Overview

Dataset statistics

Number of variables26
Number of observations3195
Missing cells15372
Missing cells (%)18.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory667.8 KiB
Average record size in memory214.0 B

Variable types

Categorical13
Text6
Numeric5
Boolean1
Unsupported1

Alerts

last_load_dttm has constant value ""Constant
add_daeboo_yn is highly imbalanced (79.0%)Imbalance
main_mana_n is highly imbalanced (73.0%)Imbalance
jm_n is highly imbalanced (55.1%)Imbalance
sub_mana_n is highly imbalanced (81.1%)Imbalance
dis_restrict_yn is highly imbalanced (96.6%)Imbalance
acq_part_n is highly imbalanced (93.3%)Imbalance
account_n is highly imbalanced (97.0%)Imbalance
dev_work is highly imbalanced (97.1%)Imbalance
admi_n is highly imbalanced (50.9%)Imbalance
acq_way_n is highly imbalanced (73.9%)Imbalance
ydgy is highly imbalanced (50.4%)Imbalance
city_plan is highly imbalanced (83.7%)Imbalance
note has 2963 (92.7%) missing valuesMissing
daeboo_day has 3089 (96.7%) missing valuesMissing
dis_restrict_yn has 59 (1.8%) missing valuesMissing
plan_work has 3188 (99.8%) missing valuesMissing
dis_restrict_day has 3195 (100.0%) missing valuesMissing
plan_const has 2878 (90.1%) missing valuesMissing
fact_area is highly skewed (γ1 = 23.80298449)Skewed
acq_area is highly skewed (γ1 = 22.93398718)Skewed
fulladdr has unique valuesUnique
dis_restrict_day is an unsupported type, check if it needs cleaning or further analysisUnsupported
fact_area has 39 (1.2%) zerosZeros
acq_area has 52 (1.6%) zerosZeros

Reproduction

Analysis started2024-04-17 11:09:56.252415
Analysis finished2024-04-17 11:09:56.786498
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

add_daeboo_yn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
미대부
3089 
대부중
 
106

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미대부 3089
96.7%
대부중 106
 
3.3%

Length

2024-04-17T20:09:56.834693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:09:56.911322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미대부 3089
96.7%
대부중 106
 
3.3%

main_mana_n
Categorical

IMBALANCE 

Distinct28
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
부산광역시 기획조정실 재정관 회계재산담당관
2500 
부산광역시 도시계획실 도로계획과
368 
부산광역시 환경정책실 공원운영과
 
91
부산광역시 환경정책실 물정책국 하천관리과
 
81
부산광역시 환경정책실 산림생태과
 
38
Other values (23)
 
117

Length

Max length29
Median length23
Mean length21.912676
Min length10

Unique

Unique12 ?
Unique (%)0.4%

Sample

1st row부산광역시 환경정책실 물정책국 하천관리과
2nd row부산광역시 도시계획실 도로계획과
3rd row부산광역시 환경정책실 물정책국 하천관리과
4th row부산광역시 환경정책실 물정책국 하천관리과
5th row부산광역시 교통국 도시철도과

Common Values

ValueCountFrequency (%)
부산광역시 기획조정실 재정관 회계재산담당관 2500
78.2%
부산광역시 도시계획실 도로계획과 368
 
11.5%
부산광역시 환경정책실 공원운영과 91
 
2.8%
부산광역시 환경정책실 물정책국 하천관리과 81
 
2.5%
부산광역시 환경정책실 산림생태과 38
 
1.2%
부산광역시 도시계획실 건설행정과 28
 
0.9%
부산광역시 일자리경제실 관광마이스산업국 관광진흥과 16
 
0.5%
부산광역시 교통국 공공교통정책과 15
 
0.5%
부산광역시 푸른도시가꾸기사업소 10
 
0.3%
부산광역시 도시계획실 도시균형재생국 도시정비과 10
 
0.3%
Other values (18) 38
 
1.2%

Length

2024-04-17T20:09:57.003124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산광역시 3195
26.2%
회계재산담당관 2500
20.5%
기획조정실 2500
20.5%
재정관 2500
20.5%
도시계획실 409
 
3.4%
도로계획과 368
 
3.0%
환경정책실 210
 
1.7%
공원운영과 91
 
0.7%
물정책국 81
 
0.7%
하천관리과 81
 
0.7%
Other values (36) 252
 
2.1%

jm_n
Categorical

IMBALANCE 

Distinct20
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
대
2060 
답
253 
전
228 
잡종지
226 
임야
 
197
Other values (15)
231 

Length

Max length4
Median length1
Mean length1.3017214
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
대 2060
64.5%
답 253
 
7.9%
전 228
 
7.1%
잡종지 226
 
7.1%
임야 197
 
6.2%
도로 132
 
4.1%
묘지 18
 
0.6%
유지 15
 
0.5%
학교용지 14
 
0.4%
하천 9
 
0.3%
Other values (10) 43
 
1.3%

Length

2024-04-17T20:09:57.112558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대 2060
64.5%
답 253
 
7.9%
전 228
 
7.1%
잡종지 226
 
7.1%
임야 197
 
6.2%
도로 132
 
4.1%
묘지 18
 
0.6%
유지 15
 
0.5%
학교용지 14
 
0.4%
하천 9
 
0.3%
Other values (10) 43
 
1.3%

fulladdr
Text

UNIQUE 

Distinct3195
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
2024-04-17T20:09:57.391509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length21.993427
Min length17

Characters and Unicode

Total characters70269
Distinct characters136
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

Unique3195 ?
Unique (%)100.0%

Sample

1st row부산광역시 기장군 장안읍 임랑리 366-45
2nd row부산광역시 기장군 장안읍 임랑리 341-16
3rd row부산광역시 기장군 장안읍 좌동리 573-36
4th row부산광역시 기장군 장안읍 좌동리 573-37
5th row부산광역시 금정구 구서동 315-1
ValueCountFrequency (%)
부산광역시 3195
24.4%
영도구 686
 
5.2%
동구 583
 
4.5%
청학동 381
 
2.9%
부산진구 343
 
2.6%
해운대구 271
 
2.1%
기장군 236
 
1.8%
좌천동 194
 
1.5%
수정동 192
 
1.5%
범일동 162
 
1.2%
Other values (3287) 6851
52.3%
2024-04-17T20:09:57.784270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16053
22.8%
동 3811
 
5.4%
산 3675
 
5.2%
부 3611
 
5.1%
광 3261
 
4.6%
시 3195
 
4.5%
역 3195
 
4.5%
1 3026
 
4.3%
구 3010
 
4.3%
- 2968
 
4.2%
Other values (126) 24464
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35754
50.9%
Space Separator 16053
22.8%
Decimal Number 15494
22.0%
Dash Punctuation 2968
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3811
 
10.7%
산 3675
 
10.3%
부 3611
 
10.1%
광 3261
 
9.1%
시 3195
 
8.9%
역 3195
 
8.9%
구 3010
 
8.4%
영 897
 
2.5%
도 686
 
1.9%
대 515
 
1.4%
Other values (114) 9898
27.7%
Decimal Number
ValueCountFrequency (%)
1 3026
19.5%
2 2143
13.8%
4 1645
10.6%
3 1598
10.3%
5 1565
10.1%
0 1273
8.2%
7 1152
 
7.4%
8 1087
 
7.0%
6 1063
 
6.9%
9 942
 
6.1%
Space Separator
ValueCountFrequency (%)
16053
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2968
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35754
50.9%
Common 34515
49.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3811
 
10.7%
산 3675
 
10.3%
부 3611
 
10.1%
광 3261
 
9.1%
시 3195
 
8.9%
역 3195
 
8.9%
구 3010
 
8.4%
영 897
 
2.5%
도 686
 
1.9%
대 515
 
1.4%
Other values (114) 9898
27.7%
Common
ValueCountFrequency (%)
16053
46.5%
1 3026
 
8.8%
- 2968
 
8.6%
2 2143
 
6.2%
4 1645
 
4.8%
3 1598
 
4.6%
5 1565
 
4.5%
0 1273
 
3.7%
7 1152
 
3.3%
8 1087
 
3.1%
Other values (2) 2005
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35754
50.9%
ASCII 34515
49.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16053
46.5%
1 3026
 
8.8%
- 2968
 
8.6%
2 2143
 
6.2%
4 1645
 
4.8%
3 1598
 
4.6%
5 1565
 
4.5%
0 1273
 
3.7%
7 1152
 
3.3%
8 1087
 
3.1%
Other values (2) 2005
 
5.8%
Hangul
ValueCountFrequency (%)
동 3811
 
10.7%
산 3675
 
10.3%
부 3611
 
10.1%
광 3261
 
9.1%
시 3195
 
8.9%
역 3195
 
8.9%
구 3010
 
8.4%
영 897
 
2.5%
도 686
 
1.9%
대 515
 
1.4%
Other values (114) 9898
27.7%

note
Text

MISSING 

Distinct93
Distinct (%)40.1%
Missing2963
Missing (%)92.7%
Memory size25.1 KiB
2024-04-17T20:09:58.073385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length41
Mean length12.672414
Min length3

Characters and Unicode

Total characters2940
Distinct characters140
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

Unique79 ?
Unique (%)34.1%

Sample

1st row회계재산담당관-26766(2016.6.9.)호와 관련임.
2nd row쉼터, 간이운동시설
3rd row 대부가능면적:1755
4th row 대부가능면적:1755
5th row사진(분할전 괴정동 1040-77 참조)
ValueCountFrequency (%)
위임관리관(도시개발공사 76
24.3%
지적과(해운대구 23
 
7.3%
기존위임재산관코드 22
 
7.0%
22
 
7.0%
8417 21
 
6.7%
도형누락재산 7
 
2.2%
대부불가사유:공공용도로 6
 
1.9%
대부가능면적:1755 3
 
1.0%
회계재산담당관실-26985(07.12.24 3
 
1.0%
대부가능면적:328 2
 
0.6%
Other values (116) 128
40.9%
2024-04-17T20:09:58.481457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 186
 
6.3%
142
 
4.8%
( 117
 
4.0%
) 116
 
3.9%
임 101
 
3.4%
공 101
 
3.4%
대 100
 
3.4%
위 100
 
3.4%
도 97
 
3.3%
: 96
 
3.3%
Other values (130) 1784
60.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2052
69.8%
Decimal Number 379
 
12.9%
Space Separator 142
 
4.8%
Other Punctuation 123
 
4.2%
Open Punctuation 117
 
4.0%
Close Punctuation 116
 
3.9%
Dash Punctuation 11
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 186
 
9.1%
임 101
 
4.9%
공 101
 
4.9%
대 100
 
4.9%
위 100
 
4.9%
도 97
 
4.7%
사 92
 
4.5%
적 88
 
4.3%
시 83
 
4.0%
리 80
 
3.9%
Other values (113) 1024
49.9%
Decimal Number
ValueCountFrequency (%)
1 72
19.0%
4 48
12.7%
8 45
11.9%
2 44
11.6%
7 41
10.8%
6 29
7.7%
0 26
 
6.9%
9 25
 
6.6%
5 25
 
6.6%
3 24
 
6.3%
Other Punctuation
ValueCountFrequency (%)
: 96
78.0%
. 22
 
17.9%
, 5
 
4.1%
Space Separator
ValueCountFrequency (%)
142
100.0%
Open Punctuation
ValueCountFrequency (%)
( 117
100.0%
Close Punctuation
ValueCountFrequency (%)
) 116
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2052
69.8%
Common 888
30.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 186
 
9.1%
임 101
 
4.9%
공 101
 
4.9%
대 100
 
4.9%
위 100
 
4.9%
도 97
 
4.7%
사 92
 
4.5%
적 88
 
4.3%
시 83
 
4.0%
리 80
 
3.9%
Other values (113) 1024
49.9%
Common
ValueCountFrequency (%)
142
16.0%
( 117
13.2%
) 116
13.1%
: 96
10.8%
1 72
8.1%
4 48
 
5.4%
8 45
 
5.1%
2 44
 
5.0%
7 41
 
4.6%
6 29
 
3.3%
Other values (7) 138
15.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2052
69.8%
ASCII 888
30.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 186
 
9.1%
임 101
 
4.9%
공 101
 
4.9%
대 100
 
4.9%
위 100
 
4.9%
도 97
 
4.7%
사 92
 
4.5%
적 88
 
4.3%
시 83
 
4.0%
리 80
 
3.9%
Other values (113) 1024
49.9%
ASCII
ValueCountFrequency (%)
142
16.0%
( 117
13.2%
) 116
13.1%
: 96
10.8%
1 72
8.1%
4 48
 
5.4%
8 45
 
5.1%
2 44
 
5.0%
7 41
 
4.6%
6 29
 
3.3%
Other values (7) 138
15.5%

daeboo_day
Text

MISSING 

Distinct91
Distinct (%)85.8%
Missing3089
Missing (%)96.7%
Memory size25.1 KiB
2024-04-17T20:09:58.671908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length100
Median length17
Mean length24.745283
Min length17

Characters and Unicode

Total characters2623
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)77.4%

Sample

1st row20180301~20230228,20180301~20230228
2nd row20170829~20220828
3rd row20180101~20221231,20181001~20221231
4th row20180101~20221231,20180101~20221231
5th row20200611~20250610
ValueCountFrequency (%)
20200101~20241231 5
 
4.7%
20190101~20231231 4
 
3.8%
20200101~20231231 3
 
2.8%
20190218~20240217 2
 
1.9%
20180701~20230531 2
 
1.9%
20191015~20211014 2
 
1.9%
20190101~20231231,20190101~20231231 2
 
1.9%
20200501~20211231 2
 
1.9%
20200101~20211231 2
 
1.9%
20200311~20250310 1
 
0.9%
Other values (81) 81
76.4%
2024-04-17T20:09:58.965965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 748
28.5%
2 677
25.8%
1 457
17.4%
~ 152
 
5.8%
3 122
 
4.7%
9 95
 
3.6%
5 76
 
2.9%
8 75
 
2.9%
6 61
 
2.3%
4 59
 
2.2%
Other values (2) 101
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2425
92.5%
Math Symbol 152
 
5.8%
Other Punctuation 46
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 748
30.8%
2 677
27.9%
1 457
18.8%
3 122
 
5.0%
9 95
 
3.9%
5 76
 
3.1%
8 75
 
3.1%
6 61
 
2.5%
4 59
 
2.4%
7 55
 
2.3%
Math Symbol
ValueCountFrequency (%)
~ 152
100.0%
Other Punctuation
ValueCountFrequency (%)
, 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2623
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 748
28.5%
2 677
25.8%
1 457
17.4%
~ 152
 
5.8%
3 122
 
4.7%
9 95
 
3.6%
5 76
 
2.9%
8 75
 
2.9%
6 61
 
2.3%
4 59
 
2.2%
Other values (2) 101
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2623
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 748
28.5%
2 677
25.8%
1 457
17.4%
~ 152
 
5.8%
3 122
 
4.7%
9 95
 
3.6%
5 76
 
2.9%
8 75
 
2.9%
6 61
 
2.3%
4 59
 
2.2%
Other values (2) 101
 
3.9%

sub_mana_n
Categorical

IMBALANCE 

Distinct41
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
<NA>
2834 
부산광역시 영도구 도시안전국 도시안전과
 
49
부산광역시 기장군 안전도시국 도시기반조성과
 
36
부산광역시 동구 도시관리국 건설과
 
35
부산광역시 해운대구 미래도시국 늘푸른과
 
34
Other values (36)
 
207

Length

Max length25
Median length4
Mean length5.8647887
Min length4

Unique

Unique11 ?
Unique (%)0.3%

Sample

1st row부산광역시 기장군 안전도시국 도시기반조성과
2nd row부산광역시 기장군 안전도시국 도시기반조성과
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2834
88.7%
부산광역시 영도구 도시안전국 도시안전과 49
 
1.5%
부산광역시 기장군 안전도시국 도시기반조성과 36
 
1.1%
부산광역시 동구 도시관리국 건설과 35
 
1.1%
부산광역시 해운대구 미래도시국 늘푸른과 34
 
1.1%
부산광역시 서구 안전도시국 구민안전과 22
 
0.7%
부산광역시 금정구 안전도시국 건설과 20
 
0.6%
부산광역시 사하구 안전도시국 건설과 16
 
0.5%
부산광역시 남구 안전도시국 건설과 15
 
0.5%
부산광역시 수영구 복지환경국 일자리경제과 12
 
0.4%
Other values (31) 122
 
3.8%

Length

2024-04-17T20:09:59.088129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2834
66.4%
부산광역시 361
 
8.5%
안전도시국 143
 
3.4%
건설과 100
 
2.3%
해운대구 60
 
1.4%
도시안전과 51
 
1.2%
영도구 49
 
1.1%
도시안전국 49
 
1.1%
미래도시국 45
 
1.1%
동구 39
 
0.9%
Other values (49) 537
 
12.6%

area
Real number (ℝ)

Distinct721
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean582.58748
Minimum0
Maximum120293
Zeros17
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size28.2 KiB
2024-04-17T20:09:59.197484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median33
Q3176
95-th percentile1518.5
Maximum120293
Range120293
Interquartile range (IQR)169

Descriptive statistics

Standard deviation4078.0132
Coefficient of variation (CV)6.9998298
Kurtosis419.65821
Mean582.58748
Median Absolute Deviation (MAD)31
Skewness18.201731
Sum1861367
Variance16630192
MonotonicityNot monotonic
2024-04-17T20:09:59.330154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 206
 
6.4%
3 174
 
5.4%
2 145
 
4.5%
7 93
 
2.9%
6 78
 
2.4%
10 75
 
2.3%
13 58
 
1.8%
4 57
 
1.8%
20 55
 
1.7%
5 47
 
1.5%
Other values (711) 2207
69.1%
ValueCountFrequency (%)
0 17
 
0.5%
1 206
6.4%
2 145
4.5%
3 174
5.4%
4 57
 
1.8%
5 47
 
1.5%
6 78
 
2.4%
7 93
2.9%
8 44
 
1.4%
9 41
 
1.3%
ValueCountFrequency (%)
120293 1
< 0.1%
93675 1
< 0.1%
84991 1
< 0.1%
73416 1
< 0.1%
46134 1
< 0.1%
36619 1
< 0.1%
35281 1
< 0.1%
31802 1
< 0.1%
30969 1
< 0.1%
29985 1
< 0.1%

use_n
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
일반재산
2519 
행정재산
676 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반재산 2519
78.8%
행정재산 676
 
21.2%

Length

2024-04-17T20:09:59.449653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:09:59.546976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반재산 2519
78.8%
행정재산 676
 
21.2%

dis_restrict_yn
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing59
Missing (%)1.8%
Memory size6.4 KiB
False
3125 
True
 
11
(Missing)
 
59
ValueCountFrequency (%)
False 3125
97.8%
True 11
 
0.3%
(Missing) 59
 
1.8%
2024-04-17T20:09:59.616332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

fact_area
Real number (ℝ)

SKEWED  ZEROS 

Distinct669
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean375.77371
Minimum0
Maximum84991
Zeros39
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size28.2 KiB
2024-04-17T20:09:59.937473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median26
Q3139
95-th percentile1140.2
Maximum84991
Range84991
Interquartile range (IQR)133

Descriptive statistics

Standard deviation2583.8722
Coefficient of variation (CV)6.8761388
Kurtosis724.63853
Mean375.77371
Median Absolute Deviation (MAD)24
Skewness23.802984
Sum1200597
Variance6676395.5
MonotonicityNot monotonic
2024-04-17T20:10:00.070422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 209
 
6.5%
3 187
 
5.9%
2 163
 
5.1%
7 99
 
3.1%
6 89
 
2.8%
10 83
 
2.6%
13 60
 
1.9%
4 59
 
1.8%
20 57
 
1.8%
5 55
 
1.7%
Other values (659) 2134
66.8%
ValueCountFrequency (%)
0 39
 
1.2%
1 209
6.5%
2 163
5.1%
3 187
5.9%
4 59
 
1.8%
5 55
 
1.7%
6 89
2.8%
7 99
3.1%
8 46
 
1.4%
9 47
 
1.5%
ValueCountFrequency (%)
84991 1
< 0.1%
84418 1
< 0.1%
28879 1
< 0.1%
27354 1
< 0.1%
21115 1
< 0.1%
19738 1
< 0.1%
19586 1
< 0.1%
18950 1
< 0.1%
16860 1
< 0.1%
16024 1
< 0.1%

acq_part_n
Categorical

IMBALANCE 

Distinct16
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
<NA>
3106 
부산광역시 정책기획실 기획재정관 �
 
27
부산광역시 시민안전국 재난대응과
 
18
부산광역시 창조도시국 도시정비과
 
10
부산광역시 시민안전실 재난대응과
 
7
Other values (11)
 
27

Length

Max length19
Median length4
Mean length4.3733959
Min length4

Unique

Unique5 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3106
97.2%
부산광역시 정책기획실 기획재정관 � 27
 
0.8%
부산광역시 시민안전국 재난대응과 18
 
0.6%
부산광역시 창조도시국 도시정비과 10
 
0.3%
부산광역시 시민안전실 재난대응과 7
 
0.2%
부산광역시 기획관리실 법무담당관 6
 
0.2%
부산광역시 기획관리실 회계재산담당 5
 
0.2%
부산광역시 도시개발본부 건설방재관 5
 
0.2%
부산광역시 2
 
0.1%
부산광역시 건설본부 총무부 보상팀 2
 
0.1%
Other values (6) 7
 
0.2%

Length

2024-04-17T20:10:00.189012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3106
91.4%
부산광역시 89
 
2.6%
정책기획실 27
 
0.8%
기획재정관 27
 
0.8%
� 27
 
0.8%
재난대응과 25
 
0.7%
시민안전국 18
 
0.5%
기획관리실 13
 
0.4%
창조도시국 10
 
0.3%
도시정비과 10
 
0.3%
Other values (16) 46
 
1.4%

acq_area
Real number (ℝ)

SKEWED  ZEROS 

Distinct705
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean416.53271
Minimum0
Maximum84991
Zeros52
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size28.2 KiB
2024-04-17T20:10:00.302794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median30
Q3162
95-th percentile1420.6
Maximum84991
Range84991
Interquartile range (IQR)155

Descriptive statistics

Standard deviation2611.3762
Coefficient of variation (CV)6.2693184
Kurtosis690.88756
Mean416.53271
Median Absolute Deviation (MAD)28
Skewness22.933987
Sum1330822
Variance6819285.5
MonotonicityNot monotonic
2024-04-17T20:10:00.416429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 200
 
6.3%
3 166
 
5.2%
2 154
 
4.8%
7 95
 
3.0%
6 83
 
2.6%
10 75
 
2.3%
13 61
 
1.9%
4 58
 
1.8%
20 56
 
1.8%
5 56
 
1.8%
Other values (695) 2191
68.6%
ValueCountFrequency (%)
0 52
 
1.6%
1 200
6.3%
2 154
4.8%
3 166
5.2%
4 58
 
1.8%
5 56
 
1.8%
6 83
2.6%
7 95
3.0%
8 49
 
1.5%
9 44
 
1.4%
ValueCountFrequency (%)
84991 1
< 0.1%
84418 1
< 0.1%
28200 1
< 0.1%
21115 1
< 0.1%
19826 1
< 0.1%
19738 1
< 0.1%
19586 1
< 0.1%
18950 1
< 0.1%
16860 1
< 0.1%
16399 1
< 0.1%

gyjb
Text

Distinct208
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
2024-04-17T20:10:00.659417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length3
Mean length3.3042254
Min length3

Characters and Unicode

Total characters10557
Distinct characters12
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

Unique184 ?
Unique (%)5.8%

Sample

1st row1/1
2nd row1/1
3rd row1/1
4th row1/1
5th row1/1
ValueCountFrequency (%)
1/1 2838
88.8%
3/3 29
 
0.9%
2/2 25
 
0.8%
1/2 20
 
0.6%
2/3 19
 
0.6%
4/4 12
 
0.4%
3/4 12
 
0.4%
1/3 6
 
0.2%
1/5 6
 
0.2%
4/5 5
 
0.2%
Other values (198) 223
 
7.0%
2024-04-17T20:10:01.044160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5897
55.9%
/ 3195
30.3%
3 245
 
2.3%
2 245
 
2.3%
0 235
 
2.2%
5 142
 
1.3%
4 134
 
1.3%
6 122
 
1.2%
7 106
 
1.0%
9 105
 
1.0%
Other values (2) 131
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7331
69.4%
Other Punctuation 3226
30.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5897
80.4%
3 245
 
3.3%
2 245
 
3.3%
0 235
 
3.2%
5 142
 
1.9%
4 134
 
1.8%
6 122
 
1.7%
7 106
 
1.4%
9 105
 
1.4%
8 100
 
1.4%
Other Punctuation
ValueCountFrequency (%)
/ 3195
99.0%
. 31
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10557
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5897
55.9%
/ 3195
30.3%
3 245
 
2.3%
2 245
 
2.3%
0 235
 
2.2%
5 142
 
1.3%
4 134
 
1.3%
6 122
 
1.2%
7 106
 
1.0%
9 105
 
1.0%
Other values (2) 131
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10557
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5897
55.9%
/ 3195
30.3%
3 245
 
2.3%
2 245
 
2.3%
0 235
 
2.2%
5 142
 
1.3%
4 134
 
1.3%
6 122
 
1.2%
7 106
 
1.0%
9 105
 
1.0%
Other values (2) 131
 
1.2%

account_n
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
일반회계
3180 
도시및주거환경정비기금
 
10
교통사업특별회계
 
5

Length

Max length11
Median length4
Mean length4.028169
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반회계 3180
99.5%
도시및주거환경정비기금 10
 
0.3%
교통사업특별회계 5
 
0.2%

Length

2024-04-17T20:10:01.183585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:10:01.277890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반회계 3180
99.5%
도시및주거환경정비기금 10
 
0.3%
교통사업특별회계 5
 
0.2%

plan_work
Text

MISSING 

Distinct4
Distinct (%)57.1%
Missing3188
Missing (%)99.8%
Memory size25.1 KiB
2024-04-17T20:10:01.417475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length13
Mean length13
Min length7

Characters and Unicode

Total characters91
Distinct characters40
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

Unique2 ?
Unique (%)28.6%

Sample

1st row장림동 동원로얄듀크아파트 앞 도로확장 2차
2nd row재정비촉진지구
3rd row일단의주택단지조성사업지역
4th row일단의주택단지조성사업지역
5th row일단의주택단지조성사업지역
ValueCountFrequency (%)
일단의주택단지조성사업지역 3
27.3%
제1종지구단위계획구역 2
18.2%
장림동 1
 
9.1%
동원로얄듀크아파트 1
 
9.1%
앞 1
 
9.1%
도로확장 1
 
9.1%
2차 1
 
9.1%
재정비촉진지구 1
 
9.1%
2024-04-17T20:10:01.690786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 9
 
9.9%
단 8
 
8.8%
역 5
 
5.5%
구 5
 
5.5%
4
 
4.4%
일 3
 
3.3%
의 3
 
3.3%
주 3
 
3.3%
택 3
 
3.3%
조 3
 
3.3%
Other values (30) 45
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84
92.3%
Space Separator 4
 
4.4%
Decimal Number 3
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 9
 
10.7%
단 8
 
9.5%
역 5
 
6.0%
구 5
 
6.0%
일 3
 
3.6%
의 3
 
3.6%
주 3
 
3.6%
택 3
 
3.6%
조 3
 
3.6%
성 3
 
3.6%
Other values (27) 39
46.4%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 84
92.3%
Common 7
 
7.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 9
 
10.7%
단 8
 
9.5%
역 5
 
6.0%
구 5
 
6.0%
일 3
 
3.6%
의 3
 
3.6%
주 3
 
3.6%
택 3
 
3.6%
조 3
 
3.6%
성 3
 
3.6%
Other values (27) 39
46.4%
Common
ValueCountFrequency (%)
4
57.1%
1 2
28.6%
2 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 84
92.3%
ASCII 7
 
7.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 9
 
10.7%
단 8
 
9.5%
역 5
 
6.0%
구 5
 
6.0%
일 3
 
3.6%
의 3
 
3.6%
주 3
 
3.6%
택 3
 
3.6%
조 3
 
3.6%
성 3
 
3.6%
Other values (27) 39
46.4%
ASCII
ValueCountFrequency (%)
4
57.1%
1 2
28.6%
2 1
 
14.3%

dev_work
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
<NA>
3166 
재개발구역
 
9
개발제한구역
 
8
지방산업단지
 
4
재개발구역(양정1)
 
2
Other values (6)
 
6

Length

Max length15
Median length4
Mean length4.0244131
Min length3

Unique

Unique6 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3166
99.1%
재개발구역 9
 
0.3%
개발제한구역 8
 
0.3%
지방산업단지 4
 
0.1%
재개발구역(양정1) 2
 
0.1%
개발행위허가제한구역 1
 
< 0.1%
주택재건축정비구역도시재개발법 1
 
< 0.1%
택지개발예정지구 1
 
< 0.1%
일단의주택단지조성사업지역 1
 
< 0.1%
가야1 1
 
< 0.1%

Length

2024-04-17T20:10:01.803673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3166
99.1%
재개발구역 9
 
0.3%
개발제한구역 8
 
0.3%
지방산업단지 4
 
0.1%
재개발구역(양정1 2
 
0.1%
개발행위허가제한구역 1
 
< 0.1%
주택재건축정비구역도시재개발법 1
 
< 0.1%
택지개발예정지구 1
 
< 0.1%
일단의주택단지조성사업지역 1
 
< 0.1%
가야1 1
 
< 0.1%

admi_n
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
미등록
2519 
공공용재산
660 
공용재산
 
16

Length

Max length5
Median length3
Mean length3.4181534
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미등록 2519
78.8%
공공용재산 660
 
20.7%
공용재산 16
 
0.5%

Length

2024-04-17T20:10:01.917286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:10:02.009449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미등록 2519
78.8%
공공용재산 660
 
20.7%
공용재산 16
 
0.5%

dis_restrict_day
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3195
Missing (%)100.0%
Memory size28.2 KiB

gsjg
Real number (ℝ)

Distinct1698
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean675209.03
Minimum0
Maximum9750000
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size28.2 KiB
2024-04-17T20:10:02.111445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile55300
Q1254900
median508000
Q3778000
95-th percentile1970000
Maximum9750000
Range9750000
Interquartile range (IQR)523100

Descriptive statistics

Standard deviation727095.65
Coefficient of variation (CV)1.0768453
Kurtosis25.62334
Mean675209.03
Median Absolute Deviation (MAD)263800
Skewness3.8631903
Sum2.1572929 × 109
Variance5.2866808 × 1011
MonotonicityNot monotonic
2024-04-17T20:10:02.238472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
638600 54
 
1.7%
78000 31
 
1.0%
504400 28
 
0.9%
510000 25
 
0.8%
590900 24
 
0.8%
520000 16
 
0.5%
524700 15
 
0.5%
141900 15
 
0.5%
475000 14
 
0.4%
604600 14
 
0.4%
Other values (1688) 2959
92.6%
ValueCountFrequency (%)
0 1
 
< 0.1%
2370 1
 
< 0.1%
3460 1
 
< 0.1%
3950 1
 
< 0.1%
4140 1
 
< 0.1%
4260 4
0.1%
4580 1
 
< 0.1%
4940 1
 
< 0.1%
5040 1
 
< 0.1%
5360 1
 
< 0.1%
ValueCountFrequency (%)
9750000 1
< 0.1%
8640000 1
< 0.1%
8322000 1
< 0.1%
6366400 1
< 0.1%
6164000 1
< 0.1%
5997000 1
< 0.1%
5706000 1
< 0.1%
5604000 1
< 0.1%
5182000 1
< 0.1%
5085000 2
0.1%

acq_way_n
Categorical

IMBALANCE 

Distinct13
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
매입
2735 
누락재산등록
 
143
분할취득
 
101
수용
 
77
기타증가
 
74
Other values (8)
 
65

Length

Max length7
Median length2
Mean length2.3201878
Min length2

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row분할취득
2nd row분할취득
3rd row분할취득
4th row분할취득
5th row누락재산등록

Common Values

ValueCountFrequency (%)
매입 2735
85.6%
누락재산등록 143
 
4.5%
분할취득 101
 
3.2%
수용 77
 
2.4%
기타증가 74
 
2.3%
무상귀속 26
 
0.8%
교환취득 19
 
0.6%
신축 8
 
0.3%
양여 6
 
0.2%
기부채납 3
 
0.1%
Other values (3) 3
 
0.1%

Length

2024-04-17T20:10:02.347709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
매입 2735
85.6%
누락재산등록 143
 
4.5%
분할취득 101
 
3.2%
수용 77
 
2.4%
기타증가 74
 
2.3%
무상귀속 26
 
0.8%
교환취득 19
 
0.6%
신축 8
 
0.3%
양여 6
 
0.2%
기부채납 3
 
0.1%
Other values (3) 3
 
0.1%

acq_day
Real number (ℝ)

Distinct1288
Distinct (%)40.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19854835
Minimum19120515
Maximum20160511
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.2 KiB
2024-04-17T20:10:02.461920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19120515
5-th percentile19568001
Q119761122
median19880704
Q319981117
95-th percentile20103883
Maximum20160511
Range1039996
Interquartile range (IQR)219995

Descriptive statistics

Standard deviation178036.44
Coefficient of variation (CV)0.0089669057
Kurtosis0.775528
Mean19854835
Median Absolute Deviation (MAD)109698
Skewness-0.77737716
Sum6.3436199 × 1010
Variance3.1696973 × 1010
MonotonicityNot monotonic
2024-04-17T20:10:02.598640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19621207 111
 
3.5%
20000229 94
 
2.9%
19570912 79
 
2.5%
19820713 72
 
2.3%
19620621 39
 
1.2%
19561102 36
 
1.1%
20020429 32
 
1.0%
19561113 30
 
0.9%
19821209 27
 
0.8%
19900206 25
 
0.8%
Other values (1278) 2650
82.9%
ValueCountFrequency (%)
19120515 1
 
< 0.1%
19150206 6
0.2%
19170201 1
 
< 0.1%
19190201 9
0.3%
19191202 1
 
< 0.1%
19220916 1
 
< 0.1%
19230131 1
 
< 0.1%
19231108 1
 
< 0.1%
19240124 1
 
< 0.1%
19240605 1
 
< 0.1%
ValueCountFrequency (%)
20160511 1
 
< 0.1%
20160309 1
 
< 0.1%
20160219 3
0.1%
20160120 1
 
< 0.1%
20151221 1
 
< 0.1%
20151215 1
 
< 0.1%
20151211 1
 
< 0.1%
20151204 2
0.1%
20151202 1
 
< 0.1%
20151028 1
 
< 0.1%

ydgy
Categorical

IMBALANCE 

Distinct47
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
일반주거지역
1373 
<NA>
630 
제2종일반주거지역
278 
자연녹지지역
275 
일반상업지역
157 
Other values (42)
482 

Length

Max length21
Median length6
Mean length6.1320814
Min length4

Unique

Unique21 ?
Unique (%)0.7%

Sample

1st row자연녹지지역
2nd row자연녹지지역
3rd row자연녹지지역
4th row자연녹지지역
5th row제2종일반주거

Common Values

ValueCountFrequency (%)
일반주거지역 1373
43.0%
<NA> 630
19.7%
제2종일반주거지역 278
 
8.7%
자연녹지지역 275
 
8.6%
일반상업지역 157
 
4.9%
개발제한구역 137
 
4.3%
제3종일반주거지역 102
 
3.2%
준주거지역 60
 
1.9%
준공업지역 32
 
1.0%
자연녹지지역,개발제한구역 22
 
0.7%
Other values (37) 129
 
4.0%

Length

2024-04-17T20:10:02.716262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반주거지역 1374
42.9%
na 630
19.7%
제2종일반주거지역 286
 
8.9%
자연녹지지역 276
 
8.6%
일반상업지역 157
 
4.9%
개발제한구역 137
 
4.3%
제3종일반주거지역 102
 
3.2%
준주거지역 60
 
1.9%
준공업지역 33
 
1.0%
자연녹지지역,개발제한구역 22
 
0.7%
Other values (36) 129
 
4.0%

city_plan
Categorical

IMBALANCE 

Distinct39
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
<NA>
2854 
최고고도지구
 
100
최저고도지구
 
72
방화지구
 
44
아파트지구
 
21
Other values (34)
 
104

Length

Max length21
Median length4
Mean length4.2697966
Min length4

Unique

Unique18 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2854
89.3%
최고고도지구 100
 
3.1%
최저고도지구 72
 
2.3%
방화지구 44
 
1.4%
아파트지구 21
 
0.7%
중심지미관지구 14
 
0.4%
주거환경개선지구 11
 
0.3%
항만시설보호지구 10
 
0.3%
기타지구 7
 
0.2%
방화지구,중심지미관지구 7
 
0.2%
Other values (29) 55
 
1.7%

Length

2024-04-17T20:10:02.830044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2854
89.0%
최고고도지구 100
 
3.1%
최저고도지구 72
 
2.2%
방화지구 50
 
1.6%
아파트지구 21
 
0.7%
중심지미관지구 14
 
0.4%
주거환경개선지구 11
 
0.3%
항만시설보호지구 10
 
0.3%
제1종지구단위계획구역 8
 
0.2%
기타지구 7
 
0.2%
Other values (25) 58
 
1.8%

plan_const
Text

MISSING 

Distinct127
Distinct (%)40.1%
Missing2878
Missing (%)90.1%
Memory size25.1 KiB
2024-04-17T20:10:03.000747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length8.022082
Min length2

Characters and Unicode

Total characters2543
Distinct characters75
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)23.3%

Sample

1st row대로1류(접합)
2nd row기타유원지시설
3rd row도로저촉
4th row대로2류(폭 30M~35M)(접함),도시철도(저촉)
5th row기타유원지시설
ValueCountFrequency (%)
도로(접함 15
 
4.6%
광로2류접함 13
 
4.0%
소로3류접함 12
 
3.7%
도로(저촉 11
 
3.4%
대로3류접함 11
 
3.4%
도로(계획도로 11
 
3.4%
경관녹지 10
 
3.1%
도로(계획도로,접함 10
 
3.1%
광로3류접함 9
 
2.8%
소로2류접함 8
 
2.5%
Other values (113) 216
66.3%
2024-04-17T20:10:03.287796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 359
14.1%
류 203
 
8.0%
도 189
 
7.4%
접 179
 
7.0%
함 177
 
7.0%
, 139
 
5.5%
( 111
 
4.4%
) 111
 
4.4%
3 103
 
4.1%
촉 80
 
3.1%
Other values (65) 892
35.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1935
76.1%
Decimal Number 227
 
8.9%
Other Punctuation 140
 
5.5%
Open Punctuation 111
 
4.4%
Close Punctuation 111
 
4.4%
Space Separator 9
 
0.4%
Dash Punctuation 7
 
0.3%
Uppercase Letter 2
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 359
18.6%
류 203
10.5%
도 189
 
9.8%
접 179
 
9.3%
함 177
 
9.1%
촉 80
 
4.1%
저 80
 
4.1%
중 77
 
4.0%
소 65
 
3.4%
광 50
 
2.6%
Other values (50) 476
24.6%
Decimal Number
ValueCountFrequency (%)
3 103
45.4%
2 74
32.6%
1 36
 
15.9%
9 6
 
2.6%
4 6
 
2.6%
5 1
 
0.4%
0 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 139
99.3%
. 1
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 111
100.0%
Close Punctuation
ValueCountFrequency (%)
) 111
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1935
76.1%
Common 606
 
23.8%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 359
18.6%
류 203
10.5%
도 189
 
9.8%
접 179
 
9.3%
함 177
 
9.1%
촉 80
 
4.1%
저 80
 
4.1%
중 77
 
4.0%
소 65
 
3.4%
광 50
 
2.6%
Other values (50) 476
24.6%
Common
ValueCountFrequency (%)
, 139
22.9%
( 111
18.3%
) 111
18.3%
3 103
17.0%
2 74
12.2%
1 36
 
5.9%
9
 
1.5%
- 7
 
1.2%
9 6
 
1.0%
4 6
 
1.0%
Other values (4) 4
 
0.7%
Latin
ValueCountFrequency (%)
M 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1935
76.1%
ASCII 608
 
23.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 359
18.6%
류 203
10.5%
도 189
 
9.8%
접 179
 
9.3%
함 177
 
9.1%
촉 80
 
4.1%
저 80
 
4.1%
중 77
 
4.0%
소 65
 
3.4%
광 50
 
2.6%
Other values (50) 476
24.6%
ASCII
ValueCountFrequency (%)
, 139
22.9%
( 111
18.3%
) 111
18.3%
3 103
16.9%
2 74
12.2%
1 36
 
5.9%
9
 
1.5%
- 7
 
1.2%
9 6
 
1.0%
4 6
 
1.0%
Other values (5) 6
 
1.0%

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
2021-03-01 05:33:03
3195 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-03-01 05:33:03
2nd row2021-03-01 05:33:03
3rd row2021-03-01 05:33:03
4th row2021-03-01 05:33:03
5th row2021-03-01 05:33:03

Common Values

ValueCountFrequency (%)
2021-03-01 05:33:03 3195
100.0%

Length

2024-04-17T20:10:03.398793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:10:03.476455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-03-01 3195
50.0%
05:33:03 3195
50.0%

Sample

add_daeboo_ynmain_mana_njm_nfulladdrnotedaeboo_daysub_mana_nareause_ndis_restrict_ynfact_areaacq_part_nacq_areagyjbaccount_nplan_workdev_workadmi_ndis_restrict_daygsjgacq_way_nacq_dayydgycity_planplan_constlast_load_dttm
0미대부부산광역시 환경정책실 물정책국 하천관리과답부산광역시 기장군 장안읍 임랑리 366-45<NA><NA>부산광역시 기장군 안전도시국 도시기반조성과11행정재산N11<NA>111/1일반회계<NA><NA>공공용재산<NA>128300분할취득20120305자연녹지지역<NA><NA>2021-03-01 05:33:03
1미대부부산광역시 도시계획실 도로계획과답부산광역시 기장군 장안읍 임랑리 341-16<NA><NA>부산광역시 기장군 안전도시국 도시기반조성과83행정재산N83<NA>831/1일반회계<NA><NA>공공용재산<NA>130900분할취득20140224자연녹지지역<NA><NA>2021-03-01 05:33:03
2미대부부산광역시 환경정책실 물정책국 하천관리과답부산광역시 기장군 장안읍 좌동리 573-36<NA><NA><NA>247행정재산N247<NA>2471/1일반회계<NA><NA>공공용재산<NA>128000분할취득20141222자연녹지지역<NA><NA>2021-03-01 05:33:03
3미대부부산광역시 환경정책실 물정책국 하천관리과답부산광역시 기장군 장안읍 좌동리 573-37<NA><NA><NA>90행정재산N90<NA>901/1일반회계<NA><NA>공공용재산<NA>128000분할취득20141222자연녹지지역<NA><NA>2021-03-01 05:33:03
4미대부부산광역시 교통국 도시철도과대부산광역시 금정구 구서동 315-1회계재산담당관-26766(2016.6.9.)호와 관련임.<NA><NA>972행정재산N972<NA>9721/1일반회계<NA><NA>공공용재산<NA>343200누락재산등록19830128제2종일반주거<NA>대로1류(접합)2021-03-01 05:33:03
5미대부부산광역시 기획조정실 재정관 회계재산담당관잡종지부산광역시 기장군 장안읍 좌천리 510-258<NA><NA><NA>17일반재산N17<NA>61/1일반회계<NA><NA>미등록<NA>534300분할취득20150106자연녹지지역<NA><NA>2021-03-01 05:33:03
6미대부부산광역시 환경정책실 물정책국 하천관리과잡종지부산광역시 기장군 장안읍 좌천리 510-259<NA><NA>부산광역시 기장군 안전도시국 도시기반조성과125행정재산N125<NA>1621/1일반회계<NA><NA>공공용재산<NA>518200분할취득20150106자연녹지지역<NA><NA>2021-03-01 05:33:03
7미대부부산광역시 환경정책실 물정책국 하천관리과잡종지부산광역시 기장군 장안읍 좌천리 510-213<NA><NA><NA>70행정재산N70<NA>701/1일반회계<NA><NA>공공용재산<NA>231000분할취득20140710자연녹지지역<NA><NA>2021-03-01 05:33:03
8미대부부산광역시 기획조정실 재정관 회계재산담당관잡종지부산광역시 기장군 장안읍 좌천리 510-256<NA><NA><NA>1일반재산N1<NA>11/1일반회계<NA><NA>미등록<NA>567100분할취득20150106자연녹지지역<NA><NA>2021-03-01 05:33:03
9미대부부산광역시 기획조정실 재정관 회계재산담당관임야부산광역시 서구 서대신동3가 21-40<NA><NA><NA>15일반재산N15<NA>151/1일반회계<NA><NA>미등록<NA>597300분할취득20160219<NA><NA><NA>2021-03-01 05:33:03
add_daeboo_ynmain_mana_njm_nfulladdrnotedaeboo_daysub_mana_nareause_ndis_restrict_ynfact_areaacq_part_nacq_areagyjbaccount_nplan_workdev_workadmi_ndis_restrict_daygsjgacq_way_nacq_dayydgycity_planplan_constlast_load_dttm
3185미대부부산광역시 기획조정실 재정관 회계재산담당관대부산광역시 동구 좌천동 730-12<NA><NA><NA>93일반재산N93<NA>931/1일반회계<NA><NA>미등록<NA>240000매입19741210일반주거지역<NA><NA>2021-03-01 05:33:03
3186미대부부산광역시 기획조정실 재정관 회계재산담당관대부산광역시 동구 좌천동 734-2<NA><NA><NA>39일반재산N39<NA>391/1일반회계<NA><NA>미등록<NA>592200매입19750712일반주거지역<NA><NA>2021-03-01 05:33:03
3187미대부부산광역시 기획조정실 재정관 회계재산담당관대부산광역시 중구 영주동 1-89<NA><NA><NA>2507일반재산N1946<NA>561194600/250780일반회계<NA><NA>미등록<NA>492100매입19920831일반주거지역최고고도지구<NA>2021-03-01 05:33:03
3188미대부부산광역시 기획조정실 재정관 회계재산담당관대부산광역시 중구 영주동 1-959<NA><NA><NA>4일반재산N4<NA>41/1일반회계<NA><NA>미등록<NA>264000매입19570912일반주거지역최고고도지구<NA>2021-03-01 05:33:03
3189미대부부산광역시 기획조정실 재정관 회계재산담당관대부산광역시 중구 영주동 1-968<NA><NA><NA>12일반재산N12<NA>121/1일반회계<NA><NA>미등록<NA>283800매입19570914일반주거지역<NA><NA>2021-03-01 05:33:03
3190미대부부산광역시 기획조정실 재정관 회계재산담당관대부산광역시 중구 영주동 1-1012<NA><NA><NA>1578일반재산N89<NA>15788990/157890일반회계<NA><NA>미등록<NA>525300매입19950613일반주거지역최고고도지구<NA>2021-03-01 05:33:03
3191미대부부산광역시 기획조정실 재정관 회계재산담당관대부산광역시 중구 영주동 1-1013<NA><NA><NA>561일반재산N561<NA>5611/1일반회계<NA><NA>미등록<NA>362000매입19881111일반주거지역최고고도지구<NA>2021-03-01 05:33:03
3192미대부부산광역시 기획조정실 재정관 회계재산담당관대부산광역시 중구 영주동 2-10<NA><NA><NA>625일반재산N625<NA>71/1일반회계<NA><NA>미등록<NA>640500매입19570912일반주거지역최고고도지구<NA>2021-03-01 05:33:03
3193미대부부산광역시 기획조정실 재정관 회계재산담당관대부산광역시 중구 영주동 2-63<NA><NA><NA>256일반재산N256<NA>231/1일반회계<NA><NA>미등록<NA>559400매입19570912일반주거지역최고고도지구<NA>2021-03-01 05:33:03
3194미대부부산광역시 기획조정실 재정관 회계재산담당관대부산광역시 중구 영주동 2-69<NA><NA><NA>155일반재산N155<NA>201/1일반회계<NA><NA>미등록<NA>559400매입19570912일반주거지역최고고도지구<NA>2021-03-01 05:33:03