Overview

Dataset statistics

Number of variables14
Number of observations302
Missing cells114
Missing cells (%)2.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.2 KiB
Average record size in memory119.4 B

Variable types

Categorical3
Text3
Numeric6
DateTime2

Dataset

Description제공 신청 데이터로 신청된 2022년 1월부터 2023년 6월까지의 여주시 내 건축물 사용승인 허가 목록입니다. 1회성 데이터입니다.
URLhttps://www.data.go.kr/data/15116416/fileData.do

Alerts

대지면적 is highly overall correlated with 건축면적 and 1 other fieldsHigh correlation
건축면적 is highly overall correlated with 대지면적 and 1 other fieldsHigh correlation
연면적 is highly overall correlated with 대지면적 and 2 other fieldsHigh correlation
건폐율 is highly overall correlated with 용적률High correlation
용적률 is highly overall correlated with 건폐율 and 1 other fieldsHigh correlation
지상층수 is highly overall correlated with 용적률High correlation
지하층수 is highly overall correlated with 연면적 and 1 other fieldsHigh correlation
주용도 is highly overall correlated with 지하층수High correlation
건물명 has 35 (11.6%) missing valuesMissing
부속용도 has 79 (26.2%) missing valuesMissing
소재지지번주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:07:11.564507
Analysis finished2023-12-12 15:07:16.238489
Duration4.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
신축
251 
증축
51 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row신축
2nd row신축
3rd row증축
4th row증축
5th row신축

Common Values

ValueCountFrequency (%)
신축 251
83.1%
증축 51
 
16.9%

Length

2023-12-13T00:07:16.292907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:07:16.398456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 251
83.1%
증축 51
 
16.9%

건물명
Text

MISSING 

Distinct258
Distinct (%)96.6%
Missing35
Missing (%)11.6%
Memory size2.5 KiB
2023-12-13T00:07:16.727111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length24
Mean length15.644195
Min length1

Characters and Unicode

Total characters4177
Distinct characters220
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique254 ?
Unique (%)95.1%

Sample

1st row온실
2nd row오학동 426-8 제2종근린생활시설
3rd row월송동 345-37 제2종근린생활시설 증축공사
4th row흥천면 대당리 125-41
5th row상동 139 제2종근린생활시설
ValueCountFrequency (%)
제2종근린생활시설 61
 
7.7%
단독주택 41
 
5.2%
가남읍 24
 
3.0%
제1종근린생활시설 21
 
2.7%
오학동 20
 
2.5%
공장 20
 
2.5%
상동 15
 
1.9%
산북면 15
 
1.9%
강천면 14
 
1.8%
월송동 13
 
1.6%
Other values (354) 545
69.1%
2023-12-13T00:07:17.316899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
665
 
15.9%
1 188
 
4.5%
2 185
 
4.4%
- 162
 
3.9%
동 127
 
3.0%
시 125
 
3.0%
설 123
 
2.9%
리 122
 
2.9%
3 110
 
2.6%
종 109
 
2.6%
Other values (210) 2261
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2392
57.3%
Decimal Number 908
 
21.7%
Space Separator 665
 
15.9%
Dash Punctuation 162
 
3.9%
Other Punctuation 22
 
0.5%
Uppercase Letter 12
 
0.3%
Close Punctuation 8
 
0.2%
Open Punctuation 7
 
0.2%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 127
 
5.3%
시 125
 
5.2%
설 123
 
5.1%
리 122
 
5.1%
종 109
 
4.6%
생 98
 
4.1%
근 98
 
4.1%
제 96
 
4.0%
린 95
 
4.0%
활 95
 
4.0%
Other values (187) 1304
54.5%
Decimal Number
ValueCountFrequency (%)
1 188
20.7%
2 185
20.4%
3 110
12.1%
4 75
 
8.3%
0 72
 
7.9%
5 66
 
7.3%
6 58
 
6.4%
7 56
 
6.2%
9 54
 
5.9%
8 44
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
C 4
33.3%
A 3
25.0%
I 2
16.7%
B 2
16.7%
V 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
. 13
59.1%
, 9
40.9%
Close Punctuation
ValueCountFrequency (%)
) 7
87.5%
] 1
 
12.5%
Space Separator
ValueCountFrequency (%)
665
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 162
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2389
57.2%
Common 1772
42.4%
Latin 13
 
0.3%
Han 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 127
 
5.3%
시 125
 
5.2%
설 123
 
5.1%
리 122
 
5.1%
종 109
 
4.6%
생 98
 
4.1%
근 98
 
4.1%
제 96
 
4.0%
린 95
 
4.0%
활 95
 
4.0%
Other values (184) 1301
54.5%
Common
ValueCountFrequency (%)
665
37.5%
1 188
 
10.6%
2 185
 
10.4%
- 162
 
9.1%
3 110
 
6.2%
4 75
 
4.2%
0 72
 
4.1%
5 66
 
3.7%
6 58
 
3.3%
7 56
 
3.2%
Other values (7) 135
 
7.6%
Latin
ValueCountFrequency (%)
C 4
30.8%
A 3
23.1%
I 2
15.4%
B 2
15.4%
V 1
 
7.7%
k 1
 
7.7%
Han
ValueCountFrequency (%)
恩 1
33.3%
亨 1
33.3%
齋 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2389
57.2%
ASCII 1785
42.7%
CJK 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
665
37.3%
1 188
 
10.5%
2 185
 
10.4%
- 162
 
9.1%
3 110
 
6.2%
4 75
 
4.2%
0 72
 
4.0%
5 66
 
3.7%
6 58
 
3.2%
7 56
 
3.1%
Other values (13) 148
 
8.3%
Hangul
ValueCountFrequency (%)
동 127
 
5.3%
시 125
 
5.2%
설 123
 
5.1%
리 122
 
5.1%
종 109
 
4.6%
생 98
 
4.1%
근 98
 
4.1%
제 96
 
4.0%
린 95
 
4.0%
활 95
 
4.0%
Other values (184) 1301
54.5%
CJK
ValueCountFrequency (%)
恩 1
33.3%
亨 1
33.3%
齋 1
33.3%

소재지지번주소
Text

UNIQUE 

Distinct302
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-13T00:07:17.718469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length19.986755
Min length13

Characters and Unicode

Total characters6036
Distinct characters112
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique302 ?
Unique (%)100.0%

Sample

1st row경기도 여주시 북내면 지내리 560-1
2nd row경기도 여주시 오학동 426-8
3rd row경기도 여주시 월송동 345-37
4th row경기도 여주시 흥천면 대당리 125-41
5th row경기도 여주시 상동 139
ValueCountFrequency (%)
경기도 302
21.0%
여주시 302
21.0%
가남읍 42
 
2.9%
외1필지 39
 
2.7%
오학동 28
 
1.9%
점봉동 24
 
1.7%
산북면 22
 
1.5%
강천면 21
 
1.5%
상동 18
 
1.2%
세종대왕면 15
 
1.0%
Other values (384) 628
43.6%
2023-12-13T00:07:18.280302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1139
18.9%
도 308
 
5.1%
주 304
 
5.0%
경 302
 
5.0%
시 302
 
5.0%
기 302
 
5.0%
여 302
 
5.0%
1 249
 
4.1%
- 242
 
4.0%
2 181
 
3.0%
Other values (102) 2405
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3386
56.1%
Decimal Number 1269
 
21.0%
Space Separator 1139
 
18.9%
Dash Punctuation 242
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 308
 
9.1%
주 304
 
9.0%
경 302
 
8.9%
시 302
 
8.9%
기 302
 
8.9%
여 302
 
8.9%
동 164
 
4.8%
리 153
 
4.5%
면 111
 
3.3%
지 81
 
2.4%
Other values (90) 1057
31.2%
Decimal Number
ValueCountFrequency (%)
1 249
19.6%
2 181
14.3%
3 162
12.8%
4 141
11.1%
5 119
9.4%
6 100
7.9%
9 91
 
7.2%
7 85
 
6.7%
0 74
 
5.8%
8 67
 
5.3%
Space Separator
ValueCountFrequency (%)
1139
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3386
56.1%
Common 2650
43.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 308
 
9.1%
주 304
 
9.0%
경 302
 
8.9%
시 302
 
8.9%
기 302
 
8.9%
여 302
 
8.9%
동 164
 
4.8%
리 153
 
4.5%
면 111
 
3.3%
지 81
 
2.4%
Other values (90) 1057
31.2%
Common
ValueCountFrequency (%)
1139
43.0%
1 249
 
9.4%
- 242
 
9.1%
2 181
 
6.8%
3 162
 
6.1%
4 141
 
5.3%
5 119
 
4.5%
6 100
 
3.8%
9 91
 
3.4%
7 85
 
3.2%
Other values (2) 141
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3386
56.1%
ASCII 2650
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1139
43.0%
1 249
 
9.4%
- 242
 
9.1%
2 181
 
6.8%
3 162
 
6.1%
4 141
 
5.3%
5 119
 
4.5%
6 100
 
3.8%
9 91
 
3.4%
7 85
 
3.2%
Other values (2) 141
 
5.3%
Hangul
ValueCountFrequency (%)
도 308
 
9.1%
주 304
 
9.0%
경 302
 
8.9%
시 302
 
8.9%
기 302
 
8.9%
여 302
 
8.9%
동 164
 
4.8%
리 153
 
4.5%
면 111
 
3.3%
지 81
 
2.4%
Other values (90) 1057
31.2%

대지면적
Real number (ℝ)

HIGH CORRELATION 

Distinct275
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21255.623
Minimum132.6
Maximum1959772
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-13T00:07:18.469346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum132.6
5-th percentile284.175
Q1583.5
median1025
Q33240.25
95-th percentile28745.815
Maximum1959772
Range1959639.4
Interquartile range (IQR)2656.75

Descriptive statistics

Standard deviation167665.14
Coefficient of variation (CV)7.888037
Kurtosis117.19536
Mean21255.623
Median Absolute Deviation (MAD)641
Skewness10.672765
Sum6419198.1
Variance2.8111599 × 1010
MonotonicityNot monotonic
2023-12-13T00:07:18.616607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
660.0 5
 
1.7%
625.0 4
 
1.3%
990.0 3
 
1.0%
455.0 3
 
1.0%
986.0 3
 
1.0%
817.0 3
 
1.0%
457.0 3
 
1.0%
989.0 2
 
0.7%
603.0 2
 
0.7%
836.0 2
 
0.7%
Other values (265) 272
90.1%
ValueCountFrequency (%)
132.6 1
0.3%
148.0 1
0.3%
149.0 1
0.3%
171.0 1
0.3%
206.4 1
0.3%
232.7 1
0.3%
239.0 1
0.3%
250.1 1
0.3%
252.2 1
0.3%
260.8 1
0.3%
ValueCountFrequency (%)
1959772.0 1
0.3%
1923897.0 1
0.3%
966977.0 1
0.3%
314387.0 1
0.3%
43077.0 1
0.3%
33187.0 1
0.3%
32959.0 1
0.3%
30843.5 1
0.3%
29980.0 1
0.3%
29974.9 1
0.3%

건축면적
Real number (ℝ)

HIGH CORRELATION 

Distinct281
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1249.2402
Minimum53.4
Maximum16823.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-13T00:07:18.768815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum53.4
5-th percentile83.6705
Q1171.815
median296.9
Q3918.6075
95-th percentile5776.298
Maximum16823.2
Range16769.8
Interquartile range (IQR)746.7925

Descriptive statistics

Standard deviation2524.1146
Coefficient of variation (CV)2.0205198
Kurtosis14.121636
Mean1249.2402
Median Absolute Deviation (MAD)174.925
Skewness3.5884864
Sum377270.55
Variance6371154.5
MonotonicityNot monotonic
2023-12-13T00:07:18.910603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
495.0 6
 
2.0%
114.64 4
 
1.3%
263.76 2
 
0.7%
243.9 2
 
0.7%
242.36 2
 
0.7%
220.4 2
 
0.7%
343.0 2
 
0.7%
181.2 2
 
0.7%
244.72 2
 
0.7%
82.674 2
 
0.7%
Other values (271) 276
91.4%
ValueCountFrequency (%)
53.4 1
0.3%
57.62 1
0.3%
58.04 1
0.3%
66.3 1
0.3%
77.09 1
0.3%
77.82 1
0.3%
78.86 1
0.3%
80.36 1
0.3%
80.94 1
0.3%
81.42 1
0.3%
ValueCountFrequency (%)
16823.2 1
0.3%
16002.42 1
0.3%
13508.2 1
0.3%
11898.34 1
0.3%
11708.15 1
0.3%
11136.75 1
0.3%
10546.98 1
0.3%
10369.11 1
0.3%
10332.04 1
0.3%
10218.448 1
0.3%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct285
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3246.2059
Minimum102.1
Maximum75881.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-13T00:07:19.415507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102.1
5-th percentile161.817
Q1327.18
median634.79
Q31406.455
95-th percentile17700.934
Maximum75881.69
Range75779.59
Interquartile range (IQR)1079.275

Descriptive statistics

Standard deviation8997.7269
Coefficient of variation (CV)2.7717672
Kurtosis25.571119
Mean3246.2059
Median Absolute Deviation (MAD)364.94
Skewness4.7663653
Sum980354.18
Variance80959089
MonotonicityNot monotonic
2023-12-13T00:07:19.551783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
495.0 6
 
2.0%
189.52 3
 
1.0%
496.0 2
 
0.7%
343.0 2
 
0.7%
623.11 2
 
0.7%
605.5 2
 
0.7%
141.35 2
 
0.7%
198.9 2
 
0.7%
655.74 2
 
0.7%
199.8 2
 
0.7%
Other values (275) 277
91.7%
ValueCountFrequency (%)
102.1 1
0.3%
111.45 1
0.3%
130.83 1
0.3%
133.3 1
0.3%
133.62 1
0.3%
134.4 1
0.3%
135.18 1
0.3%
136.4 1
0.3%
136.62 1
0.3%
138.24 1
0.3%
ValueCountFrequency (%)
75881.69 1
0.3%
55897.3 1
0.3%
49989.19 1
0.3%
47230.83 1
0.3%
43273.043 1
0.3%
42395.09 1
0.3%
39900.81 1
0.3%
39846.82 1
0.3%
38633.29 1
0.3%
26759.61 1
0.3%

건폐율
Real number (ℝ)

HIGH CORRELATION 

Distinct285
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.54677
Minimum0.3909
Maximum69.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-13T00:07:19.718312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3909
5-th percentile11.458755
Q119.82
median31.085
Q339.5825
95-th percentile58.7055
Maximum69.4
Range69.0091
Interquartile range (IQR)19.7625

Descriptive statistics

Standard deviation14.428286
Coefficient of variation (CV)0.45736174
Kurtosis-0.42031383
Mean31.54677
Median Absolute Deviation (MAD)10.5
Skewness0.32974573
Sum9527.1246
Variance208.17543
MonotonicityNot monotonic
2023-12-13T00:07:19.888012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19.97 3
 
1.0%
39.34 2
 
0.7%
22.87 2
 
0.7%
29.85 2
 
0.7%
19.99 2
 
0.7%
34.49 2
 
0.7%
19.95 2
 
0.7%
19.87 2
 
0.7%
19.98 2
 
0.7%
39.16 2
 
0.7%
Other values (275) 281
93.0%
ValueCountFrequency (%)
0.3909 1
0.3%
0.43 1
0.3%
0.51 1
0.3%
0.537 1
0.3%
1.7714 1
0.3%
3.58 1
0.3%
4.92 1
0.3%
5.67 1
0.3%
6.1186 1
0.3%
8.01 1
0.3%
ValueCountFrequency (%)
69.4 1
0.3%
65.41 1
0.3%
63.2721 1
0.3%
62.07 1
0.3%
60.1348 1
0.3%
59.8853 1
0.3%
59.88 1
0.3%
59.87 1
0.3%
59.83 1
0.3%
59.81 1
0.3%

용적률
Real number (ℝ)

HIGH CORRELATION 

Distinct291
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.355386
Minimum0.3389
Maximum424.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-13T00:07:20.040862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3389
5-th percentile14.4335
Q130.696025
median47.3869
Q396.4825
95-th percentile173.8495
Maximum424.74
Range424.4011
Interquartile range (IQR)65.786475

Descriptive statistics

Standard deviation54.97896
Coefficient of variation (CV)0.82855309
Kurtosis7.6964512
Mean66.355386
Median Absolute Deviation (MAD)23.005
Skewness2.2150345
Sum20039.327
Variance3022.6861
MonotonicityNot monotonic
2023-12-13T00:07:20.187842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.59 3
 
1.0%
37.61 2
 
0.7%
99.7 2
 
0.7%
36.72 2
 
0.7%
41.65 2
 
0.7%
22.87 2
 
0.7%
99.67 2
 
0.7%
19.3 2
 
0.7%
99.35 2
 
0.7%
99.34 2
 
0.7%
Other values (281) 281
93.0%
ValueCountFrequency (%)
0.3389 1
0.3%
0.7 1
0.3%
0.7491 1
0.3%
0.86 1
0.3%
1.7714 1
0.3%
4.49 1
0.3%
5.0716 1
0.3%
6.26 1
0.3%
10.01 1
0.3%
10.87 1
0.3%
ValueCountFrequency (%)
424.74 1
0.3%
295.95 1
0.3%
255.3 1
0.3%
249.93 1
0.3%
249.6241 1
0.3%
247.47 1
0.3%
243.1 1
0.3%
234.82 1
0.3%
199.86 1
0.3%
199.46 1
0.3%

사용승인일
Date

Distinct198
Distinct (%)65.6%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum2022-01-04 00:00:00
Maximum2023-06-30 00:00:00
2023-12-13T00:07:20.338350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:20.520298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

건축허가일
Date

Distinct223
Distinct (%)73.8%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum2007-09-14 00:00:00
Maximum2023-02-15 00:00:00
2023-12-13T00:07:20.702899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:20.868799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

지상층수
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.589404
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-13T00:07:21.016456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q33
95-th percentile4
Maximum22
Range21
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.7455078
Coefficient of variation (CV)0.67409638
Kurtosis51.159447
Mean2.589404
Median Absolute Deviation (MAD)1
Skewness5.1243016
Sum782
Variance3.0467977
MonotonicityNot monotonic
2023-12-13T00:07:21.150429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 94
31.1%
1 74
24.5%
3 62
20.5%
4 57
18.9%
5 8
 
2.6%
6 3
 
1.0%
9 1
 
0.3%
7 1
 
0.3%
22 1
 
0.3%
10 1
 
0.3%
ValueCountFrequency (%)
1 74
24.5%
2 94
31.1%
3 62
20.5%
4 57
18.9%
5 8
 
2.6%
6 3
 
1.0%
7 1
 
0.3%
9 1
 
0.3%
10 1
 
0.3%
22 1
 
0.3%
ValueCountFrequency (%)
22 1
 
0.3%
10 1
 
0.3%
9 1
 
0.3%
7 1
 
0.3%
6 3
 
1.0%
5 8
 
2.6%
4 57
18.9%
3 62
20.5%
2 94
31.1%
1 74
24.5%

지하층수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
0
210 
<NA>
43 
1
43 
2
 
5
4
 
1

Length

Max length4
Median length1
Mean length1.4271523
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row0
2nd row0
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 210
69.5%
<NA> 43
 
14.2%
1 43
 
14.2%
2 5
 
1.7%
4 1
 
0.3%

Length

2023-12-13T00:07:21.322919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:07:21.467689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 210
69.5%
na 43
 
14.2%
1 43
 
14.2%
2 5
 
1.7%
4 1
 
0.3%

주용도
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
단독주택
82 
제2종근린생활시설
77 
제1종근린생활시설
43 
공장
24 
창고시설
20 
Other values (14)
56 

Length

Max length10
Median length9
Mean length6.0463576
Min length2

Unique

Unique6 ?
Unique (%)2.0%

Sample

1st row동물및식물관련시설
2nd row제2종근린생활시설
3rd row제2종근린생활시설
4th row단독주택
5th row제2종근린생활시설

Common Values

ValueCountFrequency (%)
단독주택 82
27.2%
제2종근린생활시설 77
25.5%
제1종근린생활시설 43
14.2%
공장 24
 
7.9%
창고시설 20
 
6.6%
공동주택 15
 
5.0%
동물및식물관련시설 9
 
3.0%
종교시설 9
 
3.0%
업무시설 7
 
2.3%
운동시설 4
 
1.3%
Other values (9) 12
 
4.0%

Length

2023-12-13T00:07:21.627950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독주택 82
27.2%
제2종근린생활시설 77
25.5%
제1종근린생활시설 43
14.2%
공장 24
 
7.9%
창고시설 20
 
6.6%
공동주택 15
 
5.0%
동물및식물관련시설 9
 
3.0%
종교시설 9
 
3.0%
업무시설 7
 
2.3%
운동시설 4
 
1.3%
Other values (9) 12
 
4.0%

부속용도
Text

MISSING 

Distinct134
Distinct (%)60.1%
Missing79
Missing (%)26.2%
Memory size2.5 KiB
2023-12-13T00:07:21.931308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length22
Mean length7.6816143
Min length2

Characters and Unicode

Total characters1713
Distinct characters138
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)49.3%

Sample

1st row온실
2nd row일반음식점,사무소
3rd row주택,주차장
4th row자동차수리점,사무소
5th row및 농가창고
ValueCountFrequency (%)
다가구주택 26
 
9.7%
소매점 17
 
6.4%
제조업소 17
 
6.4%
및 15
 
5.6%
사무소 11
 
4.1%
주택 6
 
2.2%
다가구주택및제1종근린생활시설 6
 
2.2%
단독주택 6
 
2.2%
일반음식점 5
 
1.9%
다세대주택 5
 
1.9%
Other values (121) 153
57.3%
2023-12-13T00:07:22.364929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 87
 
5.1%
주 80
 
4.7%
택 76
 
4.4%
, 65
 
3.8%
시 62
 
3.6%
설 57
 
3.3%
점 55
 
3.2%
사 54
 
3.2%
제 52
 
3.0%
다 48
 
2.8%
Other values (128) 1077
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1475
86.1%
Other Punctuation 74
 
4.3%
Space Separator 45
 
2.6%
Decimal Number 42
 
2.5%
Close Punctuation 38
 
2.2%
Open Punctuation 37
 
2.2%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 87
 
5.9%
주 80
 
5.4%
택 76
 
5.2%
시 62
 
4.2%
설 57
 
3.9%
점 55
 
3.7%
사 54
 
3.7%
제 52
 
3.5%
다 48
 
3.3%
가 47
 
3.2%
Other values (116) 857
58.1%
Decimal Number
ValueCountFrequency (%)
1 25
59.5%
2 12
28.6%
8 3
 
7.1%
0 1
 
2.4%
6 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
, 65
87.8%
/ 7
 
9.5%
. 2
 
2.7%
Space Separator
ValueCountFrequency (%)
45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1475
86.1%
Common 238
 
13.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 87
 
5.9%
주 80
 
5.4%
택 76
 
5.2%
시 62
 
4.2%
설 57
 
3.9%
점 55
 
3.7%
사 54
 
3.7%
제 52
 
3.5%
다 48
 
3.3%
가 47
 
3.2%
Other values (116) 857
58.1%
Common
ValueCountFrequency (%)
, 65
27.3%
45
18.9%
) 38
16.0%
( 37
15.5%
1 25
 
10.5%
2 12
 
5.0%
/ 7
 
2.9%
8 3
 
1.3%
. 2
 
0.8%
- 2
 
0.8%
Other values (2) 2
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1475
86.1%
ASCII 238
 
13.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 87
 
5.9%
주 80
 
5.4%
택 76
 
5.2%
시 62
 
4.2%
설 57
 
3.9%
점 55
 
3.7%
사 54
 
3.7%
제 52
 
3.5%
다 48
 
3.3%
가 47
 
3.2%
Other values (116) 857
58.1%
ASCII
ValueCountFrequency (%)
, 65
27.3%
45
18.9%
) 38
16.0%
( 37
15.5%
1 25
 
10.5%
2 12
 
5.0%
/ 7
 
2.9%
8 3
 
1.3%
. 2
 
0.8%
- 2
 
0.8%
Other values (2) 2
 
0.8%

Interactions

2023-12-13T00:07:15.248467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:12.258403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:13.098298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:13.667804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:14.255186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:14.762450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:15.353733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:12.383237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:13.194082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:13.761327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:14.355580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:14.862582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:15.432168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:12.482419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:13.293302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:13.865409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:14.442722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:14.942156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:15.539872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:12.574008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:13.411768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:13.954348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:14.523495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:15.022963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:15.668999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:12.932562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:13.504725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:14.047213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:14.607478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:15.102551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:15.787485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:13.009113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:13.581672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:14.149709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:14.682989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:07:15.170890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:07:22.493364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축구분대지면적건축면적연면적건폐율용적률지상층수지하층수주용도
건축구분1.0000.3020.5650.3460.4030.2280.3190.4500.530
대지면적0.3021.0000.4960.8120.5300.0000.0000.0000.691
건축면적0.5650.4961.0000.8750.3320.0000.1040.5740.704
연면적0.3460.8120.8751.0000.3170.5820.4140.8620.700
건폐율0.4030.5300.3320.3171.0000.6620.3780.0000.552
용적률0.2280.0000.0000.5820.6621.0000.8370.6280.596
지상층수0.3190.0000.1040.4140.3780.8371.0000.4500.697
지하층수0.4500.0000.5740.8620.0000.6280.4501.0000.842
주용도0.5300.6910.7040.7000.5520.5960.6970.8421.000
2023-12-13T00:07:22.628668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주용도지하층수건축구분
주용도1.0000.5380.459
지하층수0.5381.0000.302
건축구분0.4590.3021.000
2023-12-13T00:07:22.732074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대지면적건축면적연면적건폐율용적률지상층수건축구분지하층수주용도
대지면적1.0000.8920.769-0.359-0.421-0.2030.2000.0000.445
건축면적0.8921.0000.8880.039-0.117-0.1140.4310.4030.347
연면적0.7690.8881.0000.1080.1690.2580.2570.5370.378
건폐율-0.3590.0390.1081.0000.7960.2770.3050.0000.238
용적률-0.421-0.1170.1690.7961.0000.7170.1690.3190.293
지상층수-0.203-0.1140.2580.2770.7171.0000.2280.3040.404
건축구분0.2000.4310.2570.3050.1690.2281.0000.3020.459
지하층수0.0000.4030.5370.0000.3190.3040.3021.0000.538
주용도0.4450.3470.3780.2380.2930.4040.4590.5381.000

Missing values

2023-12-13T00:07:15.911385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:07:16.083400image/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.
2023-12-13T00:07:16.188878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

건축구분건물명소재지지번주소대지면적건축면적연면적건폐율용적률사용승인일건축허가일지상층수지하층수주용도부속용도
0신축온실경기도 여주시 북내면 지내리 560-13937.02311.382311.3858.7158.712023-06-292023-02-1510동물및식물관련시설온실
1신축오학동 426-8 제2종근린생활시설경기도 여주시 오학동 426-8364.9165.89165.8945.4645.462023-05-082022-11-0910제2종근린생활시설<NA>
2증축월송동 345-37 제2종근린생활시설 증축공사경기도 여주시 월송동 345-37397.0137.7254.5234.6964.112022-12-142022-10-112<NA>제2종근린생활시설일반음식점,사무소
3증축흥천면 대당리 125-41경기도 여주시 흥천면 대당리 125-41829.0198.2439.4423.9142.32023-02-012022-09-292<NA>단독주택주택,주차장
4신축상동 139 제2종근린생활시설경기도 여주시 상동 139282.3160.0192.056.6868.012023-01-312022-09-2920제2종근린생활시설자동차수리점,사무소
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6신축<NA>경기도 여주시 가남읍 태평리 87-1660.0124.54102.118.8715.472023-06-302022-09-1510단독주택<NA>
7신축상동 483-1 제1종근린생활시설경기도 여주시 상동 483-1447.081.9193.5918.3243.312023-05-232022-09-1430제1종근린생활시설휴게음식점(단독주택)
8신축현암동 153-9 제2종근린생활시설경기도 여주시 현암동 153-9 외1필지149.081.73163.4654.85109.72023-03-312022-09-0820제1종근린생활시설휴게음식점
9증축가남읍 심석리 99-2 제2종근린생활시설경기도 여주시 가남읍 심석리 99-22172.0803.781048.2737.0148.262023-02-032022-08-312<NA>제2종근린생활시설소매점,골프연습장
건축구분건물명소재지지번주소대지면적건축면적연면적건폐율용적률사용승인일건축허가일지상층수지하층수주용도부속용도
292신축가남읍 태평리 773-8 근생경기도 여주시 가남읍 태평리 773-8364.0207.65328.6557.0590.292022-04-182017-01-0220제1종근린생활시설1/2종근린생활시설(소매점/사무소)
293신축.경기도 여주시 대신면 율촌리 276-13620.0123.72190.4419.9625.882023-02-162016-03-1521단독주택<NA>
294증축오학동 118 동.식물관련시설경기도 여주시 오학동 1186522.02526.752689.938.7441.242022-12-142016-02-052<NA>동물및식물관련시설콩나물재배사
295신축상동 90-2 제1,2종근린생활시설경기도 여주시 상동 90-2989.0150.02747.1715.1756.82023-01-062015-10-2741제2종근린생활시설사무소,휴게음식점
296신축케이투코리아 여주 물류센터 1차경기도 여주시 가남읍 본두리 91425340.010369.1139846.8240.9199118.19742022-12-292014-07-2441창고시설물류창고
297신축<NA>경기도 여주시 상동 64-11420.082.17182.1519.5636.062022-11-212014-04-0121단독주택<NA>
298증축가남면 삼군리 230-4 공장경기도 여주시 가남읍 삼군리 230-4 외4필지14085.03515.914736.6124.9633.632023-03-232013-03-291<NA>공장<NA>
299신축산북면 상품리 516-3 종교시설경기도 여주시 산북면 상품리 516-31504.0431.22610.628.671540.59842023-05-102012-08-1630종교시설<NA>
300증축북내면 주암리 210-1 제1종근린생활시설경기도 여주시 북내면 주암리 210-1 외1필지672.0144.25249.0521.4737.062022-11-082010-04-221<NA>제1종근린생활시설마을회관,경노당,회의실
301신축천송동 427-17 제2종근린생활시설경기도 여주시 천송동 427-17825.0212.1314.7225.7138.152022-11-232007-09-1420제2종근린생활시설일반음식점,사무실