Overview

Dataset statistics

Number of variables49
Number of observations214
Missing cells2946
Missing cells (%)28.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory88.1 KiB
Average record size in memory421.6 B

Variable types

Categorical14
Text4
Numeric17
Unsupported6
DateTime8

Dataset

Description화성시 2015년 08월 기준 사용(임시)승인허가현황(건축구분, 대지위치, 지목, 대지면적, 임시사용승인기간 등) 정보를 제공합니다.
Author경기도 화성시
URLhttps://www.data.go.kr/data/15052044/fileData.do

Alerts

건축구분 is highly imbalanced (51.8%)Imbalance
구조 is highly imbalanced (52.2%)Imbalance
최대지하층수 is highly imbalanced (51.9%)Imbalance
승강기합 is highly imbalanced (59.2%)Imbalance
비상승강기합 is highly imbalanced (95.7%)Imbalance
용도지구 is highly imbalanced (80.3%)Imbalance
용도구역 is highly imbalanced (61.5%)Imbalance
기계식옥외주차장(대) is highly imbalanced (95.7%)Imbalance
호수 is highly imbalanced (92.6%)Imbalance
부속건축물수 is highly imbalanced (86.9%)Imbalance
증축연면적(㎡) has 181 (84.6%) missing valuesMissing
취소구분 has 214 (100.0%) missing valuesMissing
철거멸실구분 has 214 (100.0%) missing valuesMissing
허가취소일 has 214 (100.0%) missing valuesMissing
최종설계변경일 has 140 (65.4%) missing valuesMissing
착공처리일 has 9 (4.2%) missing valuesMissing
착공예정일 has 9 (4.2%) missing valuesMissing
실제착공일 has 7 (3.3%) missing valuesMissing
착공연기일 has 201 (93.9%) missing valuesMissing
착공연기사유 has 203 (94.9%) missing valuesMissing
임시사용승인기간 has 212 (99.1%) missing valuesMissing
하수처리시설용량(㎥) has 86 (40.2%) missing valuesMissing
부속용도 has 70 (32.7%) missing valuesMissing
자주식옥내주차장(대) has 183 (85.5%) missing valuesMissing
자주식옥외주차장(대) has 23 (10.7%) missing valuesMissing
기계식옥내주차장(대) has 214 (100.0%) missing valuesMissing
인근자주식주차장(대) has 214 (100.0%) missing valuesMissing
인근기계식주차장(대) has 214 (100.0%) missing valuesMissing
세대수 has 204 (95.3%) missing valuesMissing
가구수 has 126 (58.9%) missing valuesMissing
주차장대수 has 6 (2.8%) missing valuesMissing
대지위치 has unique valuesUnique
취소구분 is an unsupported type, check if it needs cleaning or further analysisUnsupported
철거멸실구분 is an unsupported type, check if it needs cleaning or further analysisUnsupported
허가취소일 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기계식옥내주차장(대) is an unsupported type, check if it needs cleaning or further analysisUnsupported
인근자주식주차장(대) is an unsupported type, check if it needs cleaning or further analysisUnsupported
인근기계식주차장(대) is an unsupported type, check if it needs cleaning or further analysisUnsupported
동수 has 6 (2.8%) zerosZeros
주건축물수 has 4 (1.9%) zerosZeros

Reproduction

Analysis started2023-12-12 11:53:35.536995
Analysis finished2023-12-12 11:53:36.363451
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
신축
169 
증축
33 
용도변경
 
9
대수선
 
3

Length

Max length4
Median length2
Mean length2.0981308
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row용도변경
2nd row용도변경
3rd row증축
4th row대수선
5th row증축

Common Values

ValueCountFrequency (%)
신축 169
79.0%
증축 33
 
15.4%
용도변경 9
 
4.2%
대수선 3
 
1.4%

Length

2023-12-12T20:53:36.460716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:53:36.605422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 169
79.0%
증축 33
 
15.4%
용도변경 9
 
4.2%
대수선 3
 
1.4%

대지위치
Text

UNIQUE 

Distinct214
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T20:53:36.879220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length29
Mean length22.920561
Min length14

Characters and Unicode

Total characters4905
Distinct characters132
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

Unique214 ?
Unique (%)100.0%

Sample

1st row경기도 화성시 매송면 원평리 227-18
2nd row경기도 화성시 능동 1064-5
3rd row경기도 화성시 팔탄면 지월리 389-35
4th row경기도 화성시 정남면 덕절리 190-6
5th row경기도 화성시 반송동 63-3
ValueCountFrequency (%)
경기도 214
19.1%
화성시 214
19.1%
외1필지 37
 
3.3%
동탄면 33
 
2.9%
동탄2택지개발지구 26
 
2.3%
남양읍 23
 
2.0%
향남읍 22
 
2.0%
장안면 17
 
1.5%
정남면 17
 
1.5%
외2필지 14
 
1.2%
Other values (316) 506
45.1%
2023-12-12T20:53:37.379066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
909
18.5%
화 225
 
4.6%
도 224
 
4.6%
1 220
 
4.5%
성 216
 
4.4%
기 215
 
4.4%
경 214
 
4.4%
시 214
 
4.4%
- 160
 
3.3%
리 149
 
3.0%
Other values (122) 2159
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2790
56.9%
Decimal Number 1046
 
21.3%
Space Separator 909
 
18.5%
Dash Punctuation 160
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 225
 
8.1%
도 224
 
8.0%
성 216
 
7.7%
기 215
 
7.7%
경 214
 
7.7%
시 214
 
7.7%
리 149
 
5.3%
지 122
 
4.4%
면 114
 
4.1%
동 101
 
3.6%
Other values (110) 996
35.7%
Decimal Number
ValueCountFrequency (%)
1 220
21.0%
2 130
12.4%
4 124
11.9%
0 115
11.0%
3 101
9.7%
5 89
8.5%
7 72
 
6.9%
6 67
 
6.4%
9 65
 
6.2%
8 63
 
6.0%
Space Separator
ValueCountFrequency (%)
909
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 160
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2790
56.9%
Common 2115
43.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
화 225
 
8.1%
도 224
 
8.0%
성 216
 
7.7%
기 215
 
7.7%
경 214
 
7.7%
시 214
 
7.7%
리 149
 
5.3%
지 122
 
4.4%
면 114
 
4.1%
동 101
 
3.6%
Other values (110) 996
35.7%
Common
ValueCountFrequency (%)
909
43.0%
1 220
 
10.4%
- 160
 
7.6%
2 130
 
6.1%
4 124
 
5.9%
0 115
 
5.4%
3 101
 
4.8%
5 89
 
4.2%
7 72
 
3.4%
6 67
 
3.2%
Other values (2) 128
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2790
56.9%
ASCII 2115
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
909
43.0%
1 220
 
10.4%
- 160
 
7.6%
2 130
 
6.1%
4 124
 
5.9%
0 115
 
5.4%
3 101
 
4.8%
5 89
 
4.2%
7 72
 
3.4%
6 67
 
3.2%
Other values (2) 128
 
6.1%
Hangul
ValueCountFrequency (%)
화 225
 
8.1%
도 224
 
8.0%
성 216
 
7.7%
기 215
 
7.7%
경 214
 
7.7%
시 214
 
7.7%
리 149
 
5.3%
지 122
 
4.4%
면 114
 
4.1%
동 101
 
3.6%
Other values (110) 996
35.7%

지목
Categorical

Distinct10
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
대
94 
공장용지
38 
임야
29 
전
28 
답
12 
Other values (5)
13 

Length

Max length4
Median length1
Mean length1.8084112
Min length1

Unique

Unique2 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
대 94
43.9%
공장용지 38
17.8%
임야 29
 
13.6%
전 28
 
13.1%
답 12
 
5.6%
잡종지 5
 
2.3%
창고용지 4
 
1.9%
주차장 2
 
0.9%
목장용지 1
 
0.5%
유지 1
 
0.5%

Length

2023-12-12T20:53:37.536612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:53:37.697320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대 94
43.9%
공장용지 38
17.8%
임야 29
 
13.6%
전 28
 
13.1%
답 12
 
5.6%
잡종지 5
 
2.3%
창고용지 4
 
1.9%
주차장 2
 
0.9%
목장용지 1
 
0.5%
유지 1
 
0.5%

대지면적(㎡)
Real number (ℝ)

Distinct192
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2811.8818
Minimum170
Maximum150000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:53:37.897682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum170
5-th percentile236.985
Q1291.675
median889
Q31833.25
95-th percentile7133.415
Maximum150000
Range149830
Interquartile range (IQR)1541.575

Descriptive statistics

Standard deviation11581.659
Coefficient of variation (CV)4.1188286
Kurtosis127.58524
Mean2811.8818
Median Absolute Deviation (MAD)618.8
Skewness10.661991
Sum601742.7
Variance1.3413483 × 108
MonotonicityNot monotonic
2023-12-12T20:53:38.104962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
266.0 4
 
1.9%
265.0 3
 
1.4%
274.0 3
 
1.4%
988.0 3
 
1.4%
1386.0 2
 
0.9%
207.0 2
 
0.9%
1416.0 2
 
0.9%
252.0 2
 
0.9%
241.0 2
 
0.9%
913.0 2
 
0.9%
Other values (182) 189
88.3%
ValueCountFrequency (%)
170.0 1
0.5%
207.0 2
0.9%
229.1 1
0.5%
230.1 1
0.5%
230.3 1
0.5%
231.0 2
0.9%
233.5 1
0.5%
235.0 1
0.5%
235.1 1
0.5%
238.0 1
0.5%
ValueCountFrequency (%)
150000.0 1
0.5%
64899.9 1
0.5%
42182.0 1
0.5%
17582.8 1
0.5%
15404.2 1
0.5%
13882.0 1
0.5%
8994.0 1
0.5%
8434.0 1
0.5%
8379.0 1
0.5%
7837.1 1
0.5%

건축면적(㎡)
Real number (ℝ)

Distinct210
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean739.3049
Minimum101.84
Maximum18044.34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:53:38.315462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101.84
5-th percentile136.3325
Q1157.57
median265.995
Q3582.97
95-th percentile2368.501
Maximum18044.34
Range17942.5
Interquartile range (IQR)425.4

Descriptive statistics

Standard deviation1695.514
Coefficient of variation (CV)2.2933894
Kurtosis59.27261
Mean739.3049
Median Absolute Deviation (MAD)127.14
Skewness6.9223509
Sum158211.25
Variance2874767.8
MonotonicityNot monotonic
2023-12-12T20:53:38.517408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
495.0 2
 
0.9%
686.4 2
 
0.9%
145.2 2
 
0.9%
159.0 2
 
0.9%
183.62 1
 
0.5%
497.52 1
 
0.5%
149.0 1
 
0.5%
552.24 1
 
0.5%
375.0 1
 
0.5%
285.47 1
 
0.5%
Other values (200) 200
93.5%
ValueCountFrequency (%)
101.84 1
0.5%
102.52 1
0.5%
105.45 1
0.5%
106.04 1
0.5%
114.84 1
0.5%
115.95 1
0.5%
117.82 1
0.5%
120.6 1
0.5%
121.74 1
0.5%
134.36 1
0.5%
ValueCountFrequency (%)
18044.34 1
0.5%
10669.16 1
0.5%
9628.69 1
0.5%
5480.08 1
0.5%
4497.11 1
0.5%
4038.19 1
0.5%
3465.2 1
0.5%
2951.78 1
0.5%
2890.05 1
0.5%
2797.92 1
0.5%

연면적(㎡)
Real number (ℝ)

Distinct212
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1358.6976
Minimum135
Maximum20274.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:53:38.754518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum135
5-th percentile190.7575
Q1375.1475
median477.065
Q3864.4125
95-th percentile5568.71
Maximum20274.13
Range20139.13
Interquartile range (IQR)489.265

Descriptive statistics

Standard deviation2760.912
Coefficient of variation (CV)2.0320284
Kurtosis21.722993
Mean1358.6976
Median Absolute Deviation (MAD)182.56
Skewness4.4195621
Sum290761.28
Variance7622635.3
MonotonicityNot monotonic
2023-12-12T20:53:38.999022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
495.0 2
 
0.9%
414.62 2
 
0.9%
375.59 1
 
0.5%
855.21 1
 
0.5%
372.76 1
 
0.5%
2999.56 1
 
0.5%
375.0 1
 
0.5%
1134.95 1
 
0.5%
452.7 1
 
0.5%
239.45 1
 
0.5%
Other values (202) 202
94.4%
ValueCountFrequency (%)
135.0 1
0.5%
137.5 1
0.5%
147.32 1
0.5%
163.76 1
0.5%
164.64 1
0.5%
165.16 1
0.5%
173.8 1
0.5%
178.62 1
0.5%
186.3 1
0.5%
187.21 1
0.5%
ValueCountFrequency (%)
20274.13 1
0.5%
17411.38 1
0.5%
15586.86 1
0.5%
14998.57 1
0.5%
11046.87 1
0.5%
10656.04 1
0.5%
9430.05 1
0.5%
8806.41 1
0.5%
8230.03 1
0.5%
6878.38 1
0.5%

증축연면적(㎡)
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)100.0%
Missing181
Missing (%)84.6%
Infinite0
Infinite (%)0.0%
Mean802.67667
Minimum-151.22
Maximum11046.87
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)0.5%
Memory size2.0 KiB
2023-12-12T20:53:39.199914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-151.22
5-th percentile38.97
Q1127.68
median352.44
Q3648
95-th percentile1640.5
Maximum11046.87
Range11198.09
Interquartile range (IQR)520.32

Descriptive statistics

Standard deviation1903.8182
Coefficient of variation (CV)2.3718369
Kurtosis28.321253
Mean802.67667
Median Absolute Deviation (MAD)244.09
Skewness5.1666273
Sum26488.33
Variance3624523.6
MonotonicityNot monotonic
2023-12-12T20:53:39.399369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
423.59 1
 
0.5%
431.7 1
 
0.5%
1348.38 1
 
0.5%
11046.87 1
 
0.5%
648.0 1
 
0.5%
1999.0 1
 
0.5%
1398.53 1
 
0.5%
352.44 1
 
0.5%
59.91 1
 
0.5%
491.7 1
 
0.5%
Other values (23) 23
 
10.7%
(Missing) 181
84.6%
ValueCountFrequency (%)
-151.22 1
0.5%
7.56 1
0.5%
59.91 1
0.5%
87.8 1
0.5%
89.8 1
0.5%
105.0 1
0.5%
108.35 1
0.5%
120.19 1
0.5%
127.68 1
0.5%
135.84 1
0.5%
ValueCountFrequency (%)
11046.87 1
0.5%
1999.0 1
0.5%
1401.5 1
0.5%
1398.53 1
0.5%
1348.38 1
0.5%
1164.95 1
0.5%
926.88 1
0.5%
700.75 1
0.5%
648.0 1
0.5%
634.1 1
0.5%

건폐율(%)
Real number (ℝ)

Distinct196
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.05335
Minimum5.49
Maximum84.208
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:53:39.600033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.49
5-th percentile16.562
Q128.3125
median39.50715
Q359.558325
95-th percentile59.977
Maximum84.208
Range78.718
Interquartile range (IQR)31.245825

Descriptive statistics

Standard deviation16.72703
Coefficient of variation (CV)0.39775738
Kurtosis-0.95979057
Mean42.05335
Median Absolute Deviation (MAD)17.255
Skewness0.0050958999
Sum8999.417
Variance279.79355
MonotonicityNot monotonic
2023-12-12T20:53:39.798350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59.77 3
 
1.4%
59.71 3
 
1.4%
59.91 3
 
1.4%
59.88 3
 
1.4%
19.87 2
 
0.9%
59.84 2
 
0.9%
59.95 2
 
0.9%
59.65 2
 
0.9%
27.27 2
 
0.9%
39.77 2
 
0.9%
Other values (186) 190
88.8%
ValueCountFrequency (%)
5.49 1
0.5%
7.11 1
0.5%
9.59 1
0.5%
11.66 1
0.5%
11.821 1
0.5%
15.09 1
0.5%
15.11 1
0.5%
15.41 1
0.5%
15.46 1
0.5%
16.06 1
0.5%
ValueCountFrequency (%)
84.208 1
0.5%
79.76 1
0.5%
79.49 1
0.5%
77.47 1
0.5%
71.42 1
0.5%
69.84 1
0.5%
66.43 1
0.5%
64.5277 1
0.5%
63.58 1
0.5%
62.5 1
0.5%

용적률(%)
Real number (ℝ)

Distinct212
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93.864358
Minimum7.1
Maximum499.85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:53:40.012086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.1
5-th percentile19.7245
Q137.085
median59.95
Q3150.525
95-th percentile193.9955
Maximum499.85
Range492.75
Interquartile range (IQR)113.44

Descriptive statistics

Standard deviation78.724425
Coefficient of variation (CV)0.83870414
Kurtosis6.2532947
Mean93.864358
Median Absolute Deviation (MAD)32.835
Skewness1.9548497
Sum20086.973
Variance6197.5352
MonotonicityNot monotonic
2023-12-12T20:53:40.216673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
79.7 2
 
0.9%
27.27 2
 
0.9%
68.78 1
 
0.5%
162.59 1
 
0.5%
36.47 1
 
0.5%
61.7 1
 
0.5%
138.06 1
 
0.5%
149.86 1
 
0.5%
37.96 1
 
0.5%
183.95 1
 
0.5%
Other values (202) 202
94.4%
ValueCountFrequency (%)
7.1 1
0.5%
7.41 1
0.5%
15.11 1
0.5%
15.46 1
0.5%
16.25 1
0.5%
16.73 1
0.5%
16.86 1
0.5%
17.59 1
0.5%
19.45 1
0.5%
19.48 1
0.5%
ValueCountFrequency (%)
499.85 1
0.5%
481.24 1
0.5%
403.76 1
0.5%
399.81 1
0.5%
296.8217 1
0.5%
240.1714 1
0.5%
233.49 1
0.5%
203.12 1
0.5%
199.46 1
0.5%
198.78 1
0.5%

구조
Categorical

IMBALANCE 

Distinct7
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
철근콘크리트구조
107 
일반철골구조
95 
경량철골구조
 
8
일반목구조
 
1
프리케스트콘크리트구조
 
1
Other values (2)
 
2

Length

Max length11
Median length10.5
Mean length7.0280374
Min length4

Unique

Unique4 ?
Unique (%)1.9%

Sample

1st row철근콘크리트구조
2nd row철근콘크리트구조
3rd row일반철골구조
4th row철근콘크리트구조
5th row철근콘크리트구조

Common Values

ValueCountFrequency (%)
철근콘크리트구조 107
50.0%
일반철골구조 95
44.4%
경량철골구조 8
 
3.7%
일반목구조 1
 
0.5%
프리케스트콘크리트구조 1
 
0.5%
철골철근콘크리트구조 1
 
0.5%
블록구조 1
 
0.5%

Length

2023-12-12T20:53:40.409958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:53:40.970939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근콘크리트구조 107
50.0%
일반철골구조 95
44.4%
경량철골구조 8
 
3.7%
일반목구조 1
 
0.5%
프리케스트콘크리트구조 1
 
0.5%
철골철근콘크리트구조 1
 
0.5%
블록구조 1
 
0.5%

취소구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing214
Missing (%)100.0%
Memory size2.0 KiB

철거멸실구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing214
Missing (%)100.0%
Memory size2.0 KiB

허가취소일
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing214
Missing (%)100.0%
Memory size2.0 KiB

허가일
Date

Distinct150
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2000-11-01 00:00:00
Maximum2015-08-24 00:00:00
2023-12-12T20:53:41.178195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:53:41.395218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최종설계변경일
Date

MISSING 

Distinct62
Distinct (%)83.8%
Missing140
Missing (%)65.4%
Memory size1.8 KiB
Minimum2011-07-01 00:00:00
Maximum2015-08-11 00:00:00
2023-12-12T20:53:41.580448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:53:41.845475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공처리일
Date

MISSING 

Distinct125
Distinct (%)61.0%
Missing9
Missing (%)4.2%
Memory size1.8 KiB
Minimum2003-06-30 00:00:00
Maximum2015-08-06 00:00:00
2023-12-12T20:53:42.069952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:53:42.275120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공예정일
Text

MISSING 

Distinct137
Distinct (%)66.8%
Missing9
Missing (%)4.2%
Memory size1.8 KiB
2023-12-12T20:53:42.649260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters2050
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)49.3%

Sample

1st row2015-08-05
2nd row2015-08-10
3rd row2015-07-28
4th row2015-07-27
5th row2015-07-27
ValueCountFrequency (%)
2015-03-23 6
 
2.9%
2015-03-20 5
 
2.4%
2015-04-10 5
 
2.4%
2015-04-17 5
 
2.4%
2015-02-23 4
 
2.0%
2015-04-06 4
 
2.0%
2015-04-03 4
 
2.0%
2015-04-28 3
 
1.5%
2015-04-01 3
 
1.5%
2015-03-10 3
 
1.5%
Other values (127) 163
79.5%
2023-12-12T20:53:43.174676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 486
23.7%
- 410
20.0%
1 332
16.2%
2 320
15.6%
5 185
 
9.0%
3 95
 
4.6%
4 95
 
4.6%
6 43
 
2.1%
7 35
 
1.7%
8 27
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1640
80.0%
Dash Punctuation 410
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 486
29.6%
1 332
20.2%
2 320
19.5%
5 185
 
11.3%
3 95
 
5.8%
4 95
 
5.8%
6 43
 
2.6%
7 35
 
2.1%
8 27
 
1.6%
9 22
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 410
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2050
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 486
23.7%
- 410
20.0%
1 332
16.2%
2 320
15.6%
5 185
 
9.0%
3 95
 
4.6%
4 95
 
4.6%
6 43
 
2.1%
7 35
 
1.7%
8 27
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2050
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 486
23.7%
- 410
20.0%
1 332
16.2%
2 320
15.6%
5 185
 
9.0%
3 95
 
4.6%
4 95
 
4.6%
6 43
 
2.1%
7 35
 
1.7%
8 27
 
1.3%

실제착공일
Text

MISSING 

Distinct141
Distinct (%)68.1%
Missing7
Missing (%)3.3%
Memory size1.8 KiB
2023-12-12T20:53:43.535743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters2070
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)49.3%

Sample

1st row2015-08-05
2nd row2015-08-10
3rd row2015-07-28
4th row2015-07-27
5th row2015-07-27
ValueCountFrequency (%)
2015-03-23 5
 
2.4%
2015-03-20 5
 
2.4%
2015-04-10 4
 
1.9%
2015-04-03 4
 
1.9%
2015-05-11 4
 
1.9%
2015-02-23 4
 
1.9%
2015-04-06 4
 
1.9%
2015-02-13 4
 
1.9%
2015-04-01 4
 
1.9%
2015-04-17 3
 
1.4%
Other values (131) 166
80.2%
2023-12-12T20:53:44.113578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 495
23.9%
- 414
20.0%
1 334
16.1%
2 328
15.8%
5 189
 
9.1%
4 94
 
4.5%
3 93
 
4.5%
6 45
 
2.2%
7 34
 
1.6%
9 22
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1656
80.0%
Dash Punctuation 414
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 495
29.9%
1 334
20.2%
2 328
19.8%
5 189
 
11.4%
4 94
 
5.7%
3 93
 
5.6%
6 45
 
2.7%
7 34
 
2.1%
9 22
 
1.3%
8 22
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 414
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2070
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 495
23.9%
- 414
20.0%
1 334
16.1%
2 328
15.8%
5 189
 
9.1%
4 94
 
4.5%
3 93
 
4.5%
6 45
 
2.2%
7 34
 
1.6%
9 22
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2070
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 495
23.9%
- 414
20.0%
1 334
16.1%
2 328
15.8%
5 189
 
9.1%
4 94
 
4.5%
3 93
 
4.5%
6 45
 
2.2%
7 34
 
1.6%
9 22
 
1.1%

착공연기일
Date

MISSING 

Distinct11
Distinct (%)84.6%
Missing201
Missing (%)93.9%
Memory size1.8 KiB
Minimum2002-11-01 00:00:00
Maximum2016-03-26 00:00:00
2023-12-12T20:53:44.311959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:53:44.428981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

착공연기사유
Date

MISSING 

Distinct9
Distinct (%)81.8%
Missing203
Missing (%)94.9%
Memory size1.8 KiB
Minimum2008-07-01 00:00:00
Maximum2016-03-26 00:00:00
2023-12-12T20:53:44.558755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:53:44.704720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)

임시사용승인기간
Date

MISSING 

Distinct2
Distinct (%)100.0%
Missing212
Missing (%)99.1%
Memory size1.8 KiB
Minimum2015-12-29 00:00:00
Maximum2016-04-12 00:00:00
2023-12-12T20:53:44.851236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:53:44.969182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

사용승인일
Date

Distinct20
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2015-08-03 00:00:00
Maximum2015-08-31 00:00:00
2023-12-12T20:53:45.132141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:53:45.321586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)

건축허가최초접수일
Date

Distinct159
Distinct (%)74.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2000-10-18 00:00:00
Maximum2015-08-18 00:00:00
2023-12-12T20:53:45.514496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:53:45.729860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최대지상층수
Real number (ℝ)

Distinct7
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.588785
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:53:45.892597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile5
Maximum10
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4499686
Coefficient of variation (CV)0.56009616
Kurtosis5.2548918
Mean2.588785
Median Absolute Deviation (MAD)1
Skewness1.5193598
Sum554
Variance2.1024088
MonotonicityNot monotonic
2023-12-12T20:53:46.046057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 57
26.6%
2 53
24.8%
3 51
23.8%
4 41
19.2%
5 8
 
3.7%
10 2
 
0.9%
7 2
 
0.9%
ValueCountFrequency (%)
1 57
26.6%
2 53
24.8%
3 51
23.8%
4 41
19.2%
5 8
 
3.7%
7 2
 
0.9%
10 2
 
0.9%
ValueCountFrequency (%)
10 2
 
0.9%
7 2
 
0.9%
5 8
 
3.7%
4 41
19.2%
3 51
23.8%
2 53
24.8%
1 57
26.6%

최대지하층수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
0
160 
<NA>
39 
1
 
10
2
 
3
3
 
2

Length

Max length4
Median length1
Mean length1.546729
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row3
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
0 160
74.8%
<NA> 39
 
18.2%
1 10
 
4.7%
2 3
 
1.4%
3 2
 
0.9%

Length

2023-12-12T20:53:46.242988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:53:46.421652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 160
74.8%
na 39
 
18.2%
1 10
 
4.7%
2 3
 
1.4%
3 2
 
0.9%

최고높이(m)
Real number (ℝ)

Distinct125
Distinct (%)58.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.981187
Minimum4.2
Maximum49.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:53:46.626400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.2
5-th percentile6.765
Q19
median11.4
Q313.675
95-th percentile16.785
Maximum49.5
Range45.3
Interquartile range (IQR)4.675

Descriptive statistics

Standard deviation5.1215412
Coefficient of variation (CV)0.42746526
Kurtosis21.009826
Mean11.981187
Median Absolute Deviation (MAD)2.35
Skewness3.6817848
Sum2563.974
Variance26.230185
MonotonicityNot monotonic
2023-12-12T20:53:46.855232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.7 7
 
3.3%
10.1 6
 
2.8%
12.2 6
 
2.8%
9.7 5
 
2.3%
9.0 5
 
2.3%
14.3 5
 
2.3%
9.9 5
 
2.3%
13.1 4
 
1.9%
15.7 4
 
1.9%
13.3 3
 
1.4%
Other values (115) 164
76.6%
ValueCountFrequency (%)
4.2 1
0.5%
4.3 1
0.5%
4.5 1
0.5%
5.0 1
0.5%
5.15 1
0.5%
5.7 1
0.5%
6.0 1
0.5%
6.1 1
0.5%
6.2 1
0.5%
6.55 1
0.5%
ValueCountFrequency (%)
49.5 1
0.5%
42.2 1
0.5%
34.8 1
0.5%
33.1 1
0.5%
29.113 1
0.5%
22.37 1
0.5%
19.95 1
0.5%
17.0 1
0.5%
16.95 1
0.5%
16.9 1
0.5%

동수
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.453271
Minimum0
Maximum11
Zeros6
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:53:47.027008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile3
Maximum11
Range11
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2122859
Coefficient of variation (CV)0.83417745
Kurtosis23.988428
Mean1.453271
Median Absolute Deviation (MAD)0
Skewness4.1959116
Sum311
Variance1.4696371
MonotonicityNot monotonic
2023-12-12T20:53:47.204602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 152
71.0%
2 37
 
17.3%
3 9
 
4.2%
0 6
 
2.8%
4 4
 
1.9%
5 2
 
0.9%
11 1
 
0.5%
6 1
 
0.5%
7 1
 
0.5%
8 1
 
0.5%
ValueCountFrequency (%)
0 6
 
2.8%
1 152
71.0%
2 37
 
17.3%
3 9
 
4.2%
4 4
 
1.9%
5 2
 
0.9%
6 1
 
0.5%
7 1
 
0.5%
8 1
 
0.5%
11 1
 
0.5%
ValueCountFrequency (%)
11 1
 
0.5%
8 1
 
0.5%
7 1
 
0.5%
6 1
 
0.5%
5 2
 
0.9%
4 4
 
1.9%
3 9
 
4.2%
2 37
 
17.3%
1 152
71.0%
0 6
 
2.8%

승강기합
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
172 
1
31 
2
 
5
0
 
5
4
 
1

Length

Max length4
Median length4
Mean length3.411215
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row4
3rd row<NA>
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 172
80.4%
1 31
 
14.5%
2 5
 
2.3%
0 5
 
2.3%
4 1
 
0.5%

Length

2023-12-12T20:53:47.397661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:53:47.567271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 172
80.4%
1 31
 
14.5%
2 5
 
2.3%
0 5
 
2.3%
4 1
 
0.5%

비상승강기합
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
213 
1
 
1

Length

Max length4
Median length4
Mean length3.9859813
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 213
99.5%
1 1
 
0.5%

Length

2023-12-12T20:53:47.769221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:53:47.942057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 213
99.5%
1 1
 
0.5%

하수처리시설명
Categorical

Distinct10
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
하수종말처리장연결
100 
기타오수처리시설
88 
접촉산화방법
 
7
현수미생물접촉방법
 
5
혐기및호기성미생물조정방법
 
4
Other values (5)
 
10

Length

Max length13
Median length9
Mean length8.411215
Min length4

Unique

Unique2 ?
Unique (%)0.9%

Sample

1st row기타오수처리시설
2nd row하수종말처리장연결
3rd row기타오수처리시설
4th row기타오수처리시설
5th row하수종말처리장연결

Common Values

ValueCountFrequency (%)
하수종말처리장연결 100
46.7%
기타오수처리시설 88
41.1%
접촉산화방법 7
 
3.3%
현수미생물접촉방법 5
 
2.3%
혐기및호기성미생물조정방법 4
 
1.9%
부패탱크방법 3
 
1.4%
접촉폭기방법 3
 
1.4%
<NA> 2
 
0.9%
장기폭기방법 1
 
0.5%
기타단독정화조 1
 
0.5%

Length

2023-12-12T20:53:48.103366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:53:48.279282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
하수종말처리장연결 100
46.7%
기타오수처리시설 88
41.1%
접촉산화방법 7
 
3.3%
현수미생물접촉방법 5
 
2.3%
혐기및호기성미생물조정방법 4
 
1.9%
부패탱크방법 3
 
1.4%
접촉폭기방법 3
 
1.4%
na 2
 
0.9%
장기폭기방법 1
 
0.5%
기타단독정화조 1
 
0.5%

하수처리시설용량(㎥)
Real number (ℝ)

MISSING 

Distinct36
Distinct (%)28.1%
Missing86
Missing (%)40.2%
Infinite0
Infinite (%)0.0%
Mean11.240797
Minimum1
Maximum77.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:53:48.496002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.3045
Q13.8925
median8
Q315
95-th percentile30
Maximum77.71
Range76.71
Interquartile range (IQR)11.1075

Descriptive statistics

Standard deviation11.430367
Coefficient of variation (CV)1.0168645
Kurtosis10.873303
Mean11.240797
Median Absolute Deviation (MAD)5
Skewness2.8037562
Sum1438.822
Variance130.6533
MonotonicityNot monotonic
2023-12-12T20:53:48.699337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
3.0 20
 
9.3%
10.0 15
 
7.0%
8.0 9
 
4.2%
20.0 8
 
3.7%
4.0 8
 
3.7%
6.0 8
 
3.7%
5.0 7
 
3.3%
16.0 6
 
2.8%
12.0 5
 
2.3%
30.0 5
 
2.3%
Other values (26) 37
17.3%
(Missing) 86
40.2%
ValueCountFrequency (%)
1.0 2
 
0.9%
2.0 5
 
2.3%
2.87 1
 
0.5%
2.98 1
 
0.5%
3.0 20
9.3%
3.15 1
 
0.5%
3.44 1
 
0.5%
3.57 1
 
0.5%
4.0 8
 
3.7%
4.5 1
 
0.5%
ValueCountFrequency (%)
77.71 1
 
0.5%
53.91 1
 
0.5%
51.5 1
 
0.5%
50.0 1
 
0.5%
30.0 5
2.3%
27.67 1
 
0.5%
26.482 1
 
0.5%
26.0 1
 
0.5%
24.0 2
 
0.9%
20.0 8
3.7%

주용도
Categorical

Distinct12
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
단독주택
79 
제2종근린생활시설
50 
공장
45 
제1종근린생활시설
15 
공동주택
11 
Other values (7)
14 

Length

Max length9
Median length8
Mean length5.2102804
Min length2

Unique

Unique2 ?
Unique (%)0.9%

Sample

1st row단독주택
2nd row제1종근린생활시설
3rd row공장
4th row단독주택
5th row단독주택

Common Values

ValueCountFrequency (%)
단독주택 79
36.9%
제2종근린생활시설 50
23.4%
공장 45
21.0%
제1종근린생활시설 15
 
7.0%
공동주택 11
 
5.1%
자동차관련시설 3
 
1.4%
교육연구시설 3
 
1.4%
숙박시설 2
 
0.9%
동.식물관련시설 2
 
0.9%
창고시설 2
 
0.9%
Other values (2) 2
 
0.9%

Length

2023-12-12T20:53:48.902789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독주택 79
36.9%
제2종근린생활시설 50
23.4%
공장 45
21.0%
제1종근린생활시설 15
 
7.0%
공동주택 11
 
5.1%
자동차관련시설 3
 
1.4%
교육연구시설 3
 
1.4%
숙박시설 2
 
0.9%
동.식물관련시설 2
 
0.9%
창고시설 2
 
0.9%
Other values (2) 2
 
0.9%

부속용도
Text

MISSING 

Distinct86
Distinct (%)59.7%
Missing70
Missing (%)32.7%
Memory size1.8 KiB
2023-12-12T20:53:49.164129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length21
Mean length10.277778
Min length2

Characters and Unicode

Total characters1480
Distinct characters104
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)44.4%

Sample

1st row제2종근린생활시설_일반음식점
2nd row제2종근린생활시설,위락시설,판매시설
3rd row다가구주택
4th row다가구주택, 소매점
5th row제1종근생(휴게음식점),다가구주택
ValueCountFrequency (%)
다가구주택 28
 
15.1%
제조업소 17
 
9.1%
및 16
 
8.6%
제2종근린생활시설 7
 
3.8%
소매점 6
 
3.2%
단독주택 6
 
3.2%
사무소 5
 
2.7%
일반음식점 5
 
2.7%
근린생활시설 5
 
2.7%
제2종근생(일반음식점),다가구주택 4
 
2.2%
Other values (68) 87
46.8%
2023-12-12T20:53:49.616854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 82
 
5.5%
택 79
 
5.3%
구 76
 
5.1%
가 73
 
4.9%
다 63
 
4.3%
제 60
 
4.1%
생 59
 
4.0%
근 54
 
3.6%
( 52
 
3.5%
) 52
 
3.5%
Other values (94) 830
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1219
82.4%
Decimal Number 63
 
4.3%
Open Punctuation 52
 
3.5%
Close Punctuation 52
 
3.5%
Other Punctuation 49
 
3.3%
Space Separator 42
 
2.8%
Dash Punctuation 2
 
0.1%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 82
 
6.7%
택 79
 
6.5%
구 76
 
6.2%
가 73
 
6.0%
다 63
 
5.2%
제 60
 
4.9%
생 59
 
4.8%
근 54
 
4.4%
시 51
 
4.2%
소 48
 
3.9%
Other values (79) 574
47.1%
Decimal Number
ValueCountFrequency (%)
2 30
47.6%
1 18
28.6%
3 6
 
9.5%
5 5
 
7.9%
4 2
 
3.2%
6 1
 
1.6%
8 1
 
1.6%
Other Punctuation
ValueCountFrequency (%)
, 44
89.8%
/ 4
 
8.2%
& 1
 
2.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Space Separator
ValueCountFrequency (%)
42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1219
82.4%
Common 261
 
17.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 82
 
6.7%
택 79
 
6.5%
구 76
 
6.2%
가 73
 
6.0%
다 63
 
5.2%
제 60
 
4.9%
생 59
 
4.8%
근 54
 
4.4%
시 51
 
4.2%
소 48
 
3.9%
Other values (79) 574
47.1%
Common
ValueCountFrequency (%)
( 52
19.9%
) 52
19.9%
, 44
16.9%
42
16.1%
2 30
11.5%
1 18
 
6.9%
3 6
 
2.3%
5 5
 
1.9%
/ 4
 
1.5%
4 2
 
0.8%
Other values (5) 6
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1219
82.4%
ASCII 261
 
17.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 82
 
6.7%
택 79
 
6.5%
구 76
 
6.2%
가 73
 
6.0%
다 63
 
5.2%
제 60
 
4.9%
생 59
 
4.8%
근 54
 
4.4%
시 51
 
4.2%
소 48
 
3.9%
Other values (79) 574
47.1%
ASCII
ValueCountFrequency (%)
( 52
19.9%
) 52
19.9%
, 44
16.9%
42
16.1%
2 30
11.5%
1 18
 
6.9%
3 6
 
2.3%
5 5
 
1.9%
/ 4
 
1.5%
4 2
 
0.8%
Other values (5) 6
 
2.3%

용도지역
Categorical

Distinct19
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
계획관리지역
85 
제1종일반주거지역
41 
제2종일반주거지역
24 
자연녹지지역
22 
<NA>
10 
Other values (14)
32 

Length

Max length9
Median length6
Mean length6.7990654
Min length4

Unique

Unique10 ?
Unique (%)4.7%

Sample

1st row<NA>
2nd row일반상업지역
3rd row계획관리지역
4th row계획관리지역
5th row제2종일반주거지역

Common Values

ValueCountFrequency (%)
계획관리지역 85
39.7%
제1종일반주거지역 41
19.2%
제2종일반주거지역 24
 
11.2%
자연녹지지역 22
 
10.3%
<NA> 10
 
4.7%
일반공업지역 9
 
4.2%
일반상업지역 7
 
3.3%
준주거지역 3
 
1.4%
생산녹지지역 3
 
1.4%
준공업지역 1
 
0.5%
Other values (9) 9
 
4.2%

Length

2023-12-12T20:53:49.826174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
계획관리지역 85
39.7%
제1종일반주거지역 41
19.2%
제2종일반주거지역 24
 
11.2%
자연녹지지역 22
 
10.3%
na 10
 
4.7%
일반공업지역 9
 
4.2%
일반상업지역 7
 
3.3%
준주거지역 3
 
1.4%
생산녹지지역 3
 
1.4%
생산관리지역 1
 
0.5%
Other values (9) 9
 
4.2%

용도지구
Categorical

IMBALANCE 

Distinct7
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
198 
자연취락지구
 
7
비행안전제6구역(전술)
 
2
주거개발진흥지구
 
2
기타지구
 
2
Other values (2)
 
3

Length

Max length12
Median length4
Mean length4.2336449
Min length4

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 198
92.5%
자연취락지구 7
 
3.3%
비행안전제6구역(전술) 2
 
0.9%
주거개발진흥지구 2
 
0.9%
기타지구 2
 
0.9%
집단취락지구 2
 
0.9%
비행안전제2구역(전술) 1
 
0.5%

Length

2023-12-12T20:53:50.022556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:53:50.545083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 198
92.5%
자연취락지구 7
 
3.3%
비행안전제6구역(전술 2
 
0.9%
주거개발진흥지구 2
 
0.9%
기타지구 2
 
0.9%
집단취락지구 2
 
0.9%
비행안전제2구역(전술 1
 
0.5%

용도구역
Categorical

IMBALANCE 

Distinct11
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
151 
제1종지구단위계획구역
47 
지구단위계획구역
 
5
제2종지구단위계획구역
 
2
기타
 
2
Other values (6)
 
7

Length

Max length13
Median length4
Mean length5.7850467
Min length2

Unique

Unique5 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 151
70.6%
제1종지구단위계획구역 47
 
22.0%
지구단위계획구역 5
 
2.3%
제2종지구단위계획구역 2
 
0.9%
기타 2
 
0.9%
접도구역 2
 
0.9%
농업진흥구역 1
 
0.5%
비행 안전구역 1
 
0.5%
개발제한구역 1
 
0.5%
현상변경허가 대상구역 1
 
0.5%

Length

2023-12-12T20:53:50.726277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 151
69.9%
제1종지구단위계획구역 47
 
21.8%
지구단위계획구역 5
 
2.3%
제2종지구단위계획구역 2
 
0.9%
기타 2
 
0.9%
접도구역 2
 
0.9%
농업진흥구역 1
 
0.5%
비행 1
 
0.5%
안전구역 1
 
0.5%
개발제한구역 1
 
0.5%
Other values (3) 3
 
1.4%

자주식옥내주차장(대)
Real number (ℝ)

MISSING 

Distinct19
Distinct (%)61.3%
Missing183
Missing (%)85.5%
Infinite0
Infinite (%)0.0%
Mean19.258065
Minimum2
Maximum107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:53:50.866717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q14
median7
Q324.5
95-th percentile66.5
Maximum107
Range105
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation25.310035
Coefficient of variation (CV)1.3142564
Kurtosis4.2108068
Mean19.258065
Median Absolute Deviation (MAD)4
Skewness2.057311
Sum597
Variance640.59785
MonotonicityNot monotonic
2023-12-12T20:53:51.026353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
2 4
 
1.9%
4 4
 
1.9%
6 3
 
1.4%
8 3
 
1.4%
3 2
 
0.9%
7 2
 
0.9%
50 1
 
0.5%
29 1
 
0.5%
20 1
 
0.5%
78 1
 
0.5%
Other values (9) 9
 
4.2%
(Missing) 183
85.5%
ValueCountFrequency (%)
2 4
1.9%
3 2
0.9%
4 4
1.9%
5 1
 
0.5%
6 3
1.4%
7 2
0.9%
8 3
1.4%
11 1
 
0.5%
14 1
 
0.5%
20 1
 
0.5%
ValueCountFrequency (%)
107 1
0.5%
78 1
0.5%
55 1
0.5%
51 1
0.5%
50 1
0.5%
42 1
0.5%
29 1
0.5%
27 1
0.5%
22 1
0.5%
20 1
0.5%

자주식옥외주차장(대)
Real number (ℝ)

MISSING 

Distinct28
Distinct (%)14.7%
Missing23
Missing (%)10.7%
Infinite0
Infinite (%)0.0%
Mean7.2356021
Minimum1
Maximum98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:53:51.200999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q37
95-th percentile21.5
Maximum98
Range97
Interquartile range (IQR)4

Descriptive statistics

Standard deviation10.33451
Coefficient of variation (CV)1.4282861
Kurtosis36.805656
Mean7.2356021
Median Absolute Deviation (MAD)2
Skewness5.3653956
Sum1382
Variance106.80209
MonotonicityNot monotonic
2023-12-12T20:53:51.368750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
4 48
22.4%
2 22
10.3%
3 22
10.3%
6 19
 
8.9%
5 17
 
7.9%
7 16
 
7.5%
8 11
 
5.1%
1 7
 
3.3%
9 4
 
1.9%
12 3
 
1.4%
Other values (18) 22
10.3%
(Missing) 23
10.7%
ValueCountFrequency (%)
1 7
 
3.3%
2 22
10.3%
3 22
10.3%
4 48
22.4%
5 17
 
7.9%
6 19
 
8.9%
7 16
 
7.5%
8 11
 
5.1%
9 4
 
1.9%
10 2
 
0.9%
ValueCountFrequency (%)
98 1
0.5%
62 1
0.5%
45 1
0.5%
44 1
0.5%
40 1
0.5%
39 1
0.5%
31 1
0.5%
28 1
0.5%
26 1
0.5%
24 1
0.5%

기계식옥내주차장(대)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing214
Missing (%)100.0%
Memory size2.0 KiB

기계식옥외주차장(대)
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
213 
2
 
1

Length

Max length4
Median length4
Mean length3.9859813
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 213
99.5%
2 1
 
0.5%

Length

2023-12-12T20:53:51.538454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:53:51.676237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 213
99.5%
2 1
 
0.5%

인근자주식주차장(대)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing214
Missing (%)100.0%
Memory size2.0 KiB

인근기계식주차장(대)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing214
Missing (%)100.0%
Memory size2.0 KiB

총주차장면적(㎡)
Real number (ℝ)

Distinct37
Distinct (%)17.4%
Missing1
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean9.3004695
Minimum1
Maximum107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:53:51.832018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q38
95-th percentile40.8
Maximum107
Range106
Interquartile range (IQR)4

Descriptive statistics

Standard deviation14.527912
Coefficient of variation (CV)1.5620623
Kurtosis19.418346
Mean9.3004695
Median Absolute Deviation (MAD)2
Skewness4.1022534
Sum1981
Variance211.06024
MonotonicityNot monotonic
2023-12-12T20:53:52.020169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
4 47
22.0%
2 25
11.7%
6 21
9.8%
3 20
9.3%
7 18
 
8.4%
5 17
 
7.9%
8 12
 
5.6%
1 7
 
3.3%
9 6
 
2.8%
11 4
 
1.9%
Other values (27) 36
16.8%
ValueCountFrequency (%)
1 7
 
3.3%
2 25
11.7%
3 20
9.3%
4 47
22.0%
5 17
 
7.9%
6 21
9.8%
7 18
 
8.4%
8 12
 
5.6%
9 6
 
2.8%
10 3
 
1.4%
ValueCountFrequency (%)
107 1
0.5%
98 1
0.5%
78 1
0.5%
62 1
0.5%
60 1
0.5%
55 1
0.5%
51 1
0.5%
50 1
0.5%
45 1
0.5%
44 1
0.5%

주건축물수
Real number (ℝ)

ZEROS 

Distinct61
Distinct (%)28.6%
Missing1
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean146.99986
Minimum0
Maximum4179.81
Zeros4
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:53:52.214137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18.4
Q134.5
median57.5
Q392
95-th percentile531.296
Maximum4179.81
Range4179.81
Interquartile range (IQR)57.5

Descriptive statistics

Standard deviation388.53394
Coefficient of variation (CV)2.6430906
Kurtosis61.081111
Mean146.99986
Median Absolute Deviation (MAD)23
Skewness7.0364431
Sum31310.97
Variance150958.62
MonotonicityNot monotonic
2023-12-12T20:53:52.404442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46.0 40
18.7%
23.0 25
11.7%
34.5 19
 
8.9%
69.0 17
 
7.9%
80.5 16
 
7.5%
57.5 15
 
7.0%
92.0 11
 
5.1%
11.5 7
 
3.3%
103.5 5
 
2.3%
0.0 4
 
1.9%
Other values (51) 54
25.2%
ValueCountFrequency (%)
0.0 4
 
1.9%
11.5 7
 
3.3%
23.0 25
11.7%
34.5 19
8.9%
36.0 1
 
0.5%
43.0 1
 
0.5%
45.9 1
 
0.5%
46.0 40
18.7%
46.5 1
 
0.5%
47.0 2
 
0.9%
ValueCountFrequency (%)
4179.81 1
0.5%
2219.55 1
0.5%
1975.53 1
0.5%
1561.7 1
0.5%
1179.54 1
0.5%
1177.0 1
0.5%
897.0 1
0.5%
760.5 1
0.5%
719.14 1
0.5%
686.14 1
0.5%

세대수
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)90.0%
Missing204
Missing (%)95.3%
Infinite0
Infinite (%)0.0%
Mean15.3
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:53:52.576668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.15
Q19.5
median15.5
Q320.75
95-th percentile25.3
Maximum28
Range27
Interquartile range (IQR)11.25

Descriptive statistics

Standard deviation7.9867947
Coefficient of variation (CV)0.52201272
Kurtosis-0.2052995
Mean15.3
Median Absolute Deviation (MAD)6
Skewness-0.29059682
Sum153
Variance63.788889
MonotonicityNot monotonic
2023-12-12T20:53:52.714280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
8 2
 
0.9%
22 1
 
0.5%
28 1
 
0.5%
21 1
 
0.5%
14 1
 
0.5%
20 1
 
0.5%
16 1
 
0.5%
15 1
 
0.5%
1 1
 
0.5%
(Missing) 204
95.3%
ValueCountFrequency (%)
1 1
0.5%
8 2
0.9%
14 1
0.5%
15 1
0.5%
16 1
0.5%
20 1
0.5%
21 1
0.5%
22 1
0.5%
28 1
0.5%
ValueCountFrequency (%)
28 1
0.5%
22 1
0.5%
21 1
0.5%
20 1
0.5%
16 1
0.5%
15 1
0.5%
14 1
0.5%
8 2
0.9%
1 1
0.5%

호수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
210 
1
 
1
50
 
1
94
 
1
15
 
1

Length

Max length4
Median length4
Mean length3.9579439
Min length1

Unique

Unique4 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 210
98.1%
1 1
 
0.5%
50 1
 
0.5%
94 1
 
0.5%
15 1
 
0.5%

Length

2023-12-12T20:53:52.882242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:53:53.052623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 210
98.1%
1 1
 
0.5%
50 1
 
0.5%
94 1
 
0.5%
15 1
 
0.5%

가구수
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)17.0%
Missing126
Missing (%)58.9%
Infinite0
Infinite (%)0.0%
Mean4.625
Minimum1
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:53:53.237983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3.5
Q35
95-th percentile11.3
Maximum18
Range17
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.3263576
Coefficient of variation (CV)0.71921246
Kurtosis3.4171451
Mean4.625
Median Absolute Deviation (MAD)1.5
Skewness1.6331629
Sum407
Variance11.064655
MonotonicityNot monotonic
2023-12-12T20:53:53.410442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3 26
 
12.1%
5 22
 
10.3%
1 15
 
7.0%
7 5
 
2.3%
8 5
 
2.3%
9 3
 
1.4%
2 3
 
1.4%
4 2
 
0.9%
12 1
 
0.5%
14 1
 
0.5%
Other values (5) 5
 
2.3%
(Missing) 126
58.9%
ValueCountFrequency (%)
1 15
7.0%
2 3
 
1.4%
3 26
12.1%
4 2
 
0.9%
5 22
10.3%
6 1
 
0.5%
7 5
 
2.3%
8 5
 
2.3%
9 3
 
1.4%
10 1
 
0.5%
ValueCountFrequency (%)
18 1
 
0.5%
15 1
 
0.5%
14 1
 
0.5%
13 1
 
0.5%
12 1
 
0.5%
10 1
 
0.5%
9 3
1.4%
8 5
2.3%
7 5
2.3%
6 1
 
0.5%

주차장대수
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)3.8%
Missing6
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean1.4134615
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T20:53:53.569672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile3
Maximum11
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1086884
Coefficient of variation (CV)0.78437816
Kurtosis33.98521
Mean1.4134615
Median Absolute Deviation (MAD)0
Skewness5.0743354
Sum294
Variance1.2291899
MonotonicityNot monotonic
2023-12-12T20:53:53.721424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 159
74.3%
2 34
 
15.9%
3 8
 
3.7%
4 2
 
0.9%
5 2
 
0.9%
11 1
 
0.5%
6 1
 
0.5%
8 1
 
0.5%
(Missing) 6
 
2.8%
ValueCountFrequency (%)
1 159
74.3%
2 34
 
15.9%
3 8
 
3.7%
4 2
 
0.9%
5 2
 
0.9%
6 1
 
0.5%
8 1
 
0.5%
11 1
 
0.5%
ValueCountFrequency (%)
11 1
 
0.5%
8 1
 
0.5%
6 1
 
0.5%
5 2
 
0.9%
4 2
 
0.9%
3 8
 
3.7%
2 34
 
15.9%
1 159
74.3%

부속건축물수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
205 
1
 
4
3
 
2
0
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.8738318
Min length1

Unique

Unique3 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 205
95.8%
1 4
 
1.9%
3 2
 
0.9%
0 1
 
0.5%
5 1
 
0.5%
2 1
 
0.5%

Length

2023-12-12T20:53:53.904093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:53:54.069722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 205
95.8%
1 4
 
1.9%
3 2
 
0.9%
0 1
 
0.5%
5 1
 
0.5%
2 1
 
0.5%

Sample

건축구분대지위치지목대지면적(㎡)건축면적(㎡)연면적(㎡)증축연면적(㎡)건폐율(%)용적률(%)구조취소구분철거멸실구분허가취소일허가일최종설계변경일착공처리일착공예정일실제착공일착공연기일착공연기사유임시사용승인기간사용승인일건축허가최초접수일최대지상층수최대지하층수최고높이(m)동수승강기합비상승강기합하수처리시설명하수처리시설용량(㎥)주용도부속용도용도지역용도지구용도구역자주식옥내주차장(대)자주식옥외주차장(대)기계식옥내주차장(대)기계식옥외주차장(대)인근자주식주차장(대)인근기계식주차장(대)총주차장면적(㎡)주건축물수세대수호수가구수주차장대수부속건축물수
0용도변경경기도 화성시 매송면 원평리 227-18대330.0183.62229.98<NA>55.6468.78철근콘크리트구조<NA><NA><NA>2015-08-24<NA><NA><NA><NA><NA><NA><NA>2015-08-282015-08-182<NA>9.11<NA><NA>기타오수처리시설12.0단독주택제2종근린생활시설_일반음식점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>11<NA>
1용도변경경기도 화성시 능동 1064-5대2052.01636.7514998.57<NA>79.76499.85철근콘크리트구조<NA><NA><NA>2015-08-17<NA><NA><NA><NA><NA><NA><NA>2015-08-172015-08-0710342.214<NA>하수종말처리장연결<NA>제1종근린생활시설제2종근린생활시설,위락시설,판매시설일반상업지역<NA>제1종지구단위계획구역107<NA><NA><NA><NA><NA>1074179.81<NA><NA><NA>1<NA>
2증축경기도 화성시 팔탄면 지월리 389-35공장용지2999.0727.5727.5142.524.2624.26일반철골구조<NA><NA><NA>2015-08-05<NA>2015-08-052015-08-052015-08-05<NA><NA><NA>2015-08-062015-08-031<NA>10.11<NA><NA>기타오수처리시설4.0공장<NA>계획관리지역<NA><NA><NA>3<NA><NA><NA><NA>334.5<NA><NA><NA>1<NA>
3대수선경기도 화성시 정남면 덕절리 190-6대355.0137.05349.6<NA>38.6198.48철근콘크리트구조<NA><NA><NA>2015-08-04<NA>2015-08-062015-08-102015-08-10<NA><NA><NA>2015-08-272015-07-214013.211<NA>기타오수처리시설8.0단독주택다가구주택계획관리지역<NA><NA>45<NA><NA><NA><NA>9103.5<NA><NA>121<NA>
4증축경기도 화성시 반송동 63-3대271.8162.52484.2559.9159.79178.16철근콘크리트구조<NA><NA><NA>2015-07-24<NA>2015-07-272015-07-282015-07-28<NA><NA><NA>2015-08-042015-07-144<NA>14.651<NA><NA>하수종말처리장연결<NA>단독주택다가구주택, 소매점제2종일반주거지역<NA>제1종지구단위계획구역<NA>6<NA><NA><NA><NA>669.0<NA><NA>51<NA>
5증축경기도 화성시 반정동 604-3대363.5217.06725.02135.8459.71199.46철근콘크리트구조<NA><NA><NA>2015-07-23<NA>2015-07-272015-07-272015-07-27<NA><NA><NA>2015-08-242015-07-024<NA>16.7511<NA>하수종말처리장연결<NA>단독주택제1종근생(휴게음식점),다가구주택제2종일반주거지역<NA><NA><NA>8<NA><NA><NA><NA>892.0<NA><NA>71<NA>
6증축경기도 화성시 반정동 607-2대332.7198.59661.35127.6859.69198.78철근콘크리트구조<NA><NA><NA>2015-07-23<NA>2015-07-272015-07-272015-07-27<NA><NA><NA>2015-08-242015-07-094<NA>16.9511<NA>하수종말처리장연결<NA>단독주택제1종근생(휴게음식점),다가구주택제2종일반주거지역<NA>제1종지구단위계획구역<NA>8<NA><NA><NA><NA>892.0<NA><NA>71<NA>
7용도변경경기도 화성시 남양읍 남양리 2077-15 외1필지대954.8758.986194.4<NA>79.49481.24철근콘크리트구조<NA><NA><NA>2015-07-17<NA><NA><NA><NA><NA><NA><NA>2015-08-252015-07-107229.11312<NA>하수종말처리장연결<NA>숙박시설<NA>일반상업지역<NA><NA>42<NA><NA><NA><NA><NA>42485.0<NA><NA><NA>1<NA>
8용도변경경기도 화성시 정남면 괘랑리 1064-19잡종지1503.0266.7493.9<NA>17.7432.86일반철골구조<NA><NA><NA>2015-07-16<NA><NA><NA>2015-07-21<NA><NA><NA>2015-08-072015-06-303<NA>10.41<NA><NA>기타오수처리시설<NA>자동차관련시설<NA>자연녹지지역<NA><NA><NA>4<NA><NA><NA><NA>446.0<NA><NA><NA>1<NA>
9증축경기도 화성시 팔탄면 지월리 389-36 외1필지공장용지3174.0531.0531.0141.016.7316.73일반철골구조<NA><NA><NA>2015-07-082015-08-052015-07-102015-07-102015-07-10<NA><NA><NA>2015-08-202015-07-011<NA>10.11<NA><NA>기타오수처리시설4.0공장<NA>계획관리지역<NA><NA><NA>3<NA><NA><NA><NA>334.5<NA><NA><NA>1<NA>
건축구분대지위치지목대지면적(㎡)건축면적(㎡)연면적(㎡)증축연면적(㎡)건폐율(%)용적률(%)구조취소구분철거멸실구분허가취소일허가일최종설계변경일착공처리일착공예정일실제착공일착공연기일착공연기사유임시사용승인기간사용승인일건축허가최초접수일최대지상층수최대지하층수최고높이(m)동수승강기합비상승강기합하수처리시설명하수처리시설용량(㎥)주용도부속용도용도지역용도지구용도구역자주식옥내주차장(대)자주식옥외주차장(대)기계식옥내주차장(대)기계식옥외주차장(대)인근자주식주차장(대)인근기계식주차장(대)총주차장면적(㎡)주건축물수세대수호수가구수주차장대수부속건축물수
204신축경기도 화성시 봉담읍 동화리 556-9대296.7174.1490.3<NA>58.68165.25철근콘크리트구조<NA><NA><NA>2008-06-122015-04-102010-06-102010-06-112010-06-102010-06-10<NA><NA>2015-08-112008-05-294013.11<NA><NA>하수종말처리장연결<NA>단독주택제1종근생제2종일반주거지역<NA>제1종지구단위계획구역<NA>5<NA><NA><NA><NA>557.5<NA><NA>51<NA>
205신축경기도 화성시 향남읍 길성리 183-1 외2필지전1669.0647.65855.7<NA>38.851.27일반철골구조<NA><NA><NA>2008-03-252014-08-142008-05-282008-06-022008-06-02<NA><NA><NA>2015-08-072008-02-15209.61<NA><NA>기타오수처리시설10.0제1종근린생활시설제2종근린생활시설계획관리지역<NA><NA><NA>7<NA><NA><NA><NA>780.5<NA><NA><NA>1<NA>
206신축경기도 화성시 우정읍 화산리 701-49임야2206.0863.7863.7<NA>39.1539.15일반철골구조<NA><NA><NA>2008-03-032011-07-012010-04-022010-04-102010-02-282010-02-282010-02-28<NA>2015-08-072007-12-111010.152<NA><NA>현수미생물접촉방법5.0공장공장계획관리지역<NA><NA><NA>4<NA><NA><NA><NA>446.0<NA><NA><NA>2<NA>
207신축경기도 화성시 마도면 두곡리 494-12임야1653.0495.0495.0<NA>29.9529.95일반철골구조<NA><NA><NA>2007-12-202015-06-242008-04-142008-04-162008-04-16<NA><NA><NA>2015-08-042007-12-17108.43<NA><NA>기타오수처리시설8.0제2종근린생활시설사무소자연녹지지역<NA><NA><NA>4<NA><NA><NA><NA>446.0<NA><NA><NA>3<NA>
208신축경기도 화성시 봉담읍 덕우리 99 외1필지전1068.0395.74395.74<NA>37.0537.05경량철골구조<NA><NA><NA>2007-05-012015-01-272007-06-302007-06-252007-06-25<NA><NA><NA>2015-08-282007-03-13107.21<NA><NA>하수종말처리장연결<NA>제1종근린생활시설<NA>계획관리지역<NA><NA><NA>3<NA><NA><NA><NA>336.0<NA><NA><NA>1<NA>
209신축경기도 화성시 팔탄면 가재리 781공장용지42182.04038.198230.03<NA>9.5919.51철골철근콘크리트구조<NA><NA><NA>2006-07-112015-06-102008-08-112008-08-042008-07-012008-07-012008-07-01<NA>2015-08-312006-06-293016.421<NA>기타오수처리시설51.5공장<NA>자연녹지지역<NA><NA><NA>62<NA><NA><NA><NA>62760.5<NA><NA><NA>2<NA>
210신축경기도 화성시 송산면 삼존리 206-20대633.0120.6186.3<NA>19.0529.43일반철골구조<NA><NA><NA>2006-07-102014-05-012008-04-112008-04-142008-04-112008-07-012008-07-01<NA>2015-08-042006-06-232013.51<NA><NA>기타오수처리시설16.0제2종근린생활시설일반음식점 및 단독주택자연녹지지역<NA><NA>23<NA><NA><NA><NA>557.5<NA><NA>11<NA>
211신축경기도 화성시 팔탄면 기천리 177-23전770.0153.0459.0<NA>19.8723.84철근콘크리트구조<NA><NA><NA>2006-07-082014-12-312008-01-052007-12-262007-12-26<NA><NA><NA>2015-08-102006-06-26218.371<NA><NA>기타오수처리시설12.0제1종근린생활시설소매점보전관리지역<NA><NA>3<NA><NA><NA><NA><NA>334.5<NA><NA><NA>1<NA>
212신축경기도 화성시 매송면 어천리 511-2 외2필지답913.0170.71238.15<NA>18.726.08블록구조<NA><NA><NA>2004-10-082015-07-202015-07-302015-07-282015-07-28<NA><NA><NA>2015-08-182004-10-01209.31<NA><NA>기타오수처리시설3.0단독주택(다가구주택)제1종일반주거지역<NA><NA><NA>4<NA><NA><NA><NA>446.0<NA><NA>21<NA>
213신축경기도 화성시 남양읍 북양리 527-3창고용지1850.0504.44504.44<NA>27.2727.27일반철골구조<NA><NA><NA>2000-11-012015-03-052003-06-302003-07-032003-06-302002-11-01<NA><NA>2015-08-122000-10-18106.553<NA><NA>기타오수처리시설3.0창고시설<NA>계획관리지역<NA>접도구역<NA>3<NA><NA><NA><NA>334.5<NA><NA><NA>3<NA>