Overview

Dataset statistics

Number of variables26
Number of observations3205
Missing cells15354
Missing cells (%)18.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory669.9 KiB
Average record size in memory214.0 B

Variable types

Categorical12
Text6
Numeric5
Boolean1
Unsupported1
DateTime1

Alerts

add_daeboo_yn is highly imbalanced (70.1%)Imbalance
main_mana_n is highly imbalanced (72.8%)Imbalance
jm_n is highly imbalanced (55.0%)Imbalance
sub_mana_n is highly imbalanced (81.2%)Imbalance
dis_restrict_yn is highly imbalanced (96.6%)Imbalance
acq_part_n is highly imbalanced (93.3%)Imbalance
account_n is highly imbalanced (97.4%)Imbalance
dev_work is highly imbalanced (97.1%)Imbalance
admi_n is highly imbalanced (50.7%)Imbalance
acq_way_n is highly imbalanced (74.0%)Imbalance
ydgy is highly imbalanced (50.5%)Imbalance
city_plan is highly imbalanced (83.6%)Imbalance
note has 2971 (92.7%) missing valuesMissing
daeboo_day has 3035 (94.7%) missing valuesMissing
dis_restrict_yn has 59 (1.8%) missing valuesMissing
plan_work has 3198 (99.8%) missing valuesMissing
dis_restrict_day has 3205 (100.0%) missing valuesMissing
plan_const has 2886 (90.0%) missing valuesMissing
fact_area is highly skewed (γ1 = 23.84441755)Skewed
acq_area is highly skewed (γ1 = 22.96880988)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 11:07:41.292114
Analysis finished2024-04-17 11:07:41.915126
Duration0.62 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 size25.2 KiB
미대부
3035 
대부중
 
170

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 3035
94.7%
대부중 170
 
5.3%

Length

2024-04-17T20:07:41.965080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:07:42.040322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미대부 3035
94.7%
대부중 170
 
5.3%

main_mana_n
Categorical

IMBALANCE 

Distinct28
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
부산광역시 기획조정실 재정관 회계재산담당관
2503 
부산광역시 도시계획실 도로계획과
368 
부산광역시 환경정책실 공원운영과
 
98
부산광역시 환경정책실 물정책국 하천관리과
 
81
부산광역시 환경정책실 산림생태과
 
38
Other values (23)
 
117

Length

Max length29
Median length23
Mean length21.902964
Min length10

Unique

Unique12 ?
Unique (%)0.4%

Sample

1st row부산광역시 도시계획실 도시균형재생국 도시정비과
2nd row부산광역시 기획조정실 재정관 회계재산담당관
3rd row부산광역시 환경정책실 산림생태과
4th row부산광역시 기획조정실 재정관 회계재산담당관
5th row부산광역시 기획조정실 재정관 회계재산담당관

Common Values

ValueCountFrequency (%)
부산광역시 기획조정실 재정관 회계재산담당관 2503
78.1%
부산광역시 도시계획실 도로계획과 368
 
11.5%
부산광역시 환경정책실 공원운영과 98
 
3.1%
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 도시계획실 도시균형재생국 도시정비과 10
 
0.3%
부산광역시 푸른도시가꾸기사업소 10
 
0.3%
Other values (18) 38
 
1.2%

Length

2024-04-17T20:07:42.138934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산광역시 3205
26.2%
회계재산담당관 2503
20.5%
기획조정실 2503
20.5%
재정관 2503
20.5%
도시계획실 409
 
3.3%
도로계획과 368
 
3.0%
환경정책실 217
 
1.8%
공원운영과 98
 
0.8%
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 size25.2 KiB
대
2064 
답
253 
전
232 
잡종지
227 
임야
 
197
Other values (15)
232 

Length

Max length4
Median length1
Mean length1.3017161
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row대
2nd row대
3rd row임야
4th row전
5th row하천

Common Values

ValueCountFrequency (%)
대 2064
64.4%
답 253
 
7.9%
전 232
 
7.2%
잡종지 227
 
7.1%
임야 197
 
6.1%
도로 133
 
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

2024-04-17T20:07:42.245767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대 2064
64.4%
답 253
 
7.9%
전 232
 
7.2%
잡종지 227
 
7.1%
임야 197
 
6.1%
도로 133
 
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 

Distinct3205
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
2024-04-17T20:07:42.518169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length21.994384
Min length17

Characters and Unicode

Total characters70492
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

Unique3205 ?
Unique (%)100.0%

Sample

1st row부산광역시 남구 대연동 1865
2nd row부산광역시 서구 암남동 81-129
3rd row부산광역시 해운대구 재송동 산 74-76
4th row부산광역시 기장군 기장읍 내리 701-106
5th row부산광역시 기장군 철마면 웅천리 879-66
ValueCountFrequency (%)
부산광역시 3205
24.4%
영도구 686
 
5.2%
동구 583
 
4.4%
청학동 381
 
2.9%
부산진구 343
 
2.6%
해운대구 271
 
2.1%
기장군 237
 
1.8%
좌천동 194
 
1.5%
수정동 192
 
1.5%
범일동 162
 
1.2%
Other values (3296) 6881
52.4%
2024-04-17T20:07:42.914455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16103
22.8%
동 3823
 
5.4%
산 3686
 
5.2%
부 3621
 
5.1%
광 3271
 
4.6%
시 3205
 
4.5%
역 3205
 
4.5%
1 3036
 
4.3%
구 3019
 
4.3%
- 2978
 
4.2%
Other values (126) 24545
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35867
50.9%
Space Separator 16103
22.8%
Decimal Number 15544
22.1%
Dash Punctuation 2978
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3823
 
10.7%
산 3686
 
10.3%
부 3621
 
10.1%
광 3271
 
9.1%
시 3205
 
8.9%
역 3205
 
8.9%
구 3019
 
8.4%
영 897
 
2.5%
도 686
 
1.9%
대 515
 
1.4%
Other values (114) 9939
27.7%
Decimal Number
ValueCountFrequency (%)
1 3036
19.5%
2 2154
13.9%
4 1648
10.6%
3 1602
10.3%
5 1567
10.1%
0 1275
8.2%
7 1156
 
7.4%
8 1095
 
7.0%
6 1066
 
6.9%
9 945
 
6.1%
Space Separator
ValueCountFrequency (%)
16103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2978
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35867
50.9%
Common 34625
49.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3823
 
10.7%
산 3686
 
10.3%
부 3621
 
10.1%
광 3271
 
9.1%
시 3205
 
8.9%
역 3205
 
8.9%
구 3019
 
8.4%
영 897
 
2.5%
도 686
 
1.9%
대 515
 
1.4%
Other values (114) 9939
27.7%
Common
ValueCountFrequency (%)
16103
46.5%
1 3036
 
8.8%
- 2978
 
8.6%
2 2154
 
6.2%
4 1648
 
4.8%
3 1602
 
4.6%
5 1567
 
4.5%
0 1275
 
3.7%
7 1156
 
3.3%
8 1095
 
3.2%
Other values (2) 2011
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35867
50.9%
ASCII 34625
49.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16103
46.5%
1 3036
 
8.8%
- 2978
 
8.6%
2 2154
 
6.2%
4 1648
 
4.8%
3 1602
 
4.6%
5 1567
 
4.5%
0 1275
 
3.7%
7 1156
 
3.3%
8 1095
 
3.2%
Other values (2) 2011
 
5.8%
Hangul
ValueCountFrequency (%)
동 3823
 
10.7%
산 3686
 
10.3%
부 3621
 
10.1%
광 3271
 
9.1%
시 3205
 
8.9%
역 3205
 
8.9%
구 3019
 
8.4%
영 897
 
2.5%
도 686
 
1.9%
대 515
 
1.4%
Other values (114) 9939
27.7%

note
Text

MISSING 

Distinct95
Distinct (%)40.6%
Missing2971
Missing (%)92.7%
Memory size25.2 KiB
2024-04-17T20:07:43.223785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length41
Mean length12.760684
Min length3

Characters and Unicode

Total characters2986
Distinct characters148
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

Unique81 ?
Unique (%)34.6%

Sample

1st row쉼터, 간이운동시설
2nd row 대부가능면적:1755
3rd row 대부가능면적:1755
4th row진우도
5th row진우도
ValueCountFrequency (%)
위임관리관(도시개발공사 76
23.7%
지적과(해운대구 23
 
7.2%
기존위임재산관코드 22
 
6.9%
22
 
6.9%
8417 21
 
6.5%
도형누락재산 7
 
2.2%
대부불가사유:공공용도로 6
 
1.9%
공유 3
 
0.9%
회계재산담당관실-26985(07.12.24 3
 
0.9%
대부가능면적:1755 3
 
0.9%
Other values (123) 135
42.1%
2024-04-17T20:07:43.628489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 186
 
6.2%
148
 
5.0%
( 118
 
4.0%
) 117
 
3.9%
공 103
 
3.4%
임 101
 
3.4%
위 100
 
3.3%
대 100
 
3.3%
도 97
 
3.2%
: 96
 
3.2%
Other values (138) 1820
61.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2082
69.7%
Decimal Number 384
 
12.9%
Space Separator 148
 
5.0%
Other Punctuation 126
 
4.2%
Open Punctuation 118
 
4.0%
Close Punctuation 117
 
3.9%
Dash Punctuation 11
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 186
 
8.9%
공 103
 
4.9%
임 101
 
4.9%
위 100
 
4.8%
대 100
 
4.8%
도 97
 
4.7%
사 92
 
4.4%
적 89
 
4.3%
시 84
 
4.0%
부 80
 
3.8%
Other values (121) 1050
50.4%
Decimal Number
ValueCountFrequency (%)
1 73
19.0%
4 49
12.8%
8 45
11.7%
2 44
11.5%
7 41
10.7%
6 29
 
7.6%
9 26
 
6.8%
5 26
 
6.8%
0 26
 
6.8%
3 25
 
6.5%
Other Punctuation
ValueCountFrequency (%)
: 96
76.2%
. 23
 
18.3%
, 7
 
5.6%
Space Separator
ValueCountFrequency (%)
148
100.0%
Open Punctuation
ValueCountFrequency (%)
( 118
100.0%
Close Punctuation
ValueCountFrequency (%)
) 117
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2082
69.7%
Common 904
30.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 186
 
8.9%
공 103
 
4.9%
임 101
 
4.9%
위 100
 
4.8%
대 100
 
4.8%
도 97
 
4.7%
사 92
 
4.4%
적 89
 
4.3%
시 84
 
4.0%
부 80
 
3.8%
Other values (121) 1050
50.4%
Common
ValueCountFrequency (%)
148
16.4%
( 118
13.1%
) 117
12.9%
: 96
10.6%
1 73
8.1%
4 49
 
5.4%
8 45
 
5.0%
2 44
 
4.9%
7 41
 
4.5%
6 29
 
3.2%
Other values (7) 144
15.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2082
69.7%
ASCII 904
30.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 186
 
8.9%
공 103
 
4.9%
임 101
 
4.9%
위 100
 
4.8%
대 100
 
4.8%
도 97
 
4.7%
사 92
 
4.4%
적 89
 
4.3%
시 84
 
4.0%
부 80
 
3.8%
Other values (121) 1050
50.4%
ASCII
ValueCountFrequency (%)
148
16.4%
( 118
13.1%
) 117
12.9%
: 96
10.6%
1 73
8.1%
4 49
 
5.4%
8 45
 
5.0%
2 44
 
4.9%
7 41
 
4.5%
6 29
 
3.2%
Other values (7) 144
15.9%

daeboo_day
Text

MISSING 

Distinct114
Distinct (%)67.1%
Missing3035
Missing (%)94.7%
Memory size25.2 KiB
2024-04-17T20:07:43.844992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length100
Median length17
Mean length30.411765
Min length17

Characters and Unicode

Total characters5170
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

Unique99 ?
Unique (%)58.2%

Sample

1st row20180301~20230228,20180301~20230228
2nd row20200101~20241231,20160101~20201231,20160101~20201231
3rd row20190101~20201231,20190101~20201231
4th row20190101~20201231,20190101~20201231
5th row20170829~20220828
ValueCountFrequency (%)
20190101~20201231 11
 
6.5%
20190101~20201231,20190101~20201231 10
 
5.9%
20160101~20201231,20160101~20201231 9
 
5.3%
20160101~20201231 9
 
5.3%
20160101~20201231,20160101~20201231,20160101~20201231 4
 
2.4%
20160101~20201231,20160101~20201231,20160101~20201231,20160101~20201231 4
 
2.4%
20190101~20231231 4
 
2.4%
20180101~20201231 4
 
2.4%
20200101~20231231 3
 
1.8%
20200101~20241231 3
 
1.8%
Other values (104) 109
64.1%
2024-04-17T20:07:44.175084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1466
28.4%
2 1268
24.5%
1 1168
22.6%
~ 299
 
5.8%
3 261
 
5.0%
6 143
 
2.8%
9 139
 
2.7%
, 129
 
2.5%
5 91
 
1.8%
8 86
 
1.7%
Other values (2) 120
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4742
91.7%
Math Symbol 299
 
5.8%
Other Punctuation 129
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1466
30.9%
2 1268
26.7%
1 1168
24.6%
3 261
 
5.5%
6 143
 
3.0%
9 139
 
2.9%
5 91
 
1.9%
8 86
 
1.8%
7 61
 
1.3%
4 59
 
1.2%
Math Symbol
ValueCountFrequency (%)
~ 299
100.0%
Other Punctuation
ValueCountFrequency (%)
, 129
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5170
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1466
28.4%
2 1268
24.5%
1 1168
22.6%
~ 299
 
5.8%
3 261
 
5.0%
6 143
 
2.8%
9 139
 
2.7%
, 129
 
2.5%
5 91
 
1.8%
8 86
 
1.7%
Other values (2) 120
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5170
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1466
28.4%
2 1268
24.5%
1 1168
22.6%
~ 299
 
5.8%
3 261
 
5.0%
6 143
 
2.8%
9 139
 
2.7%
, 129
 
2.5%
5 91
 
1.8%
8 86
 
1.7%
Other values (2) 120
 
2.3%

sub_mana_n
Categorical

IMBALANCE 

Distinct43
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
<NA>
2841 
부산광역시 영도구 도시안전국 도시안전과
 
49
부산광역시 기장군 안전도시국 도시기반조성과
 
36
부산광역시 동구 도시관리국 건설과
 
35
부산광역시 해운대구 미래도시국 늘푸른과
 
34
Other values (38)
 
210

Length

Max length25
Median length4
Mean length5.8783151
Min length4

Unique

Unique12 ?
Unique (%)0.4%

Sample

1st row<NA>
2nd row<NA>
3rd row부산광역시 해운대구 미래도시국 늘푸른과
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2841
88.6%
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 (33) 125
 
3.9%

Length

2024-04-17T20:07:44.297707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2841
66.3%
부산광역시 364
 
8.5%
안전도시국 156
 
3.6%
건설과 100
 
2.3%
해운대구 60
 
1.4%
도시안전과 51
 
1.2%
영도구 49
 
1.1%
도시안전국 49
 
1.1%
동구 39
 
0.9%
도시관리국 38
 
0.9%
Other values (51) 540
 
12.6%

area
Real number (ℝ)

Distinct723
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean581.11201
Minimum0
Maximum120293
Zeros17
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-17T20:07:44.405576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median33
Q3176
95-th percentile1510.6
Maximum120293
Range120293
Interquartile range (IQR)169

Descriptive statistics

Standard deviation4071.7423
Coefficient of variation (CV)7.0068115
Kurtosis420.96466
Mean581.11201
Median Absolute Deviation (MAD)31
Skewness18.229931
Sum1862464
Variance16579086
MonotonicityNot monotonic
2024-04-17T20:07:44.527802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 208
 
6.5%
3 174
 
5.4%
2 147
 
4.6%
7 93
 
2.9%
6 78
 
2.4%
10 75
 
2.3%
4 58
 
1.8%
13 58
 
1.8%
20 55
 
1.7%
5 47
 
1.5%
Other values (713) 2212
69.0%
ValueCountFrequency (%)
0 17
 
0.5%
1 208
6.5%
2 147
4.6%
3 174
5.4%
4 58
 
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 size25.2 KiB
일반재산
2522 
행정재산
683 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반재산 2522
78.7%
행정재산 683
 
21.3%

Length

2024-04-17T20:07:44.639832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:07:44.985471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반재산 2522
78.7%
행정재산 683
 
21.3%

dis_restrict_yn
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing59
Missing (%)1.8%
Memory size6.4 KiB
False
3135 
True
 
11
(Missing)
 
59
ValueCountFrequency (%)
False 3135
97.8%
True 11
 
0.3%
(Missing) 59
 
1.8%
2024-04-17T20:07:45.054774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

fact_area
Real number (ℝ)

SKEWED  ZEROS 

Distinct670
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean374.63744
Minimum0
Maximum84991
Zeros39
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-17T20:07:45.153162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median26
Q3139
95-th percentile1131.8
Maximum84991
Range84991
Interquartile range (IQR)133

Descriptive statistics

Standard deviation2579.7255
Coefficient of variation (CV)6.8859255
Kurtosis727.08024
Mean374.63744
Median Absolute Deviation (MAD)24
Skewness23.844418
Sum1200713
Variance6654983.8
MonotonicityNot monotonic
2024-04-17T20:07:45.275206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 212
 
6.6%
3 187
 
5.8%
2 164
 
5.1%
7 99
 
3.1%
6 89
 
2.8%
10 83
 
2.6%
13 60
 
1.9%
4 60
 
1.9%
20 57
 
1.8%
5 55
 
1.7%
Other values (660) 2139
66.7%
ValueCountFrequency (%)
0 39
 
1.2%
1 212
6.6%
2 164
5.1%
3 187
5.8%
4 60
 
1.9%
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 size25.2 KiB
<NA>
3116 
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 length4.3722309
Min length4

Unique

Unique5 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3116
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 기획관리실 재정관 회계� 2
 
0.1%
Other values (6) 7
 
0.2%

Length

2024-04-17T20:07:45.396333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3116
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
 
1.3%

acq_area
Real number (ℝ)

SKEWED  ZEROS 

Distinct706
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean415.51638
Minimum0
Maximum84991
Zeros52
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-17T20:07:45.514840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation2607.3798
Coefficient of variation (CV)6.2750349
Kurtosis693.00427
Mean415.51638
Median Absolute Deviation (MAD)28
Skewness22.96881
Sum1331730
Variance6798429.4
MonotonicityNot monotonic
2024-04-17T20:07:45.635179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 203
 
6.3%
3 166
 
5.2%
2 155
 
4.8%
7 95
 
3.0%
6 83
 
2.6%
10 75
 
2.3%
13 61
 
1.9%
4 59
 
1.8%
5 56
 
1.7%
20 56
 
1.7%
Other values (696) 2196
68.5%
ValueCountFrequency (%)
0 52
 
1.6%
1 203
6.3%
2 155
4.8%
3 166
5.2%
4 59
 
1.8%
5 56
 
1.7%
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

Distinct212
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
2024-04-17T20:07:45.879996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length3
Mean length3.3113885
Min length3

Characters and Unicode

Total characters10613
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

Unique188 ?
Unique (%)5.9%

Sample

1st row3641897/100000000
2nd row1/1
3rd row1/1
4th row1/1
5th row1/1
ValueCountFrequency (%)
1/1 2844
88.7%
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%
1/5 6
 
0.2%
1/3 6
 
0.2%
4/5 5
 
0.2%
Other values (202) 227
 
7.1%
2024-04-17T20:07:46.265293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5911
55.7%
/ 3205
30.2%
2 248
 
2.3%
3 247
 
2.3%
0 244
 
2.3%
5 144
 
1.4%
4 139
 
1.3%
6 124
 
1.2%
9 111
 
1.0%
7 108
 
1.0%
Other values (2) 132
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7377
69.5%
Other Punctuation 3236
30.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5911
80.1%
2 248
 
3.4%
3 247
 
3.3%
0 244
 
3.3%
5 144
 
2.0%
4 139
 
1.9%
6 124
 
1.7%
9 111
 
1.5%
7 108
 
1.5%
8 101
 
1.4%
Other Punctuation
ValueCountFrequency (%)
/ 3205
99.0%
. 31
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10613
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5911
55.7%
/ 3205
30.2%
2 248
 
2.3%
3 247
 
2.3%
0 244
 
2.3%
5 144
 
1.4%
4 139
 
1.3%
6 124
 
1.2%
9 111
 
1.0%
7 108
 
1.0%
Other values (2) 132
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10613
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5911
55.7%
/ 3205
30.2%
2 248
 
2.3%
3 247
 
2.3%
0 244
 
2.3%
5 144
 
1.4%
4 139
 
1.3%
6 124
 
1.2%
9 111
 
1.0%
7 108
 
1.0%
Other values (2) 132
 
1.2%

account_n
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
일반회계
3189 
도시및주거환경정비기금
 
10
교통사업특별회계
 
5
항만배후도로건설사업특별회계
 
1

Length

Max length14
Median length4
Mean length4.0312012
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반회계 3189
99.5%
도시및주거환경정비기금 10
 
0.3%
교통사업특별회계 5
 
0.2%
항만배후도로건설사업특별회계 1
 
< 0.1%

Length

2024-04-17T20:07:46.391155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:07:46.486067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반회계 3189
99.5%
도시및주거환경정비기금 10
 
0.3%
교통사업특별회계 5
 
0.2%
항만배후도로건설사업특별회계 1
 
< 0.1%

plan_work
Text

MISSING 

Distinct4
Distinct (%)57.1%
Missing3198
Missing (%)99.8%
Memory size25.2 KiB
2024-04-17T20:07:46.619067image/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%
2024-04-17T20:07:46.878233image/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 size25.2 KiB
<NA>
3176 
재개발구역
 
9
개발제한구역
 
8
지방산업단지
 
4
재개발구역(양정1)
 
2
Other values (6)
 
6

Length

Max length15
Median length4
Mean length4.024337
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> 3176
99.1%
재개발구역 9
 
0.3%
개발제한구역 8
 
0.2%
지방산업단지 4
 
0.1%
재개발구역(양정1) 2
 
0.1%
개발행위허가제한구역 1
 
< 0.1%
주택재건축정비구역도시재개발법 1
 
< 0.1%
일단의주택단지조성사업지역 1
 
< 0.1%
가야1 1
 
< 0.1%
택지개발예정지구 1
 
< 0.1%

Length

2024-04-17T20:07:46.994259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3176
99.1%
재개발구역 9
 
0.3%
개발제한구역 8
 
0.2%
지방산업단지 4
 
0.1%
재개발구역(양정1 2
 
0.1%
개발행위허가제한구역 1
 
< 0.1%
주택재건축정비구역도시재개발법 1
 
< 0.1%
일단의주택단지조성사업지역 1
 
< 0.1%
가야1 1
 
< 0.1%
택지개발예정지구 1
 
< 0.1%

admi_n
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
미등록
2522 
공공용재산
667 
공용재산
 
16

Length

Max length5
Median length3
Mean length3.4212168
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미등록 2522
78.7%
공공용재산 667
 
20.8%
공용재산 16
 
0.5%

Length

2024-04-17T20:07:47.114249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:07:47.212632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미등록 2522
78.7%
공공용재산 667
 
20.8%
공용재산 16
 
0.5%

dis_restrict_day
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3205
Missing (%)100.0%
Memory size28.3 KiB

gsjg
Real number (ℝ)

Distinct1703
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean676413.31
Minimum0
Maximum9750000
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-17T20:07:47.326669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile55580
Q1257400
median508200
Q3780000
95-th percentile1970000
Maximum9750000
Range9750000
Interquartile range (IQR)522600

Descriptive statistics

Standard deviation727647.4
Coefficient of variation (CV)1.0757438
Kurtosis25.45422
Mean676413.31
Median Absolute Deviation (MAD)264000
Skewness3.8484536
Sum2.1679047 × 109
Variance5.2947074 × 1011
MonotonicityNot monotonic
2024-04-17T20:07:47.451216image/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
 
0.7%
520000 16
 
0.5%
141900 15
 
0.5%
524700 15
 
0.5%
475000 14
 
0.4%
604600 14
 
0.4%
Other values (1693) 2969
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 size25.2 KiB
매입
2744 
누락재산등록
 
144
분할취득
 
101
수용
 
77
기타증가
 
74
Other values (8)
 
65

Length

Max length7
Median length2
Mean length2.3204368
Min length2

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
매입 2744
85.6%
누락재산등록 144
 
4.5%
분할취득 101
 
3.2%
수용 77
 
2.4%
기타증가 74
 
2.3%
무상귀속 26
 
0.8%
교환취득 19
 
0.6%
신축 8
 
0.2%
양여 6
 
0.2%
기부채납 3
 
0.1%
Other values (3) 3
 
0.1%

Length

2024-04-17T20:07:47.560067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
매입 2744
85.6%
누락재산등록 144
 
4.5%
분할취득 101
 
3.2%
수용 77
 
2.4%
기타증가 74
 
2.3%
무상귀속 26
 
0.8%
교환취득 19
 
0.6%
신축 8
 
0.2%
양여 6
 
0.2%
기부채납 3
 
0.1%
Other values (3) 3
 
0.1%

acq_day
Real number (ℝ)

Distinct1295
Distinct (%)40.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19855141
Minimum19120515
Maximum20160511
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-17T20:07:47.668867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19120515
5-th percentile19570911
Q119761129
median19880721
Q319981126
95-th percentile20101217
Maximum20160511
Range1039996
Interquartile range (IQR)219997

Descriptive statistics

Standard deviation177877.46
Coefficient of variation (CV)0.0089587609
Kurtosis0.78354405
Mean19855141
Median Absolute Deviation (MAD)109711
Skewness-0.78104632
Sum6.3635726 × 1010
Variance3.164039 × 1010
MonotonicityNot monotonic
2024-04-17T20:07:47.798063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19621207 111
 
3.5%
20000229 95
 
3.0%
19570912 79
 
2.5%
19820713 72
 
2.2%
19620621 39
 
1.2%
19561102 36
 
1.1%
20020429 32
 
1.0%
19561113 30
 
0.9%
19821209 27
 
0.8%
19820820 25
 
0.8%
Other values (1285) 2659
83.0%
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 size25.2 KiB
일반주거지역
1377 
<NA>
633 
제2종일반주거지역
280 
자연녹지지역
276 
일반상업지역
157 
Other values (42)
482 

Length

Max length21
Median length6
Mean length6.1316693
Min length4

Unique

Unique21 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
일반주거지역 1377
43.0%
<NA> 633
19.8%
제2종일반주거지역 280
 
8.7%
자연녹지지역 276
 
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

2024-04-17T20:07:47.914977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반주거지역 1378
42.8%
na 633
19.7%
제2종일반주거지역 288
 
9.0%
자연녹지지역 277
 
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 

Distinct40
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
<NA>
2861 
최고고도지구
 
100
최저고도지구
 
72
방화지구
 
44
아파트지구
 
22
Other values (35)
 
106

Length

Max length21
Median length4
Mean length4.2708268
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> 2861
89.3%
최고고도지구 100
 
3.1%
최저고도지구 72
 
2.2%
방화지구 44
 
1.4%
아파트지구 22
 
0.7%
중심지미관지구 14
 
0.4%
주거환경개선지구 11
 
0.3%
항만시설보호지구 10
 
0.3%
방화지구,중심지미관지구 7
 
0.2%
주거환경개선사업지구 7
 
0.2%
Other values (30) 57
 
1.8%

Length

2024-04-17T20:07:48.037253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2861
89.0%
최고고도지구 100
 
3.1%
최저고도지구 72
 
2.2%
방화지구 50
 
1.6%
아파트지구 22
 
0.7%
중심지미관지구 14
 
0.4%
주거환경개선지구 11
 
0.3%
항만시설보호지구 10
 
0.3%
제1종지구단위계획구역 8
 
0.2%
온천지구 7
 
0.2%
Other values (26) 60
 
1.9%

plan_const
Text

MISSING 

Distinct129
Distinct (%)40.4%
Missing2886
Missing (%)90.0%
Memory size25.2 KiB
2024-04-17T20:07:48.226225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length8.0188088
Min length2

Characters and Unicode

Total characters2558
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

Unique76 ?
Unique (%)23.8%

Sample

1st row도로저촉
2nd row대로2류(폭 30M~35M)(접함),도시철도(저촉)
3rd row기타유원지시설
4th row기타유원지시설
5th row광로3류,중로2류저촉
ValueCountFrequency (%)
도로(접함 15
 
4.6%
광로2류접함 13
 
4.0%
소로3류접함 12
 
3.6%
도로(계획도로 11
 
3.3%
대로3류접함 11
 
3.3%
도로(저촉 11
 
3.3%
경관녹지 10
 
3.0%
도로(계획도로,접함 10
 
3.0%
광로3류접함 9
 
2.7%
소로2류접함 8
 
2.4%
Other values (115) 219
66.6%
2024-04-17T20:07:48.518486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 361
14.1%
류 205
 
8.0%
도 189
 
7.4%
접 181
 
7.1%
함 179
 
7.0%
, 139
 
5.4%
( 112
 
4.4%
) 112
 
4.4%
3 103
 
4.0%
저 80
 
3.1%
Other values (65) 897
35.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1945
76.0%
Decimal Number 229
 
9.0%
Other Punctuation 140
 
5.5%
Open Punctuation 112
 
4.4%
Close Punctuation 112
 
4.4%
Space Separator 10
 
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 361
18.6%
류 205
10.5%
도 189
 
9.7%
접 181
 
9.3%
함 179
 
9.2%
저 80
 
4.1%
촉 80
 
4.1%
중 77
 
4.0%
소 66
 
3.4%
광 50
 
2.6%
Other values (50) 477
24.5%
Decimal Number
ValueCountFrequency (%)
3 103
45.0%
2 76
33.2%
1 36
 
15.7%
4 6
 
2.6%
9 6
 
2.6%
5 1
 
0.4%
0 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 139
99.3%
. 1
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 112
100.0%
Close Punctuation
ValueCountFrequency (%)
) 112
100.0%
Space Separator
ValueCountFrequency (%)
10
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 1945
76.0%
Common 611
 
23.9%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 361
18.6%
류 205
10.5%
도 189
 
9.7%
접 181
 
9.3%
함 179
 
9.2%
저 80
 
4.1%
촉 80
 
4.1%
중 77
 
4.0%
소 66
 
3.4%
광 50
 
2.6%
Other values (50) 477
24.5%
Common
ValueCountFrequency (%)
, 139
22.7%
( 112
18.3%
) 112
18.3%
3 103
16.9%
2 76
12.4%
1 36
 
5.9%
10
 
1.6%
- 7
 
1.1%
4 6
 
1.0%
9 6
 
1.0%
Other values (4) 4
 
0.7%
Latin
ValueCountFrequency (%)
M 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1945
76.0%
ASCII 613
 
24.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 361
18.6%
류 205
10.5%
도 189
 
9.7%
접 181
 
9.3%
함 179
 
9.2%
저 80
 
4.1%
촉 80
 
4.1%
중 77
 
4.0%
소 66
 
3.4%
광 50
 
2.6%
Other values (50) 477
24.5%
ASCII
ValueCountFrequency (%)
, 139
22.7%
( 112
18.3%
) 112
18.3%
3 103
16.8%
2 76
12.4%
1 36
 
5.9%
10
 
1.6%
- 7
 
1.1%
4 6
 
1.0%
9 6
 
1.0%
Other values (5) 6
 
1.0%

last_load_dttm
Date

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
Minimum2020-12-22 14:22:59
Maximum2020-12-22 14:23:00
2024-04-17T20:07:48.616973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:07:48.699165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

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 도시계획실 도시균형재생국 도시정비과대부산광역시 남구 대연동 1865<NA><NA><NA>29985일반재산N1092부산광역시 창조도시국 도시정비과10923641897/100000000도시및주거환경정비기금<NA><NA>미등록<NA>2080000매입20151202<NA><NA><NA>2020-12-22 14:22:59
1미대부부산광역시 기획조정실 재정관 회계재산담당관대부산광역시 서구 암남동 81-129<NA><NA><NA>5일반재산N5<NA>51/1일반회계<NA><NA>미등록<NA>533500분할취득20160120제2종일반주거지역<NA><NA>2020-12-22 14:22:59
2미대부부산광역시 환경정책실 산림생태과임야부산광역시 해운대구 재송동 산 74-76<NA><NA>부산광역시 해운대구 미래도시국 늘푸른과24행정재산N24<NA>121/1일반회계<NA><NA>공공용재산<NA>346500분할취득20150924제2종일반주거지역<NA><NA>2020-12-22 14:22:59
3미대부부산광역시 기획조정실 재정관 회계재산담당관전부산광역시 기장군 기장읍 내리 701-106<NA><NA><NA>253일반재산N253<NA>2531/1일반회계<NA><NA>미등록<NA>101900분할취득20150529개발제한구역<NA><NA>2020-12-22 14:22:59
4미대부부산광역시 기획조정실 재정관 회계재산담당관하천부산광역시 기장군 철마면 웅천리 879-66<NA><NA><NA>316일반재산N316<NA>3161/1일반회계<NA><NA>미등록<NA>38600분할취득20150408개발제한구역<NA><NA>2020-12-22 14:22:59
5미대부부산광역시 기획조정실 재정관 회계재산담당관임야부산광역시 기장군 장안읍 기룡리 산 76-9<NA><NA><NA>1697일반재산N1697<NA>16971/1일반회계<NA><NA>미등록<NA>21100누락재산등록20131231자연녹지소하천구역도로저촉2020-12-22 14:22:59
6대부중부산광역시 기획조정실 재정관 회계재산담당관임야부산광역시 사하구 다대동 1432-21<NA>20180301~20230228,20180301~20230228<NA>40일반재산N40<NA>401/1일반회계<NA><NA>미등록<NA>369400분할취득20160511제2종일반주거지역,제3종일반주거지역상대정화구역, 절대정화구역대로2류(폭 30M~35M)(접함),도시철도(저촉)2020-12-22 14:22:59
7미대부부산광역시 환경정책실 물정책국 하천관리과답부산광역시 기장군 장안읍 임랑리 339-6<NA><NA><NA>322행정재산N322<NA>3221/1일반회계<NA><NA>공공용재산<NA>143200분할취득20140224자연녹지지역<NA><NA>2020-12-22 14:22:59
8미대부부산광역시 도시계획실 도로계획과답부산광역시 기장군 장안읍 임랑리 341-15<NA><NA>부산광역시 기장군 안전도시국 도시기반조성과243행정재산N243<NA>2431/1일반회계<NA><NA>공공용재산<NA>154100분할취득20140224자연녹지지역<NA><NA>2020-12-22 14:22:59
9미대부부산광역시 환경정책실 물정책국 하천관리과답부산광역시 기장군 장안읍 임랑리 346-5<NA><NA><NA>11행정재산N11<NA>111/1일반회계<NA><NA>공공용재산<NA>55100분할취득20120305자연녹지지역<NA><NA>2020-12-22 14:22:59
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
3195미대부부산광역시 기획조정실 재정관 회계재산담당관대부산광역시 동구 초량동 1064-199<NA><NA><NA>40일반재산N40<NA>401/1일반회계<NA><NA>미등록<NA>822000매입19750806일반주거지역<NA><NA>2020-12-22 14:23:00
3196미대부부산광역시 기획조정실 재정관 회계재산담당관대부산광역시 동구 초량동 1064-208<NA><NA><NA>127일반재산N127<NA>1271/1일반회계<NA><NA>미등록<NA>757300매입19570912일반주거지역<NA><NA>2020-12-22 14:23:00
3197미대부부산광역시 기획조정실 재정관 회계재산담당관대부산광역시 동구 초량동 1064-210<NA><NA><NA>4일반재산N4<NA>41/1일반회계<NA><NA>미등록<NA>757300매입19570912일반주거지역<NA><NA>2020-12-22 14:23:00
3198미대부부산광역시 기획조정실 재정관 회계재산담당관대부산광역시 동구 초량동 1127-1<NA><NA><NA>19일반재산N19<NA>191/1일반회계<NA><NA>미등록<NA>420700매입19821209일반주거지역<NA><NA>2020-12-22 14:23:00
3199미대부부산광역시 기획조정실 재정관 회계재산담당관대부산광역시 동구 초량동 1127-2<NA><NA><NA>23일반재산N23<NA>231/1일반회계<NA><NA>미등록<NA>473200매입19821209일반주거지역<NA><NA>2020-12-22 14:23:00
3200미대부부산광역시 기획조정실 재정관 회계재산담당관잡종지부산광역시 기장군 장안읍 좌천리 510-257<NA><NA><NA>15일반재산N15<NA>121/1일반회계<NA><NA>미등록<NA>528000분할취득20150106자연녹지지역<NA><NA>2020-12-22 14:23:00
3201미대부부산광역시 도시계획실 도로계획과대부산광역시 기장군 장안읍 좌천리 510-263<NA><NA><NA>7행정재산N7<NA>81/1일반회계<NA><NA>공공용재산<NA>491900분할취득20150106자연녹지지역<NA><NA>2020-12-22 14:23:00
3202미대부부산광역시 기획조정실 재정관 회계재산담당관하천부산광역시 기장군 철마면 웅천리 879-65<NA><NA><NA>42일반재산N42<NA>421/1일반회계<NA><NA>미등록<NA>58000분할취득20150408개발제한구역<NA><NA>2020-12-22 14:23:00
3203미대부부산광역시 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)2020-12-22 14:23:00
3204미대부부산광역시 기획조정실 재정관 회계재산담당관잡종지부산광역시 기장군 장안읍 좌천리 510-258<NA><NA><NA>17일반재산N17<NA>61/1일반회계<NA><NA>미등록<NA>534300분할취득20150106자연녹지지역<NA><NA>2020-12-22 14:23:00