T21-581637.629941127.0559410002024-01-08 03:13:26
5488노원구GDS-100T12-081537.624138127.07127910002024-01-08 01:53:02
27429노원구GDS-100T2019-000041337.636183127.07172610002024-01-08 11:16:56
652노원구GDS-100T12-597637.620676127.06124510002024-01-08 00:11:19
25128노원구GDS-100T13-935137.662532127.07072710002024-01-08 10:16:20
22510노원구GDS-100T2019-000052237.649999127.08399710002024-01-08 09:14:33
26008노원구GDS-100T21-674237.661875127.07229210002024-01-08 10:20:07
6491노원구GDS-100T15-456137.676948127.05413810002024-01-08 01:57:05
23385노원구GDS-100T13-118237.65348127.07360110002024-01-08 09:18:12
2050노원구GDS-100T16-420237.676017127.0512110002024-01-08 00:15:01