Overview

Dataset statistics

Number of variables5
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory49.3 B

Variable types

Text1
Numeric4

Dataset

Description서울주택도시공사의 전세임대주택(기존주택 유형)의 공급계획입니다 * 공급계획은 언제나 변경 될 수 있습니다. ※ 지원한도액을 초과하는 전세주택은 전세금액을 입주자가 부담할 경우 지원가능. 단, 전세금은 호당 대출한도액의 250%이내로 제한하되 세대원수가 5인 이상일 경우 예외 가능
URLhttps://www.data.go.kr/data/15088178/fileData.do

Alerts

호수(2023년) is highly overall correlated with 호수(2022년) and 2 other fieldsHigh correlation
호수(2022년) is highly overall correlated with 호수(2023년) and 2 other fieldsHigh correlation
호수(2021년) is highly overall correlated with 호수(2023년) and 2 other fieldsHigh correlation
호수(2020년) is highly overall correlated with 호수(2023년) and 2 other fieldsHigh correlation
지역 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:41:51.687506
Analysis finished2023-12-12 12:41:54.194895
Duration2.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T21:41:54.372496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.08
Min length2

Characters and Unicode

Total characters77
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row강남구
2nd row강동구
3rd row강북구
4th row강서구
5th row관악구
ValueCountFrequency (%)
강남구 1
 
4.0%
서대문구 1
 
4.0%
중구 1
 
4.0%
종로구 1
 
4.0%
은평구 1
 
4.0%
용산구 1
 
4.0%
영등포구 1
 
4.0%
양천구 1
 
4.0%
송파구 1
 
4.0%
성북구 1
 
4.0%
Other values (15) 15
60.0%
2023-12-12T21:41:54.811478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26
33.8%
4
 
5.2%
4
 
5.2%
3
 
3.9%
2
 
2.6%
2
 
2.6%
2
 
2.6%
2
 
2.6%
2
 
2.6%
2
 
2.6%
Other values (26) 28
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 77
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
26
33.8%
4
 
5.2%
4
 
5.2%
3
 
3.9%
2
 
2.6%
2
 
2.6%
2
 
2.6%
2
 
2.6%
2
 
2.6%
2
 
2.6%
Other values (26) 28
36.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 77
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
26
33.8%
4
 
5.2%
4
 
5.2%
3
 
3.9%
2
 
2.6%
2
 
2.6%
2
 
2.6%
2
 
2.6%
2
 
2.6%
2
 
2.6%
Other values (26) 28
36.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 77
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
26
33.8%
4
 
5.2%
4
 
5.2%
3
 
3.9%
2
 
2.6%
2
 
2.6%
2
 
2.6%
2
 
2.6%
2
 
2.6%
2
 
2.6%
Other values (26) 28
36.4%

호수(2023년)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108
Minimum24
Maximum289
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T21:41:54.965611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24
5-th percentile59.6
Q164
median91
Q3132
95-th percentile206.6
Maximum289
Range265
Interquartile range (IQR)68

Descriptive statistics

Standard deviation58.383074
Coefficient of variation (CV)0.54058402
Kurtosis2.6835168
Mean108
Median Absolute Deviation (MAD)28
Skewness1.4786249
Sum2700
Variance3408.5833
MonotonicityNot monotonic
2023-12-12T21:41:55.103384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
64 3
 
12.0%
63 2
 
8.0%
71 1
 
4.0%
59 1
 
4.0%
127 1
 
4.0%
24 1
 
4.0%
132 1
 
4.0%
86 1
 
4.0%
83 1
 
4.0%
156 1
 
4.0%
Other values (12) 12
48.0%
ValueCountFrequency (%)
24 1
 
4.0%
59 1
 
4.0%
62 1
 
4.0%
63 2
8.0%
64 3
12.0%
71 1
 
4.0%
83 1
 
4.0%
85 1
 
4.0%
86 1
 
4.0%
91 1
 
4.0%
ValueCountFrequency (%)
289 1
4.0%
211 1
4.0%
189 1
4.0%
156 1
4.0%
155 1
4.0%
145 1
4.0%
132 1
4.0%
127 1
4.0%
116 1
4.0%
106 1
4.0%

호수(2022년)
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108
Minimum41
Maximum199
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T21:41:55.247565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41
5-th percentile58
Q175
median96
Q3135
95-th percentile196.8
Maximum199
Range158
Interquartile range (IQR)60

Descriptive statistics

Standard deviation46.265538
Coefficient of variation (CV)0.42838461
Kurtosis-0.38089508
Mean108
Median Absolute Deviation (MAD)34
Skewness0.70967292
Sum2700
Variance2140.5
MonotonicityNot monotonic
2023-12-12T21:41:55.373248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
61 2
 
8.0%
58 2
 
8.0%
95 1
 
4.0%
158 1
 
4.0%
41 1
 
4.0%
123 1
 
4.0%
84 1
 
4.0%
116 1
 
4.0%
88 1
 
4.0%
135 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
41 1
4.0%
58 2
8.0%
61 2
8.0%
62 1
4.0%
75 1
4.0%
77 1
4.0%
84 1
4.0%
88 1
4.0%
89 1
4.0%
95 1
4.0%
ValueCountFrequency (%)
199 1
4.0%
197 1
4.0%
196 1
4.0%
166 1
4.0%
158 1
4.0%
136 1
4.0%
135 1
4.0%
123 1
4.0%
116 1
4.0%
114 1
4.0%

호수(2021년)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100
Minimum33
Maximum177
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T21:41:55.520741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33
5-th percentile49
Q174
median85
Q3134
95-th percentile152.2
Maximum177
Range144
Interquartile range (IQR)60

Descriptive statistics

Standard deviation37.20103
Coefficient of variation (CV)0.3720103
Kurtosis-0.72768911
Mean100
Median Absolute Deviation (MAD)28
Skewness0.28927798
Sum2500
Variance1383.9167
MonotonicityNot monotonic
2023-12-12T21:41:55.667328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
85 3
 
12.0%
134 2
 
8.0%
48 1
 
4.0%
149 1
 
4.0%
33 1
 
4.0%
53 1
 
4.0%
147 1
 
4.0%
72 1
 
4.0%
100 1
 
4.0%
113 1
 
4.0%
Other values (12) 12
48.0%
ValueCountFrequency (%)
33 1
4.0%
48 1
4.0%
53 1
4.0%
68 1
4.0%
70 1
4.0%
72 1
4.0%
74 1
4.0%
78 1
4.0%
81 1
4.0%
82 1
4.0%
ValueCountFrequency (%)
177 1
4.0%
153 1
4.0%
149 1
4.0%
147 1
4.0%
143 1
4.0%
134 2
8.0%
125 1
4.0%
116 1
4.0%
113 1
4.0%
100 1
4.0%

호수(2020년)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100
Minimum35
Maximum163
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T21:41:55.800263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile35.8
Q172
median93
Q3138
95-th percentile155.2
Maximum163
Range128
Interquartile range (IQR)66

Descriptive statistics

Standard deviation39.349926
Coefficient of variation (CV)0.39349926
Kurtosis-1.0779942
Mean100
Median Absolute Deviation (MAD)29
Skewness0.034496954
Sum2500
Variance1548.4167
MonotonicityNot monotonic
2023-12-12T21:41:55.929827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
35 2
 
8.0%
72 2
 
8.0%
83 2
 
8.0%
64 1
 
4.0%
39 1
 
4.0%
156 1
 
4.0%
163 1
 
4.0%
82 1
 
4.0%
89 1
 
4.0%
93 1
 
4.0%
Other values (12) 12
48.0%
ValueCountFrequency (%)
35 2
8.0%
39 1
4.0%
64 1
4.0%
69 1
4.0%
72 2
8.0%
76 1
4.0%
82 1
4.0%
83 2
8.0%
89 1
4.0%
93 1
4.0%
ValueCountFrequency (%)
163 1
4.0%
156 1
4.0%
152 1
4.0%
151 1
4.0%
146 1
4.0%
141 1
4.0%
138 1
4.0%
131 1
4.0%
129 1
4.0%
105 1
4.0%

Interactions

2023-12-12T21:41:53.553941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:51.847756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:52.269427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:52.765464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:53.668924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:51.932307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:52.404657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:52.870411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:53.773507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:52.032156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:52.553809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:52.990454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:53.909638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:52.132848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:52.663398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:53.109245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:41:56.026999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역호수(2023년)호수(2022년)호수(2021년)호수(2020년)
지역1.0001.0001.0001.0001.000
호수(2023년)1.0001.0000.8470.9170.726
호수(2022년)1.0000.8471.0000.7890.661
호수(2021년)1.0000.9170.7891.0000.679
호수(2020년)1.0000.7260.6610.6791.000
2023-12-12T21:41:56.130476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호수(2023년)호수(2022년)호수(2021년)호수(2020년)
호수(2023년)1.0000.8850.7610.789
호수(2022년)0.8851.0000.8950.821
호수(2021년)0.7610.8951.0000.863
호수(2020년)0.7890.8210.8631.000

Missing values

2023-12-12T21:41:54.051028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:41:54.148851image/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

지역호수(2023년)호수(2022년)호수(2021년)호수(2020년)
0강남구71778564
1강동구8596116138
2강북구145197143131
3강서구155166134146
4관악구211199177152
5광진구189136153141
6구로구64588172
7금천구1068982105
8노원구1021088583
9도봉구289196125129
지역호수(2023년)호수(2022년)호수(2021년)호수(2020년)
15성동구62627072
16성북구91756894
17송파구156135134151
18양천구638811393
19영등포구8311610089
20용산구86847282
21은평구132123147163
22종로구64585335
23중구24413335
24중랑구127158149156