Overview

Dataset statistics

Number of variables21
Number of observations26
Missing cells37
Missing cells (%)6.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory185.1 B

Variable types

Categorical7
Text4
Numeric6
DateTime3
Unsupported1

Dataset

Description인천광역시 연수구 건축물 착공신고 현황(건축물 대지위치, 허가일, 대지면적(㎡), 건축면적(㎡), 연면적(㎡), 사용승인일, 주용도, 부속용도)
URLhttps://www.data.go.kr/data/15029299/fileData.do

Alerts

증축연면적 is highly imbalanced (55.4%)Imbalance
호수 is highly imbalanced (53.7%)Imbalance
가구수 is highly imbalanced (53.0%)Imbalance
부속용도 has 11 (42.3%) missing valuesMissing
기타구조 has 26 (100.0%) missing valuesMissing
허가번호 has unique valuesUnique
대지위치 has unique valuesUnique
대지면적 has unique valuesUnique
건축면적 has unique valuesUnique
연면적 has unique valuesUnique
기타구조 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 23:35:05.571190
Analysis finished2023-12-12 23:35:05.848818
Duration0.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

Distinct3
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
신축
17 
증축
5 
대수선
4 

Length

Max length3
Median length2
Mean length2.1538462
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신축 17
65.4%
증축 5
 
19.2%
대수선 4
 
15.4%

Length

2023-12-13T08:35:06.135837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:35:06.225669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 17
65.4%
증축 5
 
19.2%
대수선 4
 
15.4%

허가번호
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T08:35:06.385213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length15.653846
Min length15

Characters and Unicode

Total characters407
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row2019-건축과-신축허가-12
2nd row2021-건축과-대수선허가-5
3rd row2021-건축과-신축허가-16
4th row2021-건축과-신축허가-18
5th row2021-건축과-신축허가-21
ValueCountFrequency (%)
2019-건축과-신축허가-12 1
 
3.8%
2021-건축과-대수선허가-5 1
 
3.8%
2022-건축과-증축허가-1 1
 
3.8%
2022-건축과-신축허가-8 1
 
3.8%
2022-건축과-신축허가-3 1
 
3.8%
2022-건축과-신축허가-2 1
 
3.8%
2022-건축과-신축허가-10 1
 
3.8%
2022-건축과-신축허가-1 1
 
3.8%
2022-건축과-대수선허가-5 1
 
3.8%
2022-건축과-대수선허가-4 1
 
3.8%
Other values (16) 16
61.5%
2023-12-13T08:35:06.691288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 78
19.2%
2 71
17.4%
축 48
11.8%
0 28
 
6.9%
허 26
 
6.4%
과 26
 
6.4%
가 26
 
6.4%
건 26
 
6.4%
1 24
 
5.9%
신 17
 
4.2%
Other values (11) 37
9.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 186
45.7%
Decimal Number 143
35.1%
Dash Punctuation 78
19.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 71
49.7%
0 28
 
19.6%
1 24
 
16.8%
3 7
 
4.9%
5 4
 
2.8%
4 3
 
2.1%
6 2
 
1.4%
8 2
 
1.4%
9 1
 
0.7%
7 1
 
0.7%
Other Letter
ValueCountFrequency (%)
축 48
25.8%
허 26
14.0%
과 26
14.0%
가 26
14.0%
건 26
14.0%
신 17
 
9.1%
증 5
 
2.7%
대 4
 
2.2%
수 4
 
2.2%
선 4
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 221
54.3%
Hangul 186
45.7%

Most frequent character per script

Common
ValueCountFrequency (%)
- 78
35.3%
2 71
32.1%
0 28
 
12.7%
1 24
 
10.9%
3 7
 
3.2%
5 4
 
1.8%
4 3
 
1.4%
6 2
 
0.9%
8 2
 
0.9%
9 1
 
0.5%
Hangul
ValueCountFrequency (%)
축 48
25.8%
허 26
14.0%
과 26
14.0%
가 26
14.0%
건 26
14.0%
신 17
 
9.1%
증 5
 
2.7%
대 4
 
2.2%
수 4
 
2.2%
선 4
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 221
54.3%
Hangul 186
45.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 78
35.3%
2 71
32.1%
0 28
 
12.7%
1 24
 
10.9%
3 7
 
3.2%
5 4
 
1.8%
4 3
 
1.4%
6 2
 
0.9%
8 2
 
0.9%
9 1
 
0.5%
Hangul
ValueCountFrequency (%)
축 48
25.8%
허 26
14.0%
과 26
14.0%
가 26
14.0%
건 26
14.0%
신 17
 
9.1%
증 5
 
2.7%
대 4
 
2.2%
수 4
 
2.2%
선 4
 
2.2%

대지위치
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T08:35:06.865075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length31
Mean length23.884615
Min length21

Characters and Unicode

Total characters621
Distinct characters50
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row인천광역시 연수구 옥련동 581-22호
2nd row인천광역시 연수구 동춘동 1113-1번지 외 1필지
3rd row인천광역시 연수구 옥련동 468-8 외 2필지
4th row인천광역시 연수구 동춘1구역 28BL-6LT
5th row인천광역시 연수구 동춘2구역 근생용지 2-3BL
ValueCountFrequency (%)
인천광역시 26
21.1%
연수구 26
21.1%
동춘동 9
 
7.3%
외 6
 
4.9%
옥련동 5
 
4.1%
청학동 5
 
4.1%
1필지 4
 
3.3%
동춘1구역 2
 
1.6%
동춘1도시개발사업구역 2
 
1.6%
26블럭 2
 
1.6%
Other values (35) 36
29.3%
2023-12-13T08:35:07.139247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
97
 
15.6%
동 37
 
6.0%
역 31
 
5.0%
구 31
 
5.0%
시 28
 
4.5%
연 27
 
4.3%
수 27
 
4.3%
인 26
 
4.2%
광 26
 
4.2%
천 26
 
4.2%
Other values (40) 265
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 382
61.5%
Decimal Number 114
 
18.4%
Space Separator 97
 
15.6%
Dash Punctuation 22
 
3.5%
Uppercase Letter 6
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 37
 
9.7%
역 31
 
8.1%
구 31
 
8.1%
시 28
 
7.3%
연 27
 
7.1%
수 27
 
7.1%
인 26
 
6.8%
광 26
 
6.8%
천 26
 
6.8%
지 25
 
6.5%
Other values (25) 98
25.7%
Decimal Number
ValueCountFrequency (%)
1 21
18.4%
2 16
14.0%
6 14
12.3%
8 14
12.3%
3 12
10.5%
4 12
10.5%
7 8
 
7.0%
9 8
 
7.0%
5 7
 
6.1%
0 2
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
L 3
50.0%
B 2
33.3%
T 1
 
16.7%
Space Separator
ValueCountFrequency (%)
97
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 382
61.5%
Common 233
37.5%
Latin 6
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 37
 
9.7%
역 31
 
8.1%
구 31
 
8.1%
시 28
 
7.3%
연 27
 
7.1%
수 27
 
7.1%
인 26
 
6.8%
광 26
 
6.8%
천 26
 
6.8%
지 25
 
6.5%
Other values (25) 98
25.7%
Common
ValueCountFrequency (%)
97
41.6%
- 22
 
9.4%
1 21
 
9.0%
2 16
 
6.9%
6 14
 
6.0%
8 14
 
6.0%
3 12
 
5.2%
4 12
 
5.2%
7 8
 
3.4%
9 8
 
3.4%
Other values (2) 9
 
3.9%
Latin
ValueCountFrequency (%)
L 3
50.0%
B 2
33.3%
T 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 382
61.5%
ASCII 239
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
97
40.6%
- 22
 
9.2%
1 21
 
8.8%
2 16
 
6.7%
6 14
 
5.9%
8 14
 
5.9%
3 12
 
5.0%
4 12
 
5.0%
7 8
 
3.3%
9 8
 
3.3%
Other values (5) 15
 
6.3%
Hangul
ValueCountFrequency (%)
동 37
 
9.7%
역 31
 
8.1%
구 31
 
8.1%
시 28
 
7.3%
연 27
 
7.1%
수 27
 
7.1%
인 26
 
6.8%
광 26
 
6.8%
천 26
 
6.8%
지 25
 
6.5%
Other values (25) 98
25.7%

위도
Real number (ℝ)

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.416853
Minimum37.34875
Maximum37.433019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T08:35:07.247216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.34875
5-th percentile37.396454
Q137.415405
median37.421762
Q337.426093
95-th percentile37.430889
Maximum37.433019
Range0.084269
Interquartile range (IQR)0.010688

Descriptive statistics

Standard deviation0.016644799
Coefficient of variation (CV)0.00044484764
Kurtosis11.209777
Mean37.416853
Median Absolute Deviation (MAD)0.004587
Skewness-2.9986151
Sum972.83817
Variance0.00027704932
MonotonicityNot monotonic
2023-12-13T08:35:07.334918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
37.408136 2
 
7.7%
37.41591 1
 
3.8%
37.39625 1
 
3.8%
37.412585 1
 
3.8%
37.426245 1
 
3.8%
37.433019 1
 
3.8%
37.415237 1
 
3.8%
37.422221 1
 
3.8%
37.426207 1
 
3.8%
37.42501 1
 
3.8%
Other values (15) 15
57.7%
ValueCountFrequency (%)
37.34875 1
3.8%
37.39625 1
3.8%
37.397066 1
3.8%
37.408136 2
7.7%
37.412585 1
3.8%
37.415237 1
3.8%
37.41591 1
3.8%
37.417036 1
3.8%
37.418335 1
3.8%
37.41839 1
3.8%
ValueCountFrequency (%)
37.433019 1
3.8%
37.43205 1
3.8%
37.427405 1
3.8%
37.426416 1
3.8%
37.426281 1
3.8%
37.426245 1
3.8%
37.426207 1
3.8%
37.425752 1
3.8%
37.42501 1
3.8%
37.424077 1
3.8%

경도
Real number (ℝ)

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.66712
Minimum126.64517
Maximum126.70095
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T08:35:07.424899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.64517
5-th percentile126.65158
Q1126.65552
median126.6655
Q3126.67356
95-th percentile126.69572
Maximum126.70095
Range0.055786
Interquartile range (IQR)0.018046

Descriptive statistics

Standard deviation0.014311268
Coefficient of variation (CV)0.00011298329
Kurtosis0.32849683
Mean126.66712
Median Absolute Deviation (MAD)0.0099195
Skewness0.83897027
Sum3293.3451
Variance0.00020481238
MonotonicityNot monotonic
2023-12-13T08:35:07.529071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
126.670513 2
 
7.7%
126.672984 1
 
3.8%
126.663545 1
 
3.8%
126.654207 1
 
3.8%
126.651117 1
 
3.8%
126.700954 1
 
3.8%
126.656215 1
 
3.8%
126.685517 1
 
3.8%
126.665679 1
 
3.8%
126.668281 1
 
3.8%
Other values (15) 15
57.7%
ValueCountFrequency (%)
126.645168 1
3.8%
126.651117 1
3.8%
126.652961 1
3.8%
126.653661 1
3.8%
126.654207 1
3.8%
126.654956 1
3.8%
126.655451 1
3.8%
126.655718 1
3.8%
126.656215 1
3.8%
126.657699 1
3.8%
ValueCountFrequency (%)
126.700954 1
3.8%
126.699115 1
3.8%
126.685517 1
3.8%
126.683544 1
3.8%
126.680942 1
3.8%
126.676038 1
3.8%
126.673757 1
3.8%
126.672984 1
3.8%
126.670513 2
7.7%
126.670037 1
3.8%

대지면적
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42211.954
Minimum201.5
Maximum1074465.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T08:35:07.624286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201.5
5-th percentile222.4
Q1320
median397
Q31224.25
95-th percentile4812.475
Maximum1074465.9
Range1074264.4
Interquartile range (IQR)904.25

Descriptive statistics

Standard deviation210542.49
Coefficient of variation (CV)4.9877457
Kurtosis25.998238
Mean42211.954
Median Absolute Deviation (MAD)137.25
Skewness5.0987705
Sum1097510.8
Variance4.432814 × 1010
MonotonicityNot monotonic
2023-12-13T08:35:07.719929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
295.8 1
 
3.8%
291.5 1
 
3.8%
2557.0 1
 
3.8%
705.0 1
 
3.8%
308.0 1
 
3.8%
388.0 1
 
3.8%
363.1 1
 
3.8%
266.5 1
 
3.8%
513.7 1
 
3.8%
5564.3 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
201.5 1
3.8%
213.2 1
3.8%
250.0 1
3.8%
266.5 1
3.8%
291.5 1
3.8%
295.8 1
3.8%
308.0 1
3.8%
356.0 1
3.8%
363.1 1
3.8%
370.0 1
3.8%
ValueCountFrequency (%)
1074465.9 1
3.8%
5564.3 1
3.8%
2557.0 1
3.8%
2194.0 1
3.8%
2017.7 1
3.8%
1638.0 1
3.8%
1285.0 1
3.8%
1042.0 1
3.8%
705.0 1
3.8%
541.0 1
3.8%

건축면적
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6623.9777
Minimum106.16
Maximum163551.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T08:35:07.807251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106.16
5-th percentile109.98
Q1157.095
median223.395
Q3325.9875
95-th percentile1351.93
Maximum163551.26
Range163445.1
Interquartile range (IQR)168.8925

Descriptive statistics

Standard deviation32008.769
Coefficient of variation (CV)4.832258
Kurtosis25.993573
Mean6623.9777
Median Absolute Deviation (MAD)79.725
Skewness5.098112
Sum172223.42
Variance1.0245613 × 109
MonotonicityNot monotonic
2023-12-13T08:35:07.904275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
177.4 1
 
3.8%
168.75 1
 
3.8%
510.17 1
 
3.8%
287.89 1
 
3.8%
148.32 1
 
3.8%
229.74 1
 
3.8%
171.51 1
 
3.8%
131.9 1
 
3.8%
307.77 1
 
3.8%
1203.34 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
106.16 1
3.8%
106.82 1
3.8%
119.46 1
3.8%
126.54 1
3.8%
131.9 1
3.8%
148.32 1
3.8%
153.21 1
3.8%
168.75 1
3.8%
171.51 1
3.8%
177.4 1
3.8%
ValueCountFrequency (%)
163551.26 1
3.8%
1401.46 1
3.8%
1203.34 1
3.8%
940.26 1
3.8%
598.83 1
3.8%
510.17 1
3.8%
332.06 1
3.8%
307.77 1
3.8%
298.44 1
3.8%
297.0 1
3.8%

연면적
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5043.56
Minimum148.32
Maximum82796.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T08:35:08.006436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum148.32
5-th percentile189.0775
Q1322.05
median616.45
Q31018.73
95-th percentile18570.502
Maximum82796.29
Range82647.97
Interquartile range (IQR)696.68

Descriptive statistics

Standard deviation16467.651
Coefficient of variation (CV)3.2650848
Kurtosis21.945522
Mean5043.56
Median Absolute Deviation (MAD)365.52
Skewness4.5884686
Sum131132.56
Variance2.7118354 × 108
MonotonicityNot monotonic
2023-12-13T08:35:08.093618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
573.1 1
 
3.8%
398.02 1
 
3.8%
982.14 1
 
3.8%
867.22 1
 
3.8%
148.32 1
 
3.8%
721.33 1
 
3.8%
319.5 1
 
3.8%
247.02 1
 
3.8%
1026.54 1
 
3.8%
4671.74 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
148.32 1
3.8%
185.58 1
3.8%
199.57 1
3.8%
247.02 1
3.8%
306.4 1
3.8%
319.5 1
3.8%
319.72 1
3.8%
329.04 1
3.8%
398.02 1
3.8%
467.32 1
3.8%
ValueCountFrequency (%)
82796.29 1
3.8%
21834.5 1
3.8%
8778.51 1
3.8%
4671.74 1
3.8%
1152.83 1
3.8%
1135.91 1
3.8%
1026.54 1
3.8%
995.3 1
3.8%
982.14 1
3.8%
981.8 1
3.8%

증축연면적
Categorical

IMBALANCE 

Distinct6
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
21 
425.0
 
1
104.59
 
1
164.0
 
1
345.63
 
1

Length

Max length6
Median length4
Mean length4.2692308
Min length4

Unique

Unique5 ?
Unique (%)19.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 21
80.8%
425.0 1
 
3.8%
104.59 1
 
3.8%
164.0 1
 
3.8%
345.63 1
 
3.8%
73.26 1
 
3.8%

Length

2023-12-13T08:35:08.202220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:35:08.290659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
80.8%
425.0 1
 
3.8%
104.59 1
 
3.8%
164.0 1
 
3.8%
345.63 1
 
3.8%
73.26 1
 
3.8%

허가일
Date

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum2019-03-15 00:00:00
Maximum2022-06-13 00:00:00
2023-12-13T08:35:08.374643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:35:08.465866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

착공일
Date

Distinct23
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum2021-09-28 00:00:00
Maximum2022-08-22 00:00:00
2023-12-13T08:35:08.544162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:35:08.626388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

사용승인일
Date

Distinct24
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum2022-02-14 00:00:00
Maximum2023-02-20 00:00:00
2023-12-13T08:35:08.712108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:35:08.796795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

주용도
Text

Distinct14
Distinct (%)53.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T08:35:08.935688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.7307692
Min length4

Characters and Unicode

Total characters175
Distinct characters39
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)34.6%

Sample

1st row제1종근린생활시설
2nd row제1종근린생활시설
3rd row제2종근린생활시설
4th row단독주택
5th row제2종근린생활시설
ValueCountFrequency (%)
단독주택 6
21.4%
제2종근린생활시설 5
17.9%
제1종근린생활시설 2
 
7.1%
도시형생활주택 2
 
7.1%
교육연구시설 2
 
7.1%
공동주택 1
 
3.6%
단독주택(다중주택 1
 
3.6%
위험물 1
 
3.6%
저장처리시설 1
 
3.6%
의료시설 1
 
3.6%
Other values (6) 6
21.4%
2023-12-13T08:35:09.202501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 16
 
9.1%
설 14
 
8.0%
주 13
 
7.4%
택 13
 
7.4%
생 11
 
6.3%
활 11
 
6.3%
근 10
 
5.7%
린 10
 
5.7%
종 9
 
5.1%
제 8
 
4.6%
Other values (29) 60
34.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162
92.6%
Decimal Number 9
 
5.1%
Space Separator 2
 
1.1%
Close Punctuation 1
 
0.6%
Open Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 16
 
9.9%
설 14
 
8.6%
주 13
 
8.0%
택 13
 
8.0%
생 11
 
6.8%
활 11
 
6.8%
근 10
 
6.2%
린 10
 
6.2%
종 9
 
5.6%
제 8
 
4.9%
Other values (24) 47
29.0%
Decimal Number
ValueCountFrequency (%)
2 6
66.7%
1 3
33.3%
Space Separator
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162
92.6%
Common 13
 
7.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 16
 
9.9%
설 14
 
8.6%
주 13
 
8.0%
택 13
 
8.0%
생 11
 
6.8%
활 11
 
6.8%
근 10
 
6.2%
린 10
 
6.2%
종 9
 
5.6%
제 8
 
4.9%
Other values (24) 47
29.0%
Common
ValueCountFrequency (%)
2 6
46.2%
1 3
23.1%
2
 
15.4%
) 1
 
7.7%
( 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 162
92.6%
ASCII 13
 
7.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 16
 
9.9%
설 14
 
8.6%
주 13
 
8.0%
택 13
 
8.0%
생 11
 
6.8%
활 11
 
6.8%
근 10
 
6.2%
린 10
 
6.2%
종 9
 
5.6%
제 8
 
4.9%
Other values (24) 47
29.0%
ASCII
ValueCountFrequency (%)
2 6
46.2%
1 3
23.1%
2
 
15.4%
) 1
 
7.7%
( 1
 
7.7%

부속용도
Text

MISSING 

Distinct13
Distinct (%)86.7%
Missing11
Missing (%)42.3%
Memory size340.0 B
2023-12-13T08:35:09.339915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length10
Mean length6.5333333
Min length3

Characters and Unicode

Total characters98
Distinct characters48
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)73.3%

Sample

1st row다세대주택
2nd row제2종근생(사무소)
3rd row근린생활시설
4th row주유소
5th row근린생활시설
ValueCountFrequency (%)
일반음식점 3
16.7%
근린생활시설 2
 
11.1%
다세대주택 1
 
5.6%
제2종근생(사무소 1
 
5.6%
주유소 1
 
5.6%
자동차관련시설 1
 
5.6%
주차장 1
 
5.6%
유치원 1
 
5.6%
교육연구시설및 1
 
5.6%
복지시설 1
 
5.6%
Other values (5) 5
27.8%
2023-12-13T08:35:09.589175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 7
 
7.1%
설 7
 
7.1%
근 4
 
4.1%
점 4
 
4.1%
생 4
 
4.1%
소 4
 
4.1%
주 4
 
4.1%
3
 
3.1%
린 3
 
3.1%
사 3
 
3.1%
Other values (38) 55
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91
92.9%
Space Separator 3
 
3.1%
Decimal Number 2
 
2.0%
Close Punctuation 1
 
1.0%
Open Punctuation 1
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 7
 
7.7%
설 7
 
7.7%
근 4
 
4.4%
점 4
 
4.4%
생 4
 
4.4%
소 4
 
4.4%
주 4
 
4.4%
린 3
 
3.3%
사 3
 
3.3%
유 3
 
3.3%
Other values (33) 48
52.7%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91
92.9%
Common 7
 
7.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 7
 
7.7%
설 7
 
7.7%
근 4
 
4.4%
점 4
 
4.4%
생 4
 
4.4%
소 4
 
4.4%
주 4
 
4.4%
린 3
 
3.3%
사 3
 
3.3%
유 3
 
3.3%
Other values (33) 48
52.7%
Common
ValueCountFrequency (%)
3
42.9%
1 1
 
14.3%
) 1
 
14.3%
( 1
 
14.3%
2 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91
92.9%
ASCII 7
 
7.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 7
 
7.7%
설 7
 
7.7%
근 4
 
4.4%
점 4
 
4.4%
생 4
 
4.4%
소 4
 
4.4%
주 4
 
4.4%
린 3
 
3.3%
사 3
 
3.3%
유 3
 
3.3%
Other values (33) 48
52.7%
ASCII
ValueCountFrequency (%)
3
42.9%
1 1
 
14.3%
) 1
 
14.3%
( 1
 
14.3%
2 1
 
14.3%

주구조
Categorical

Distinct4
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size340.0 B
철근콘크리트구조
20 
목구조
4 
일반철골구조
 
1
철골 구조
 
1

Length

Max length8
Median length8
Mean length7.0384615
Min length3

Unique

Unique2 ?
Unique (%)7.7%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트구조 20
76.9%
목구조 4
 
15.4%
일반철골구조 1
 
3.8%
철골 구조 1
 
3.8%

Length

2023-12-13T08:35:09.698845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:35:09.778961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근콘크리트구조 20
74.1%
목구조 4
 
14.8%
일반철골구조 1
 
3.7%
철골 1
 
3.7%
구조 1
 
3.7%

기타구조
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

지상층수
Real number (ℝ)

Distinct7
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6923077
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T08:35:09.851573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median3
Q35
95-th percentile6.5
Maximum12
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.2408789
Coefficient of variation (CV)0.60690472
Kurtosis6.7465931
Mean3.6923077
Median Absolute Deviation (MAD)1
Skewness2.1512862
Sum96
Variance5.0215385
MonotonicityNot monotonic
2023-12-13T08:35:09.932298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 9
34.6%
5 6
23.1%
3 4
15.4%
4 4
15.4%
12 1
 
3.8%
7 1
 
3.8%
1 1
 
3.8%
ValueCountFrequency (%)
1 1
 
3.8%
2 9
34.6%
3 4
15.4%
4 4
15.4%
5 6
23.1%
7 1
 
3.8%
12 1
 
3.8%
ValueCountFrequency (%)
12 1
 
3.8%
7 1
 
3.8%
5 6
23.1%
4 4
15.4%
3 4
15.4%
2 9
34.6%
1 1
 
3.8%

지하층수
Categorical

Distinct5
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
0
17 
1
5 
<NA>
2 
5
 
1
2
 
1

Length

Max length4
Median length1
Mean length1.2307692
Min length1

Unique

Unique2 ?
Unique (%)7.7%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 17
65.4%
1 5
 
19.2%
<NA> 2
 
7.7%
5 1
 
3.8%
2 1
 
3.8%

Length

2023-12-13T08:35:10.026031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:35:10.112387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 17
65.4%
1 5
 
19.2%
na 2
 
7.7%
5 1
 
3.8%
2 1
 
3.8%

세대수
Categorical

Distinct6
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
18 
1
2 
3
2 
15
2 
10
 
1

Length

Max length4
Median length4
Mean length3.1923077
Min length1

Unique

Unique2 ?
Unique (%)7.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 18
69.2%
1 2
 
7.7%
3 2
 
7.7%
15 2
 
7.7%
10 1
 
3.8%
6 1
 
3.8%

Length

2023-12-13T08:35:10.208134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:35:10.298767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
69.2%
1 2
 
7.7%
3 2
 
7.7%
15 2
 
7.7%
10 1
 
3.8%
6 1
 
3.8%

호수
Categorical

IMBALANCE 

Distinct5
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
21 
2
 
2
3
 
1
12
 
1
95
 
1

Length

Max length4
Median length4
Mean length3.5
Min length1

Unique

Unique3 ?
Unique (%)11.5%

Sample

1st row3
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row12

Common Values

ValueCountFrequency (%)
<NA> 21
80.8%
2 2
 
7.7%
3 1
 
3.8%
12 1
 
3.8%
95 1
 
3.8%

Length

2023-12-13T08:35:10.392205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:35:10.482952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
80.8%
2 2
 
7.7%
3 1
 
3.8%
12 1
 
3.8%
95 1
 
3.8%

가구수
Categorical

IMBALANCE 

Distinct3
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
22 
1
3 
5
 
1

Length

Max length4
Median length4
Mean length3.5384615
Min length1

Unique

Unique1 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 22
84.6%
1 3
 
11.5%
5 1
 
3.8%

Length

2023-12-13T08:35:10.594777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:35:10.681917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 22
84.6%
1 3
 
11.5%
5 1
 
3.8%

Sample

건축구분허가번호대지위치위도경도대지면적건축면적연면적증축연면적허가일착공일사용승인일주용도부속용도주구조기타구조지상층수지하층수세대수호수가구수
0신축2019-건축과-신축허가-12인천광역시 연수구 옥련동 581-22호37.417036126.655451295.8177.4573.1<NA>2019-03-152021-11-042022-06-16제1종근린생활시설<NA>철근콘크리트구조<NA>31<NA>3<NA>
1대수선2021-건축과-대수선허가-5인천광역시 연수구 동춘동 1113-1번지 외 1필지37.41591126.6729841638.0598.831152.83<NA>2021-12-222022-01-102022-05-06제1종근린생활시설<NA>철근콘크리트구조<NA>20<NA><NA><NA>
2신축2021-건축과-신축허가-16인천광역시 연수구 옥련동 468-8 외 2필지37.421302126.6451681042.0332.06503.34<NA>2021-08-302021-09-282022-05-13제2종근린생활시설<NA>철근콘크리트구조<NA>20<NA><NA><NA>
3신축2021-건축과-신축허가-18인천광역시 연수구 동춘1구역 28BL-6LT37.41839126.655718394.4195.74306.4<NA>2021-09-102021-10-042022-10-13단독주택<NA>철근콘크리트구조<NA>20<NA><NA>1
4신축2021-건축과-신축허가-21인천광역시 연수구 동춘2구역 근생용지 2-3BL37.422491126.654956541.0298.441135.91<NA>2021-09-132022-03-292022-09-29제2종근린생활시설<NA>철근콘크리트구조<NA>41<NA>12<NA>
5신축2021-건축과-신축허가-22인천광역시 연수구 동춘동 동춘1도시개발사업구역 19블럭 8루트37.426416126.683544399.6153.21319.72<NA>2021-09-162021-10-082022-06-23단독주택<NA>목구조<NA>211<NA><NA>
6신축2021-건축과-신축허가-23인천광역시 연수구 동춘동 동춘1도시개발사업구역 26블럭 7루트37.427405126.657699250.0106.16199.57<NA>2021-09-282021-10-122022-04-04단독주택<NA>목구조<NA>201<NA><NA>
7신축2021-건축과-신축허가-24인천광역시 연수구 옥견동369-3 외 1필지37.423408126.653661356.0211.3659.8<NA>2021-10-012021-11-052022-04-26공동주택다세대주택철근콘크리트구조<NA>5010<NA><NA>
8신축2021-건축과-신축허가-26인천광역시 연수구 청학동 470-7번지37.418335126.673757213.2126.54531.72<NA>2021-10-212021-11-092022-05-31단독주택(다중주택)제2종근생(사무소)철근콘크리트구조<NA>5032<NA>
9신축2021-건축과-신축허가-27인천광역시 연수구 청학동 562-8번지37.426281126.665329497.7297.0995.3<NA>2021-10-262021-11-052022-05-04도시형생활주택<NA>철근콘크리트구조<NA>5015<NA><NA>
건축구분허가번호대지위치위도경도대지면적건축면적연면적증축연면적허가일착공일사용승인일주용도부속용도주구조기타구조지상층수지하층수세대수호수가구수
16대수선2022-건축과-대수선허가-1인천광역시 연수구 옥련동 374-5번지37.424077126.652961370.0217.05981.8<NA>2022-01-042022-01-172022-03-07교육연구시설유치원철근콘크리트구조<NA>40<NA><NA><NA>
17대수선2022-건축과-대수선허가-4인천광역시 연수구 동춘동 937-3 외2필지37.408136126.6705132194.0940.268778.51<NA>2022-03-252022-03-312022-11-15제1종 2종근린생활시설교육연구시설및 복지시설 노유자시설철근콘크리트구조<NA>72<NA><NA><NA>
18대수선2022-건축과-대수선허가-5인천광역시 연수구 청학동 448-2번지37.42501126.6682815564.31203.344671.74<NA>2022-06-102022-08-222023-02-20근린공공시설배전사업소철근콘크리트구조<NA>51<NA><NA><NA>
19신축2022-건축과-신축허가-1인천광역시 연수구 청학동 567-2번지37.426207126.665679513.7307.771026.54<NA>2022-01-282022-03-202022-08-26도시형생활주택<NA>철근콘크리트구조<NA>5<NA>15<NA><NA>
20신축2022-건축과-신축허가-10인천광역시 연수구 옥련동 417-18번지 외 1필지37.422221126.685517266.5131.9247.02<NA>2022-06-132022-07-292023-02-20단독주택<NA>목구조<NA>20<NA><NA>1
21신축2022-건축과-신축허가-2인천광역시 연수구 동춘동 810-6번지37.415237126.656215363.1171.51319.5<NA>2022-02-242022-04-012022-08-30근린생활시설사무소철근콘크리트구조<NA>2<NA><NA><NA><NA>
22신축2022-건축과-신축허가-3인천광역시 연수구 선학동 92-26번지37.433019126.700954388.0229.74721.33<NA>2022-03-022022-04-052022-10-13다세대주택제1종근린생활시설철근콘크리트구조<NA>406<NA><NA>
23신축2022-건축과-신축허가-8인천광역시 연수구 옥련동 249-4번지 외 1필지37.426245126.651117308.0148.32148.32<NA>2022-06-102022-06-212022-12-07제2종근린생활시설일반음식점철골 구조<NA>10<NA><NA><NA>
24증축2022-건축과-증축허가-1인천광역시 연수구 동춘동 816-4번지37.412585126.654207705.0287.89867.22345.632022-02-232022-03-312022-05-16제2종근린생활시설일반음식점 단란주점철근콘크리트구조<NA>31<NA><NA><NA>
25증축2022-건축과-증축허가-2인천광역시 연수구 동춘동 698-1번지37.39625126.6635452557.0510.17982.1473.262022-03-212022-03-312022-06-02제2종근린생활시설일반음식점철근콘크리트구조<NA>30<NA><NA><NA>