Overview

Dataset statistics

Number of variables21
Number of observations244
Missing cells27
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory41.8 KiB
Average record size in memory175.5 B

Variable types

Numeric6
Categorical9
Text2
DateTime4

Dataset

Description인천광역시 남동구 도시형생활주택 인허가 현황에 대한 데이터로 사업명, 소재지, 세대수, 승인일 항목을 제공합니다.
Author인천광역시 남동구
URLhttps://www.data.go.kr/data/3078182/fileData.do

Alerts

시군구명 has constant value ""Constant
지목 is highly imbalanced (96.2%)Imbalance
용도지구 is highly imbalanced (60.3%)Imbalance
용도구역 is highly imbalanced (59.4%)Imbalance
동수 is highly imbalanced (61.0%)Imbalance
건축허가_사업계획승인 is highly imbalanced (96.2%)Imbalance
사용검사(사용승인)일 has 26 (10.7%) missing valuesMissing
연번 has unique valuesUnique
지번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:22:19.944813
Analysis finished2023-12-12 10:22:20.233954
Duration0.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct244
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.5
Minimum1
Maximum244
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T19:22:20.318449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.15
Q161.75
median122.5
Q3183.25
95-th percentile231.85
Maximum244
Range243
Interquartile range (IQR)121.5

Descriptive statistics

Standard deviation70.580923
Coefficient of variation (CV)0.5761708
Kurtosis-1.2
Mean122.5
Median Absolute Deviation (MAD)61
Skewness0
Sum29890
Variance4981.6667
MonotonicityStrictly increasing
2023-12-12T19:22:20.477376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
155 1
 
0.4%
157 1
 
0.4%
158 1
 
0.4%
159 1
 
0.4%
160 1
 
0.4%
161 1
 
0.4%
162 1
 
0.4%
163 1
 
0.4%
164 1
 
0.4%
Other values (234) 234
95.9%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
244 1
0.4%
243 1
0.4%
242 1
0.4%
241 1
0.4%
240 1
0.4%
239 1
0.4%
238 1
0.4%
237 1
0.4%
236 1
0.4%
235 1
0.4%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
인천광역시 남동구청
244 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인천광역시 남동구청
2nd row인천광역시 남동구청
3rd row인천광역시 남동구청
4th row인천광역시 남동구청
5th row인천광역시 남동구청

Common Values

ValueCountFrequency (%)
인천광역시 남동구청 244
100.0%

Length

2023-12-12T19:22:20.618940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:22:20.729029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 244
50.0%
남동구청 244
50.0%

대지위치
Categorical

Distinct7
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
구월동
90 
간석동
83 
만수동
38 
서창동
20 
장수동
10 
Other values (2)
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row간석동
2nd row간석동
3rd row구월동
4th row구월동
5th row간석동

Common Values

ValueCountFrequency (%)
구월동 90
36.9%
간석동 83
34.0%
만수동 38
15.6%
서창동 20
 
8.2%
장수동 10
 
4.1%
남촌동 2
 
0.8%
도림동 1
 
0.4%

Length

2023-12-12T19:22:20.832539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:22:20.952696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구월동 90
36.9%
간석동 83
34.0%
만수동 38
15.6%
서창동 20
 
8.2%
장수동 10
 
4.1%
남촌동 2
 
0.8%
도림동 1
 
0.4%

지번
Text

UNIQUE 

Distinct244
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-12T19:22:21.340567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10.5
Mean length7.3237705
Min length3

Characters and Unicode

Total characters1787
Distinct characters27
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique244 ?
Unique (%)100.0%

Sample

1st row250-1
2nd row122-26
3rd row1143-34
4th row1210-2
5th row125-3
ValueCountFrequency (%)
외1필지 35
 
10.2%
외 17
 
5.0%
외3필지 14
 
4.1%
1 6
 
1.7%
외1 6
 
1.7%
2 5
 
1.5%
외2필지 4
 
1.2%
3 3
 
0.9%
외1필 2
 
0.6%
107-4 1
 
0.3%
Other values (250) 250
72.9%
2023-12-12T19:22:21.887783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 336
18.8%
- 231
12.9%
2 148
 
8.3%
106
 
5.9%
3 103
 
5.8%
8 99
 
5.5%
0 98
 
5.5%
5 98
 
5.5%
7 96
 
5.4%
외 94
 
5.3%
Other values (17) 378
21.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1205
67.4%
Other Letter 238
 
13.3%
Dash Punctuation 231
 
12.9%
Space Separator 106
 
5.9%
Uppercase Letter 3
 
0.2%
Lowercase Letter 2
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 336
27.9%
2 148
12.3%
3 103
 
8.5%
8 99
 
8.2%
0 98
 
8.1%
5 98
 
8.1%
7 96
 
8.0%
4 87
 
7.2%
9 78
 
6.5%
6 62
 
5.1%
Other Letter
ValueCountFrequency (%)
외 94
39.5%
필 70
29.4%
지 69
29.0%
월 1
 
0.4%
일 1
 
0.4%
번 1
 
0.4%
도 1
 
0.4%
생 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
L 1
33.3%
J 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
a 1
50.0%
n 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 231
100.0%
Space Separator
ValueCountFrequency (%)
106
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1544
86.4%
Hangul 238
 
13.3%
Latin 5
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 336
21.8%
- 231
15.0%
2 148
9.6%
106
 
6.9%
3 103
 
6.7%
8 99
 
6.4%
0 98
 
6.3%
5 98
 
6.3%
7 96
 
6.2%
4 87
 
5.6%
Other values (4) 142
9.2%
Hangul
ValueCountFrequency (%)
외 94
39.5%
필 70
29.4%
지 69
29.0%
월 1
 
0.4%
일 1
 
0.4%
번 1
 
0.4%
도 1
 
0.4%
생 1
 
0.4%
Latin
ValueCountFrequency (%)
B 1
20.0%
L 1
20.0%
J 1
20.0%
a 1
20.0%
n 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1549
86.7%
Hangul 238
 
13.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 336
21.7%
- 231
14.9%
2 148
9.6%
106
 
6.8%
3 103
 
6.6%
8 99
 
6.4%
0 98
 
6.3%
5 98
 
6.3%
7 96
 
6.2%
4 87
 
5.6%
Other values (9) 147
9.5%
Hangul
ValueCountFrequency (%)
외 94
39.5%
필 70
29.4%
지 69
29.0%
월 1
 
0.4%
일 1
 
0.4%
번 1
 
0.4%
도 1
 
0.4%
생 1
 
0.4%

지목
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
대
243 
임야
 
1

Length

Max length2
Median length1
Mean length1.0040984
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
대 243
99.6%
임야 1
 
0.4%

Length

2023-12-12T19:22:22.056463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:22:22.162191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대 243
99.6%
임야 1
 
0.4%

대지면적
Real number (ℝ)

Distinct238
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean520.77336
Minimum139.9
Maximum3011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T19:22:22.588823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum139.9
5-th percentile206.575
Q1281.75
median424.75
Q3660.725
95-th percentile1141.255
Maximum3011
Range2871.1
Interquartile range (IQR)378.975

Descriptive statistics

Standard deviation336.60714
Coefficient of variation (CV)0.64636013
Kurtosis14.211309
Mean520.77336
Median Absolute Deviation (MAD)154.75
Skewness2.8087471
Sum127068.7
Variance113304.37
MonotonicityNot monotonic
2023-12-12T19:22:22.787161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
269.0 2
 
0.8%
245.0 2
 
0.8%
363.2 2
 
0.8%
276.8 2
 
0.8%
327.9 2
 
0.8%
424.0 2
 
0.8%
207.0 1
 
0.4%
432.1 1
 
0.4%
460.0 1
 
0.4%
282.0 1
 
0.4%
Other values (228) 228
93.4%
ValueCountFrequency (%)
139.9 1
0.4%
140.0 1
0.4%
142.8 1
0.4%
147.0 1
0.4%
154.1 1
0.4%
170.8 1
0.4%
176.2 1
0.4%
176.5 1
0.4%
180.3 1
0.4%
182.0 1
0.4%
ValueCountFrequency (%)
3011.0 1
0.4%
2190.0 1
0.4%
1663.1 1
0.4%
1409.4 1
0.4%
1388.8 1
0.4%
1322.7 1
0.4%
1317.1 1
0.4%
1285.0 1
0.4%
1222.3 1
0.4%
1199.3 1
0.4%

용도지역
Categorical

Distinct9
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
제2종일반주거지역
136 
일반상업지역
63 
준주거지역
29 
제1종일반주거지역
 
9
일반주거지역
 
2
Other values (4)
 
5

Length

Max length9
Median length9
Mean length7.6639344
Min length4

Unique

Unique3 ?
Unique (%)1.2%

Sample

1st row일반상업지역
2nd row일반상업지역
3rd row일반상업지역
4th row제2종일반주거지역
5th row일반상업지역

Common Values

ValueCountFrequency (%)
제2종일반주거지역 136
55.7%
일반상업지역 63
25.8%
준주거지역 29
 
11.9%
제1종일반주거지역 9
 
3.7%
일반주거지역 2
 
0.8%
<NA> 2
 
0.8%
제2종전용주거지역 1
 
0.4%
제3종일반주거지역 1
 
0.4%
도시지역 1
 
0.4%

Length

2023-12-12T19:22:22.960424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:22:23.087175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제2종일반주거지역 136
55.7%
일반상업지역 63
25.8%
준주거지역 29
 
11.9%
제1종일반주거지역 9
 
3.7%
일반주거지역 2
 
0.8%
na 2
 
0.8%
제2종전용주거지역 1
 
0.4%
제3종일반주거지역 1
 
0.4%
도시지역 1
 
0.4%

용도지구
Categorical

IMBALANCE 

Distinct8
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
183 
방화지구
40 
중심지미관지구
 
13
일반미관지구
 
4
중심미관지구 방화지구
 
1
Other values (3)
 
3

Length

Max length11
Median length4
Mean length4.2336066
Min length1

Unique

Unique4 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 183
75.0%
방화지구 40
 
16.4%
중심지미관지구 13
 
5.3%
일반미관지구 4
 
1.6%
중심미관지구 방화지구 1
 
0.4%
- 1
 
0.4%
보금자리주택지구 1
 
0.4%
철도보호지구 1
 
0.4%

Length

2023-12-12T19:22:23.250304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:22:23.404047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 183
74.7%
방화지구 41
 
16.7%
중심지미관지구 13
 
5.3%
일반미관지구 4
 
1.6%
중심미관지구 1
 
0.4%
1
 
0.4%
보금자리주택지구 1
 
0.4%
철도보호지구 1
 
0.4%

용도구역
Categorical

IMBALANCE 

Distinct7
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
182 
제1종지구단위계획구역
44 
상대정화구역
 
13
상대보호구역
 
2
-
 
1
Other values (2)
 
2

Length

Max length11
Median length4
Mean length5.397541
Min length1

Unique

Unique3 ?
Unique (%)1.2%

Sample

1st row<NA>
2nd row<NA>
3rd row제1종지구단위계획구역
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 182
74.6%
제1종지구단위계획구역 44
 
18.0%
상대정화구역 13
 
5.3%
상대보호구역 2
 
0.8%
- 1
 
0.4%
지구단위계획구역 1
 
0.4%
절대정화구역 1
 
0.4%

Length

2023-12-12T19:22:23.555292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:22:23.691220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 182
74.6%
제1종지구단위계획구역 44
 
18.0%
상대정화구역 13
 
5.3%
상대보호구역 2
 
0.8%
1
 
0.4%
지구단위계획구역 1
 
0.4%
절대정화구역 1
 
0.4%

건축면적
Real number (ℝ)

Distinct231
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean316.71698
Minimum82.85
Maximum1333.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T19:22:23.847272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum82.85
5-th percentile128.5515
Q1174.96
median248.625
Q3399.185
95-th percentile725.823
Maximum1333.41
Range1250.56
Interquartile range (IQR)224.225

Descriptive statistics

Standard deviation203.55404
Coefficient of variation (CV)0.6427001
Kurtosis5.5371758
Mean316.71698
Median Absolute Deviation (MAD)89.9
Skewness2.0321459
Sum77278.944
Variance41434.246
MonotonicityNot monotonic
2023-12-12T19:22:24.034732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
167.61 3
 
1.2%
179.2 2
 
0.8%
295.68 2
 
0.8%
176.01 2
 
0.8%
157.3 2
 
0.8%
428.26 2
 
0.8%
249.12 2
 
0.8%
384.7 2
 
0.8%
246.8 2
 
0.8%
160.92 2
 
0.8%
Other values (221) 223
91.4%
ValueCountFrequency (%)
82.85 1
0.4%
83.16 1
0.4%
83.52 1
0.4%
88.02 1
0.4%
91.1 1
0.4%
101.28 1
0.4%
107.3 1
0.4%
107.8 1
0.4%
119.94 1
0.4%
123.27 1
0.4%
ValueCountFrequency (%)
1333.41 1
0.4%
1305.99 1
0.4%
1064.64 1
0.4%
1055.66 1
0.4%
924.15 1
0.4%
900.21 1
0.4%
898.99 1
0.4%
831.0615 1
0.4%
775.4 1
0.4%
769.44 1
0.4%

연면적
Real number (ℝ)

Distinct233
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2120.5786
Minimum272.52
Maximum19437.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T19:22:24.206349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum272.52
5-th percentile454.068
Q1659.5275
median1124.425
Q31949.96
95-th percentile9037.2945
Maximum19437.01
Range19164.49
Interquartile range (IQR)1290.4325

Descriptive statistics

Standard deviation2903.8418
Coefficient of variation (CV)1.3693629
Kurtosis10.726541
Mean2120.5786
Median Absolute Deviation (MAD)469.445
Skewness3.1111798
Sum517421.19
Variance8432297.1
MonotonicityNot monotonic
2023-12-12T19:22:24.394284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
586.91 3
 
1.2%
573.35 2
 
0.8%
1280.05 2
 
0.8%
998.69 2
 
0.8%
1319.1 2
 
0.8%
774.99 2
 
0.8%
597.64 2
 
0.8%
1283.78 2
 
0.8%
986.87 2
 
0.8%
450.72 2
 
0.8%
Other values (223) 223
91.4%
ValueCountFrequency (%)
272.52 1
0.4%
299.13 1
0.4%
318.53 1
0.4%
348.72 1
0.4%
356.35 1
0.4%
374.34 1
0.4%
401.045 1
0.4%
417.5 1
0.4%
418.47 1
0.4%
420.08 1
0.4%
ValueCountFrequency (%)
19437.01 1
0.4%
15707.26 1
0.4%
15149.72 1
0.4%
13422.12 1
0.4%
12967.05 1
0.4%
12229.92 1
0.4%
11536.58 1
0.4%
10972.21 1
0.4%
10958.39 1
0.4%
9961.48 1
0.4%

동수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
1
206 
2
29 
3
 
6
0
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 206
84.4%
2 29
 
11.9%
3 6
 
2.5%
0 3
 
1.2%

Length

2023-12-12T19:22:24.580018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:22:24.717772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 206
84.4%
2 29
 
11.9%
3 6
 
2.5%
0 3
 
1.2%

유형
Categorical

Distinct9
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
원룸형
116 
단지형다세대
88 
단지형연립
19 
단지형
 
6
단지형연립주택
 
6
Other values (4)
 
9

Length

Max length8
Median length7.5
Mean length4.442623
Min length3

Unique

Unique2 ?
Unique (%)0.8%

Sample

1st row단지형연립
2nd row원룸형
3rd row원룸형
4th row원룸형
5th row단지형다세대

Common Values

ValueCountFrequency (%)
원룸형 116
47.5%
단지형다세대 88
36.1%
단지형연립 19
 
7.8%
단지형 6
 
2.5%
단지형연립주택 6
 
2.5%
연립주택 4
 
1.6%
단지형 연립주택 3
 
1.2%
원룸형다세대 1
 
0.4%
도시형생활주택 1
 
0.4%

Length

2023-12-12T19:22:24.891058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:22:25.053803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원룸형 116
47.0%
단지형다세대 88
35.6%
단지형연립 19
 
7.7%
단지형 9
 
3.6%
연립주택 7
 
2.8%
단지형연립주택 6
 
2.4%
원룸형다세대 1
 
0.4%
도시형생활주택 1
 
0.4%

용도
Text

Distinct55
Distinct (%)22.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-12T19:22:25.313154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length8.3934426
Min length3

Characters and Unicode

Total characters2048
Distinct characters44
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

Unique36 ?
Unique (%)14.8%

Sample

1st row업무시설 및 도시형생활주택
2nd row업무시설 및 도시형생활주택
3rd row공동주택 업무시설 근린생활시설
4th row공동주택
5th row근린생활시설 공동주택
ValueCountFrequency (%)
다세대주택 94
27.1%
도시형생활주택 47
13.5%
공동주택 37
 
10.7%
아파트 30
 
8.6%
근린생활시설 20
 
5.8%
연립주택 17
 
4.9%
및 17
 
4.9%
업무시설 14
 
4.0%
다세대주택(도시형생활주택 12
 
3.5%
오피스텔 11
 
3.2%
Other values (20) 48
13.8%
2023-12-12T19:22:25.749650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 243
 
11.9%
택 243
 
11.9%
127
 
6.2%
시 120
 
5.9%
다 115
 
5.6%
대 115
 
5.6%
세 115
 
5.6%
생 112
 
5.5%
활 104
 
5.1%
형 86
 
4.2%
Other values (34) 668
32.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1824
89.1%
Space Separator 127
 
6.2%
Open Punctuation 40
 
2.0%
Close Punctuation 40
 
2.0%
Decimal Number 15
 
0.7%
Dash Punctuation 1
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 243
13.3%
택 243
13.3%
시 120
 
6.6%
다 115
 
6.3%
대 115
 
6.3%
세 115
 
6.3%
생 112
 
6.1%
활 104
 
5.7%
형 86
 
4.7%
도 76
 
4.2%
Other values (27) 495
27.1%
Decimal Number
ValueCountFrequency (%)
2 11
73.3%
1 4
 
26.7%
Space Separator
ValueCountFrequency (%)
127
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1824
89.1%
Common 224
 
10.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 243
13.3%
택 243
13.3%
시 120
 
6.6%
다 115
 
6.3%
대 115
 
6.3%
세 115
 
6.3%
생 112
 
6.1%
활 104
 
5.7%
형 86
 
4.7%
도 76
 
4.2%
Other values (27) 495
27.1%
Common
ValueCountFrequency (%)
127
56.7%
( 40
 
17.9%
) 40
 
17.9%
2 11
 
4.9%
1 4
 
1.8%
- 1
 
0.4%
_ 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1824
89.1%
ASCII 224
 
10.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 243
13.3%
택 243
13.3%
시 120
 
6.6%
다 115
 
6.3%
대 115
 
6.3%
세 115
 
6.3%
생 112
 
6.1%
활 104
 
5.7%
형 86
 
4.7%
도 76
 
4.2%
Other values (27) 495
27.1%
ASCII
ValueCountFrequency (%)
127
56.7%
( 40
 
17.9%
) 40
 
17.9%
2 11
 
4.9%
1 4
 
1.8%
- 1
 
0.4%
_ 1
 
0.4%

세대수
Real number (ℝ)

Distinct57
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.02459
Minimum4
Maximum244
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T19:22:25.976016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile8
Q111
median16
Q326.25
95-th percentile97.7
Maximum244
Range240
Interquartile range (IQR)15.25

Descriptive statistics

Standard deviation34.998169
Coefficient of variation (CV)1.2488378
Kurtosis14.441744
Mean28.02459
Median Absolute Deviation (MAD)8
Skewness3.501298
Sum6838
Variance1224.8718
MonotonicityNot monotonic
2023-12-12T19:22:26.190523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 46
18.9%
16 30
 
12.3%
12 23
 
9.4%
24 19
 
7.8%
20 13
 
5.3%
10 9
 
3.7%
28 9
 
3.7%
14 6
 
2.5%
11 6
 
2.5%
19 6
 
2.5%
Other values (47) 77
31.6%
ValueCountFrequency (%)
4 1
 
0.4%
8 46
18.9%
9 1
 
0.4%
10 9
 
3.7%
11 6
 
2.5%
12 23
9.4%
13 4
 
1.6%
14 6
 
2.5%
15 5
 
2.0%
16 30
12.3%
ValueCountFrequency (%)
244 1
0.4%
240 1
0.4%
182 1
0.4%
168 1
0.4%
149 1
0.4%
144 1
0.4%
143 1
0.4%
130 1
0.4%
126 1
0.4%
125 1
0.4%

세대별 전용면적
Real number (ℝ)

Distinct231
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.380169
Minimum12
Maximum80.994
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T19:22:26.349874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile14.3475
Q130.255
median46.09
Q355.625
95-th percentile69.0215
Maximum80.994
Range68.994
Interquartile range (IQR)25.37

Descriptive statistics

Standard deviation17.156558
Coefficient of variation (CV)0.39549311
Kurtosis-0.80043896
Mean43.380169
Median Absolute Deviation (MAD)12.28
Skewness-0.16921328
Sum10584.761
Variance294.34748
MonotonicityNot monotonic
2023-12-12T19:22:26.529210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49.86 3
 
1.2%
43.17 3
 
1.2%
53.78 3
 
1.2%
65.43 2
 
0.8%
22.54 2
 
0.8%
42.67 2
 
0.8%
64.36 2
 
0.8%
58.93 2
 
0.8%
16.5 2
 
0.8%
38.37 2
 
0.8%
Other values (221) 221
90.6%
ValueCountFrequency (%)
12.0 1
0.4%
12.19 1
0.4%
12.22 1
0.4%
12.3 1
0.4%
12.37 1
0.4%
13.1 1
0.4%
13.25 1
0.4%
13.3 1
0.4%
13.45 1
0.4%
13.5 1
0.4%
ValueCountFrequency (%)
80.994 1
0.4%
78.78 1
0.4%
78.53 1
0.4%
76.99 1
0.4%
74.81 1
0.4%
74.48 1
0.4%
74.11 1
0.4%
72.96 1
0.4%
72.46 1
0.4%
72.18 1
0.4%

건축허가_사업계획승인
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
건축허가
243 
사업계획승인
 
1

Length

Max length6
Median length4
Mean length4.0081967
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
건축허가 243
99.6%
사업계획승인 1
 
0.4%

Length

2023-12-12T19:22:26.697008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:22:26.841880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건축허가 243
99.6%
사업계획승인 1
 
0.4%

인허가 신청일
Date

Distinct192
Distinct (%)78.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2002-04-26 00:00:00
Maximum2019-09-24 00:00:00
2023-12-12T19:22:26.977169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:22:27.154121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가일
Date

Distinct197
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2002-05-08 00:00:00
Maximum2019-10-17 00:00:00
2023-12-12T19:22:27.336229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:22:27.520942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공일
Date

Distinct201
Distinct (%)82.7%
Missing1
Missing (%)0.4%
Memory size2.0 KiB
Minimum2003-08-22 00:00:00
Maximum2019-11-06 00:00:00
2023-12-12T19:22:27.712971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:22:27.900859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사용검사(사용승인)일
Date

MISSING 

Distinct180
Distinct (%)82.6%
Missing26
Missing (%)10.7%
Memory size2.0 KiB
Minimum2007-01-08 00:00:00
Maximum2019-12-11 00:00:00
2023-12-12T19:22:28.061224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:22:28.284276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Sample

연번시군구명대지위치지번지목대지면적용도지역용도지구용도구역건축면적연면적동수유형용도세대수세대별 전용면적건축허가_사업계획승인인허가 신청일인허가일착공일사용검사(사용승인)일
01인천광역시 남동구청간석동250-1대1663.1일반상업지역중심지미관지구<NA>1305.9919437.011단지형연립업무시설 및 도시형생활주택5612.0건축허가2002-04-262002-05-082004-05-282007-03-23
12인천광역시 남동구청간석동122-26대259.3일반상업지역<NA><NA>203.691400.91원룸형업무시설 및 도시형생활주택1021.0건축허가2003-07-292003-08-052003-08-222007-01-08
23인천광역시 남동구청구월동1143-34대898.3일반상업지역중심지미관지구제1종지구단위계획구역566.349113.821원룸형공동주택 업무시설 근린생활시설12518.44건축허가2009-01-062009-01-162009-02-162014-02-27
34인천광역시 남동구청구월동1210-2대269.6제2종일반주거지역<NA><NA>157.45601.61원룸형공동주택2415.02건축허가2010-07-132010-07-272010-08-022011-01-10
45인천광역시 남동구청간석동125-3대199.3일반상업지역방화지구<NA>138.75810.571단지형다세대근린생활시설 공동주택1515.87건축허가2010-07-232010-08-122010-08-132011-06-22
56인천광역시 남동구청만수동871-26대303.3준주거지역<NA><NA>179.011164.651원룸형다세대주택 (도시형생활주택) 및 오피스텔2816.5건축허가2010-08-092010-08-272010-10-072011-06-08
67인천광역시 남동구청만수동871-25대301.5준주거지역<NA><NA>179.011168.611원룸형다세대주택 (도시형생활주택) 및 오피스텔2816.5건축허가2010-08-102010-08-272010-10-072011-06-08
78인천광역시 남동구청간석동176-3대176.2일반상업지역방화지구<NA>119.94523.581원룸형다세대주택 (도시형생활주택) 및 근린생활시설2513.3건축허가2010-08-252010-09-072010-09-202011-01-14
89인천광역시 남동구청간석동280-7대327.9준주거지역<NA><NA>192.861282.81원룸형다세대주택 (도시형생활주택) 및 오피스텔2815.85건축허가2010-09-022010-09-202010-10-252011-07-12
910인천광역시 남동구청간석동169-14대201.0일반상업지역방화지구<NA>143.53639.861원룸형근린생활시설1912.3건축허가2010-10-222010-11-052011-03-152011-10-12
연번시군구명대지위치지번지목대지면적용도지역용도지구용도구역건축면적연면적동수유형용도세대수세대별 전용면적건축허가_사업계획승인인허가 신청일인허가일착공일사용검사(사용승인)일
234235인천광역시 남동구청구월동4-95대264.7제2종일반주거지역<NA><NA>156.75638.461단지형다세대도시형생활주택872.96건축허가2019-02-212019-03-142019-03-202019-06-19
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236237인천광역시 남동구청간석동579-6대861.3제2종일반주거지역<NA><NA>516.241997.261단지형 연립주택도시형생활주택2863.85건축허가2019-02-142019-03-072019-03-192019-07-17
237238인천광역시 남동구청간석동579대849.6제2종일반주거지역<NA><NA>508.972047.271단지형 연립주택도시형생활주택2878.78건축허가2019-02-112019-03-072019-03-192019-07-17
238239인천광역시 남동구청간석동579-5대846.8제2종일반주거지역<NA><NA>506.661977.141단지형 연립주택도시형생활주택2764.38건축허가2019-02-082019-03-072019-03-152019-07-17
239240인천광역시 남동구청간석동579-4대856.5제2종일반주거지역<NA><NA>512.341977.631단지형연립주택도시형생활주택2772.18건축허가2019-02-082019-03-072019-03-192019-07-17
240241인천광역시 남동구청만수동1088-2 외1필대626.4제2종일반주거지역<NA>제1종지구단위계획구역373.781219.12단지형다세대도시형생활주택2054.9118건축허가2019-02-202019-03-072019-05-01<NA>
241242인천광역시 남동구청간석동253-29 외1필대606.3제2종일반주거지역<NA><NA>363.421309.972단지형다세대도시형생활주택1671.19건축허가2019-02-112019-02-282019-03-182019-07-19
242243인천광역시 남동구청구월동3-26 외3필지대574.3제2종일반주거지역<NA><NA>338.921221.162단지형다세대도시형생활주택1680.994건축허가2019-02-132019-02-282019-07-11<NA>
243244인천광역시 남동구청만수동900-2 외1필지대914.4제2종일반주거지역<NA>상대보호구역548.352143.281도시형생활주택도시형생활주택3149.0207건축허가2019-01-282019-02-112019-02-212019-07-05