Overview

Dataset statistics

Number of variables8
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory74.9 B

Variable types

Text1
Numeric5
Categorical1
DateTime1

Dataset

Description기준일 2023년 4월 20일자 서울특별시 송파구 통반장 현황 자료[통장정원, 통장현원, 반장정원, 반장현원, 공석(통장), 공석(반장)]입니다.
URLhttps://www.data.go.kr/data/15099081/fileData.do

Alerts

기준일 has constant value ""Constant
통장정원 is highly overall correlated with 반장정원 and 2 other fieldsHigh correlation
반장정원 is highly overall correlated with 통장정원 and 3 other fieldsHigh correlation
통장현원 is highly overall correlated with 통장정원 and 2 other fieldsHigh correlation
반장현원 is highly overall correlated with 반장정원 High correlation
공석(반장) is highly overall correlated with 통장정원 and 3 other fieldsHigh correlation
공석(통장) is highly overall correlated with 공석(반장)High correlation
공석(통장) is highly imbalanced (58.6%)Imbalance
구분 has unique valuesUnique
반장현원 has unique valuesUnique
공석(반장) has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:54:07.083713
Analysis finished2023-12-12 13:54:10.257261
Duration3.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T22:54:10.404456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.7777778
Min length3

Characters and Unicode

Total characters102
Distinct characters35
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row풍납1동
2nd row풍납2동
3rd row거여1동
4th row거여2동
5th row마천1동
ValueCountFrequency (%)
풍납1동 1
 
3.7%
가락본동 1
 
3.7%
잠실6동 1
 
3.7%
잠실4동 1
 
3.7%
잠실3동 1
 
3.7%
잠실2동 1
 
3.7%
잠실본동 1
 
3.7%
위례동 1
 
3.7%
장지동 1
 
3.7%
문정2동 1
 
3.7%
Other values (17) 17
63.0%
2023-12-12T22:54:10.754259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 27
26.5%
2 8
 
7.8%
1 7
 
6.9%
잠 6
 
5.9%
실 6
 
5.9%
가 3
 
2.9%
락 3
 
2.9%
문 2
 
2.0%
납 2
 
2.0%
본 2
 
2.0%
Other values (25) 36
35.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 83
81.4%
Decimal Number 19
 
18.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 27
32.5%
잠 6
 
7.2%
실 6
 
7.2%
가 3
 
3.6%
락 3
 
3.6%
문 2
 
2.4%
납 2
 
2.4%
본 2
 
2.4%
파 2
 
2.4%
송 2
 
2.4%
Other values (19) 28
33.7%
Decimal Number
ValueCountFrequency (%)
2 8
42.1%
1 7
36.8%
4 1
 
5.3%
3 1
 
5.3%
6 1
 
5.3%
7 1
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 83
81.4%
Common 19
 
18.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 27
32.5%
잠 6
 
7.2%
실 6
 
7.2%
가 3
 
3.6%
락 3
 
3.6%
문 2
 
2.4%
납 2
 
2.4%
본 2
 
2.4%
파 2
 
2.4%
송 2
 
2.4%
Other values (19) 28
33.7%
Common
ValueCountFrequency (%)
2 8
42.1%
1 7
36.8%
4 1
 
5.3%
3 1
 
5.3%
6 1
 
5.3%
7 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 83
81.4%
ASCII 19
 
18.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 27
32.5%
잠 6
 
7.2%
실 6
 
7.2%
가 3
 
3.6%
락 3
 
3.6%
문 2
 
2.4%
납 2
 
2.4%
본 2
 
2.4%
파 2
 
2.4%
송 2
 
2.4%
Other values (19) 28
33.7%
ASCII
ValueCountFrequency (%)
2 8
42.1%
1 7
36.8%
4 1
 
5.3%
3 1
 
5.3%
6 1
 
5.3%
7 1
 
5.3%

통장정원
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.111111
Minimum10
Maximum44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T22:54:10.924820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile15
Q122
median28
Q334.5
95-th percentile42.1
Maximum44
Range34
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation8.8070485
Coefficient of variation (CV)0.31329421
Kurtosis-0.58601208
Mean28.111111
Median Absolute Deviation (MAD)6
Skewness-0.064046372
Sum759
Variance77.564103
MonotonicityNot monotonic
2023-12-12T22:54:11.056088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
26 3
 
11.1%
22 2
 
7.4%
15 2
 
7.4%
36 2
 
7.4%
30 2
 
7.4%
32 1
 
3.7%
10 1
 
3.7%
20 1
 
3.7%
24 1
 
3.7%
33 1
 
3.7%
Other values (11) 11
40.7%
ValueCountFrequency (%)
10 1
 
3.7%
15 2
7.4%
18 1
 
3.7%
20 1
 
3.7%
21 1
 
3.7%
22 2
7.4%
23 1
 
3.7%
24 1
 
3.7%
26 3
11.1%
28 1
 
3.7%
ValueCountFrequency (%)
44 1
3.7%
43 1
3.7%
40 1
3.7%
39 1
3.7%
36 2
7.4%
35 1
3.7%
34 1
3.7%
33 1
3.7%
32 1
3.7%
31 1
3.7%

반장정원
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean157.22222
Minimum52
Maximum258
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T22:54:11.222941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum52
5-th percentile84.6
Q1124
median155
Q3189.5
95-th percentile238.2
Maximum258
Range206
Interquartile range (IQR)65.5

Descriptive statistics

Standard deviation51.239508
Coefficient of variation (CV)0.325905
Kurtosis-0.4240095
Mean157.22222
Median Absolute Deviation (MAD)38
Skewness0.090649181
Sum4245
Variance2625.4872
MonotonicityNot monotonic
2023-12-12T22:54:11.345194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
155 2
 
7.4%
204 2
 
7.4%
111 1
 
3.7%
154 1
 
3.7%
52 1
 
3.7%
103 1
 
3.7%
138 1
 
3.7%
186 1
 
3.7%
156 1
 
3.7%
234 1
 
3.7%
Other values (15) 15
55.6%
ValueCountFrequency (%)
52 1
3.7%
78 1
3.7%
100 1
3.7%
102 1
3.7%
103 1
3.7%
111 1
3.7%
116 1
3.7%
132 1
3.7%
133 1
3.7%
135 1
3.7%
ValueCountFrequency (%)
258 1
3.7%
240 1
3.7%
234 1
3.7%
227 1
3.7%
204 2
7.4%
193 1
3.7%
186 1
3.7%
183 1
3.7%
181 1
3.7%
168 1
3.7%

통장현원
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.555556
Minimum10
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T22:54:11.450926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile15
Q121.5
median28
Q334
95-th percentile42.1
Maximum43
Range33
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation8.9457052
Coefficient of variation (CV)0.32464253
Kurtosis-0.73319964
Mean27.555556
Median Absolute Deviation (MAD)7
Skewness-0.057873434
Sum744
Variance80.025641
MonotonicityNot monotonic
2023-12-12T22:54:11.587651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
15 3
 
11.1%
26 3
 
11.1%
30 3
 
11.1%
22 2
 
7.4%
43 2
 
7.4%
36 2
 
7.4%
32 1
 
3.7%
10 1
 
3.7%
20 1
 
3.7%
33 1
 
3.7%
Other values (8) 8
29.6%
ValueCountFrequency (%)
10 1
 
3.7%
15 3
11.1%
18 1
 
3.7%
20 1
 
3.7%
21 1
 
3.7%
22 2
7.4%
23 1
 
3.7%
26 3
11.1%
28 1
 
3.7%
30 3
11.1%
ValueCountFrequency (%)
43 2
7.4%
40 1
 
3.7%
38 1
 
3.7%
36 2
7.4%
35 1
 
3.7%
33 1
 
3.7%
32 1
 
3.7%
31 1
 
3.7%
30 3
11.1%
28 1
 
3.7%

공석(통장)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size348.0 B
0
23 
1
 
2
4
 
1
9
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)7.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 23
85.2%
1 2
 
7.4%
4 1
 
3.7%
9 1
 
3.7%

Length

2023-12-12T22:54:11.744263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:54:11.833057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 23
85.2%
1 2
 
7.4%
4 1
 
3.7%
9 1
 
3.7%

반장현원
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean102.18519
Minimum35
Maximum218
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T22:54:11.933601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile36.6
Q169
median95
Q3131.5
95-th percentile177.8
Maximum218
Range183
Interquartile range (IQR)62.5

Descriptive statistics

Standard deviation48.660549
Coefficient of variation (CV)0.47619964
Kurtosis-0.30682357
Mean102.18519
Median Absolute Deviation (MAD)28
Skewness0.59887724
Sum2759
Variance2367.849
MonotonicityNot monotonic
2023-12-12T22:54:12.087672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
75 1
 
3.7%
137 1
 
3.7%
38 1
 
3.7%
58 1
 
3.7%
72 1
 
3.7%
70 1
 
3.7%
43 1
 
3.7%
182 1
 
3.7%
36 1
 
3.7%
76 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
35 1
3.7%
36 1
3.7%
38 1
3.7%
43 1
3.7%
58 1
3.7%
67 1
3.7%
68 1
3.7%
70 1
3.7%
72 1
3.7%
75 1
3.7%
ValueCountFrequency (%)
218 1
3.7%
182 1
3.7%
168 1
3.7%
164 1
3.7%
161 1
3.7%
157 1
3.7%
137 1
3.7%
126 1
3.7%
117 1
3.7%
113 1
3.7%

공석(반장)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.037037
Minimum6
Maximum148
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T22:54:12.225905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile8.2
Q123
median42
Q384.5
95-th percentile124.4
Maximum148
Range142
Interquartile range (IQR)61.5

Descriptive statistics

Standard deviation40.641473
Coefficient of variation (CV)0.73843861
Kurtosis-0.45562867
Mean55.037037
Median Absolute Deviation (MAD)24
Skewness0.7861998
Sum1486
Variance1651.7293
MonotonicityNot monotonic
2023-12-12T22:54:12.359261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
36 1
 
3.7%
31 1
 
3.7%
14 1
 
3.7%
45 1
 
3.7%
66 1
 
3.7%
116 1
 
3.7%
113 1
 
3.7%
52 1
 
3.7%
99 1
 
3.7%
128 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
6 1
3.7%
7 1
3.7%
11 1
3.7%
14 1
3.7%
15 1
3.7%
20 1
3.7%
21 1
3.7%
25 1
3.7%
29 1
3.7%
31 1
3.7%
ValueCountFrequency (%)
148 1
3.7%
128 1
3.7%
116 1
3.7%
113 1
3.7%
105 1
3.7%
99 1
3.7%
86 1
3.7%
83 1
3.7%
66 1
3.7%
59 1
3.7%

기준일
Date

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
Minimum2023-04-20 00:00:00
Maximum2023-04-20 00:00:00
2023-12-12T22:54:12.482672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:12.568007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T22:54:09.637542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:07.327606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:07.835803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:08.337315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:08.838953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:09.722708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:07.431984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:07.939218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:08.462496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:08.955954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:09.798840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:07.528725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:08.016300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:08.569260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:09.052970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:09.875998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:07.623155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:08.119653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:08.660511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:09.450596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:09.963830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:07.743406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:08.222019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:08.756430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:54:09.544506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:54:12.637727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분통장정원반장정원통장현원공석(통장)반장현원공석(반장)
구분1.0001.0001.0001.0001.0001.0001.000
통장정원1.0001.0000.9150.9740.0000.2320.000
반장정원1.0000.9151.0000.8270.7440.6690.678
통장현원1.0000.9740.8271.0000.3110.3730.381
공석(통장)1.0000.0000.7440.3111.0000.4761.000
반장현원1.0000.2320.6690.3730.4761.0000.000
공석(반장)1.0000.0000.6780.3811.0000.0001.000
2023-12-12T22:54:12.773284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통장정원반장정원통장현원반장현원공석(반장)공석(통장)
통장정원1.0000.9240.9770.4500.6020.000
반장정원0.9241.0000.8970.5430.5870.464
통장현원0.9770.8971.0000.4790.5300.113
반장현원0.4500.5430.4791.000-0.2850.235
공석(반장)0.6020.5870.530-0.2851.0000.860
공석(통장)0.0000.4640.1130.2350.8601.000

Missing values

2023-12-12T22:54:10.089025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:54:10.211755image/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

구분통장정원반장정원통장현원공석(통장)반장현원공석(반장)기준일
0풍납1동2211122075362023-04-20
1풍납2동30168300137312023-04-20
2거여1동157815067112023-04-20
3거여2동30155300113422023-04-20
4마천1동2613326012672023-04-20
5마천2동26147260106412023-04-20
6방이1동1810218077252023-04-20
7방이2동35204350991052023-04-20
8오륜동151001509462023-04-20
9오금동44227431168592023-04-20
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