Overview

Dataset statistics

Number of variables22
Number of observations519
Missing cells1282
Missing cells (%)11.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory89.3 KiB
Average record size in memory176.3 B

Variable types

Text13
Categorical7
DateTime2

Alerts

last_load_dttm has constant value ""Constant
road_addr is highly imbalanced (93.8%)Imbalance
main_agent is highly imbalanced (75.5%)Imbalance
apr_at is highly imbalanced (80.1%)Imbalance
cult_herit_nm has 11 (2.1%) missing valuesMissing
addr has 34 (6.6%) missing valuesMissing
organ_manage has 16 (3.1%) missing valuesMissing
number has 13 (2.5%) missing valuesMissing
dates has 9 (1.7%) missing valuesMissing
era has 78 (15.0%) missing valuesMissing
kind has 13 (2.5%) missing valuesMissing
installed_year has 303 (58.4%) missing valuesMissing
major_contents has 264 (50.9%) missing valuesMissing
area has 421 (81.1%) missing valuesMissing
data_day has 27 (5.2%) missing valuesMissing
lat has 33 (6.4%) missing valuesMissing
lng has 33 (6.4%) missing valuesMissing
last_load_dttm has 27 (5.2%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 22:16:39.767162
Analysis finished2024-04-16 22:16:40.774939
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Text

UNIQUE 

Distinct519
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2024-04-17T07:16:40.934362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length119
Median length4
Mean length5.6358382
Min length3

Characters and Unicode

Total characters2925
Distinct characters232
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique519 ?
Unique (%)100.0%

Sample

1st row3159
2nd row3160
3rd row3161
4th row3162
5th row3163
ValueCountFrequency (%)
그 4
 
0.6%
석재장식 2
 
0.3%
위에 2
 
0.3%
함께 2
 
0.3%
이 2
 
0.3%
건물은 2
 
0.3%
매우 2
 
0.3%
있다 2
 
0.3%
해 2
 
0.3%
일반적인 2
 
0.3%
Other values (677) 680
96.9%
2024-04-17T07:16:41.261544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 697
23.8%
1 212
 
7.2%
5 202
 
6.9%
191
 
6.5%
4 187
 
6.4%
2 163
 
5.6%
0 133
 
4.5%
6 123
 
4.2%
9 118
 
4.0%
8 112
 
3.8%
Other values (222) 787
26.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2050
70.1%
Other Letter 653
 
22.3%
Space Separator 191
 
6.5%
Other Punctuation 16
 
0.5%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%
Final Punctuation 3
 
0.1%
Initial Punctuation 3
 
0.1%
Math Symbol 2
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 19
 
2.9%
이 17
 
2.6%
로 16
 
2.5%
의 14
 
2.1%
하 14
 
2.1%
산 13
 
2.0%
에 13
 
2.0%
는 13
 
2.0%
대 12
 
1.8%
다 10
 
1.5%
Other values (202) 512
78.4%
Decimal Number
ValueCountFrequency (%)
3 697
34.0%
1 212
 
10.3%
5 202
 
9.9%
4 187
 
9.1%
2 163
 
8.0%
0 133
 
6.5%
6 123
 
6.0%
9 118
 
5.8%
8 112
 
5.5%
7 103
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 12
75.0%
, 4
 
25.0%
Math Symbol
ValueCountFrequency (%)
～ 1
50.0%
~ 1
50.0%
Space Separator
ValueCountFrequency (%)
191
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 3
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2271
77.6%
Hangul 652
 
22.3%
Han 1
 
< 0.1%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 19
 
2.9%
이 17
 
2.6%
로 16
 
2.5%
의 14
 
2.1%
하 14
 
2.1%
산 13
 
2.0%
에 13
 
2.0%
는 13
 
2.0%
대 12
 
1.8%
다 10
 
1.5%
Other values (201) 511
78.4%
Common
ValueCountFrequency (%)
3 697
30.7%
1 212
 
9.3%
5 202
 
8.9%
191
 
8.4%
4 187
 
8.2%
2 163
 
7.2%
0 133
 
5.9%
6 123
 
5.4%
9 118
 
5.2%
8 112
 
4.9%
Other values (9) 133
 
5.9%
Han
ValueCountFrequency (%)
池 1
100.0%
Latin
ValueCountFrequency (%)
m 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2265
77.4%
Hangul 652
 
22.3%
Punctuation 6
 
0.2%
CJK 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 697
30.8%
1 212
 
9.4%
5 202
 
8.9%
191
 
8.4%
4 187
 
8.3%
2 163
 
7.2%
0 133
 
5.9%
6 123
 
5.4%
9 118
 
5.2%
8 112
 
4.9%
Other values (7) 127
 
5.6%
Hangul
ValueCountFrequency (%)
부 19
 
2.9%
이 17
 
2.6%
로 16
 
2.5%
의 14
 
2.1%
하 14
 
2.1%
산 13
 
2.0%
에 13
 
2.0%
는 13
 
2.0%
대 12
 
1.8%
다 10
 
1.5%
Other values (201) 511
78.4%
Punctuation
ValueCountFrequency (%)
’ 3
50.0%
‘ 3
50.0%
CJK
ValueCountFrequency (%)
池 1
100.0%
None
ValueCountFrequency (%)
～ 1
100.0%

instt_code
Categorical

Distinct22
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
3350000
122 
3260000
73 
3400000
64 
3310000
54 
3300000
41 
Other values (17)
165 

Length

Max length43
Median length7
Mean length7.3815029
Min length4

Unique

Unique4 ?
Unique (%)0.8%

Sample

1st row3350000
2nd row3350000
3rd row3350000
4th row3350000
5th row3350000

Common Values

ValueCountFrequency (%)
3350000 122
23.5%
3260000 73
14.1%
3400000 64
12.3%
3310000 54
10.4%
3300000 41
 
7.9%
3280000 22
 
4.2%
3290000 20
 
3.9%
3330000 19
 
3.7%
3380000 18
 
3.5%
3270000 16
 
3.1%
Other values (12) 70
13.5%

Length

2024-04-17T07:16:41.371796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3350000 122
23.5%
3260000 73
14.1%
3400000 64
12.3%
3310000 54
10.4%
3300000 41
 
7.9%
3280000 22
 
4.2%
3290000 20
 
3.9%
3330000 19
 
3.7%
3380000 18
 
3.5%
3270000 16
 
3.1%
Other values (12) 70
13.5%

cult_herit_nm
Text

MISSING 

Distinct502
Distinct (%)98.8%
Missing11
Missing (%)2.1%
Memory size4.2 KiB
2024-04-17T07:16:41.572796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length24
Mean length10.26378
Min length2

Characters and Unicode

Total characters5214
Distinct characters604
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique496 ?
Unique (%)97.6%

Sample

1st row훈몽자회 책판
2nd row범어사 극락암 칠성도
3rd row승자총통
4th row범어사 원효암 목조관음보살좌상 복장유물 일괄
5th row삼층석탑
ValueCountFrequency (%)
범어사 79
 
7.3%
부산 24
 
2.2%
및 15
 
1.4%
장안사 14
 
1.3%
기장 13
 
1.2%
묘법연화경 13
 
1.2%
대웅전 10
 
0.9%
영산회상도 9
 
0.8%
응진전 9
 
0.8%
필 7
 
0.6%
Other values (680) 885
82.1%
2024-04-17T07:16:41.899343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
574
 
11.0%
사 244
 
4.7%
도 104
 
2.0%
상 98
 
1.9%
어 92
 
1.8%
범 89
 
1.7%
동 79
 
1.5%
산 78
 
1.5%
조 77
 
1.5%
) 73
 
1.4%
Other values (594) 3706
71.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4385
84.1%
Space Separator 574
 
11.0%
Close Punctuation 73
 
1.4%
Open Punctuation 73
 
1.4%
Decimal Number 72
 
1.4%
Other Punctuation 17
 
0.3%
Math Symbol 6
 
0.1%
Dash Punctuation 6
 
0.1%
Other Symbol 5
 
0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 244
 
5.6%
도 104
 
2.4%
상 98
 
2.2%
어 92
 
2.1%
범 89
 
2.0%
동 79
 
1.8%
산 78
 
1.8%
조 77
 
1.8%
장 72
 
1.6%
부 64
 
1.5%
Other values (571) 3388
77.3%
Decimal Number
ValueCountFrequency (%)
1 16
22.2%
2 13
18.1%
4 12
16.7%
7 7
9.7%
3 6
 
8.3%
5 5
 
6.9%
0 4
 
5.6%
6 4
 
5.6%
8 3
 
4.2%
9 2
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 9
52.9%
. 6
35.3%
· 1
 
5.9%
? 1
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
U 1
50.0%
N 1
50.0%
Space Separator
ValueCountFrequency (%)
574
100.0%
Close Punctuation
ValueCountFrequency (%)
) 73
100.0%
Open Punctuation
ValueCountFrequency (%)
( 73
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3935
75.5%
Common 826
 
15.8%
Han 450
 
8.6%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 244
 
6.2%
도 104
 
2.6%
상 98
 
2.5%
어 92
 
2.3%
범 89
 
2.3%
동 79
 
2.0%
산 78
 
2.0%
조 77
 
2.0%
장 72
 
1.8%
부 64
 
1.6%
Other values (328) 2938
74.7%
Han
ValueCountFrequency (%)
圖 16
 
3.6%
像 12
 
2.7%
坐 8
 
1.8%
山 8
 
1.8%
碑 7
 
1.6%
括 7
 
1.6%
造 7
 
1.6%
一 7
 
1.6%
壺 6
 
1.3%
石 6
 
1.3%
Other values (233) 366
81.3%
Common
ValueCountFrequency (%)
574
69.5%
) 73
 
8.8%
( 73
 
8.8%
1 16
 
1.9%
2 13
 
1.6%
4 12
 
1.5%
, 9
 
1.1%
7 7
 
0.8%
~ 6
 
0.7%
. 6
 
0.7%
Other values (10) 37
 
4.5%
Latin
ValueCountFrequency (%)
m 1
33.3%
U 1
33.3%
N 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3935
75.5%
ASCII 823
 
15.8%
CJK 433
 
8.3%
CJK Compat Ideographs 17
 
0.3%
CJK Compat 5
 
0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
574
69.7%
) 73
 
8.9%
( 73
 
8.9%
1 16
 
1.9%
2 13
 
1.6%
4 12
 
1.5%
, 9
 
1.1%
7 7
 
0.9%
~ 6
 
0.7%
. 6
 
0.7%
Other values (11) 34
 
4.1%
Hangul
ValueCountFrequency (%)
사 244
 
6.2%
도 104
 
2.6%
상 98
 
2.5%
어 92
 
2.3%
범 89
 
2.3%
동 79
 
2.0%
산 78
 
2.0%
조 77
 
2.0%
장 72
 
1.8%
부 64
 
1.6%
Other values (328) 2938
74.7%
CJK
ValueCountFrequency (%)
圖 16
 
3.7%
像 12
 
2.8%
坐 8
 
1.8%
山 8
 
1.8%
碑 7
 
1.6%
括 7
 
1.6%
造 7
 
1.6%
一 7
 
1.6%
壺 6
 
1.4%
石 6
 
1.4%
Other values (223) 349
80.6%
CJK Compat Ideographs
ValueCountFrequency (%)
金 5
29.4%
李 3
17.6%
柳 2
 
11.8%
蠟 1
 
5.9%
立 1
 
5.9%
列 1
 
5.9%
龍 1
 
5.9%
沈 1
 
5.9%
琉 1
 
5.9%
禮 1
 
5.9%
CJK Compat
ValueCountFrequency (%)
㎡ 5
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

road_addr
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
513 
051-600-4066
 
5
2020-07-31
 
1

Length

Max length12
Median length4
Mean length4.088632
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 513
98.8%
051-600-4066 5
 
1.0%
2020-07-31 1
 
0.2%

Length

2024-04-17T07:16:42.015026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:16:42.093621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 513
98.8%
051-600-4066 5
 
1.0%
2020-07-31 1
 
0.2%

addr
Text

MISSING 

Distinct174
Distinct (%)35.9%
Missing34
Missing (%)6.6%
Memory size4.2 KiB
2024-04-17T07:16:42.282900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length33
Mean length20.084536
Min length7

Characters and Unicode

Total characters9741
Distinct characters170
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

Unique120 ?
Unique (%)24.7%

Sample

1st row부산시 금정구 부산대학로 63번길 2 부산대학교박물관
2nd row부산시 금정구 범어사로 250 금정산 범어사
3rd row부산시 금정구 부산대학로 63번길 2 부산대학교박물관
4th row부산시 금정구 범어사로 250 금정산 범어사
5th row부산시 금정구 상현로 79번길 59-15
ValueCountFrequency (%)
부산광역시 289
 
13.2%
부산시 133
 
6.1%
금정구 124
 
5.6%
범어사로 89
 
4.1%
범어사 87
 
4.0%
250 84
 
3.8%
금정산 82
 
3.7%
서구 73
 
3.3%
부민동2가 56
 
2.6%
1 56
 
2.6%
Other values (343) 1123
51.1%
2024-04-17T07:16:42.598959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1716
 
17.6%
산 613
 
6.3%
부 550
 
5.6%
시 430
 
4.4%
구 429
 
4.4%
동 338
 
3.5%
1 301
 
3.1%
광 300
 
3.1%
역 290
 
3.0%
2 265
 
2.7%
Other values (160) 4509
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6205
63.7%
Space Separator 1716
 
17.6%
Decimal Number 1522
 
15.6%
Dash Punctuation 139
 
1.4%
Close Punctuation 64
 
0.7%
Open Punctuation 64
 
0.7%
Other Punctuation 31
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 613
 
9.9%
부 550
 
8.9%
시 430
 
6.9%
구 429
 
6.9%
동 338
 
5.4%
광 300
 
4.8%
역 290
 
4.7%
금 223
 
3.6%
정 222
 
3.6%
사 210
 
3.4%
Other values (144) 2600
41.9%
Decimal Number
ValueCountFrequency (%)
1 301
19.8%
2 265
17.4%
5 173
11.4%
3 146
9.6%
0 136
8.9%
4 133
8.7%
9 104
 
6.8%
6 104
 
6.8%
8 97
 
6.4%
7 63
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 30
96.8%
. 1
 
3.2%
Space Separator
ValueCountFrequency (%)
1716
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 139
100.0%
Close Punctuation
ValueCountFrequency (%)
) 64
100.0%
Open Punctuation
ValueCountFrequency (%)
( 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6205
63.7%
Common 3536
36.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 613
 
9.9%
부 550
 
8.9%
시 430
 
6.9%
구 429
 
6.9%
동 338
 
5.4%
광 300
 
4.8%
역 290
 
4.7%
금 223
 
3.6%
정 222
 
3.6%
사 210
 
3.4%
Other values (144) 2600
41.9%
Common
ValueCountFrequency (%)
1716
48.5%
1 301
 
8.5%
2 265
 
7.5%
5 173
 
4.9%
3 146
 
4.1%
- 139
 
3.9%
0 136
 
3.8%
4 133
 
3.8%
9 104
 
2.9%
6 104
 
2.9%
Other values (6) 319
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6205
63.7%
ASCII 3536
36.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1716
48.5%
1 301
 
8.5%
2 265
 
7.5%
5 173
 
4.9%
3 146
 
4.1%
- 139
 
3.9%
0 136
 
3.8%
4 133
 
3.8%
9 104
 
2.9%
6 104
 
2.9%
Other values (6) 319
 
9.0%
Hangul
ValueCountFrequency (%)
산 613
 
9.9%
부 550
 
8.9%
시 430
 
6.9%
구 429
 
6.9%
동 338
 
5.4%
광 300
 
4.8%
역 290
 
4.7%
금 223
 
3.6%
정 222
 
3.6%
사 210
 
3.4%
Other values (144) 2600
41.9%

organ_manage
Text

MISSING 

Distinct129
Distinct (%)25.6%
Missing16
Missing (%)3.1%
Memory size4.2 KiB
2024-04-17T07:16:42.768172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length5.1908549
Min length2

Characters and Unicode

Total characters2611
Distinct characters180
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)14.1%

Sample

1st row부산대학교
2nd row범어사
3rd row부산대학교
4th row범어사
5th row금정구청
ValueCountFrequency (%)
범어사 87
 
15.6%
동아대학교 56
 
10.0%
부산박물관 45
 
8.1%
부산광역시 28
 
5.0%
부산대학교 18
 
3.2%
동래구청장 17
 
3.0%
장안사 15
 
2.7%
수영구청 11
 
2.0%
기장군 9
 
1.6%
강서구청 9
 
1.6%
Other values (128) 264
47.2%
2024-04-17T07:16:43.033364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 239
 
9.2%
산 140
 
5.4%
부 135
 
5.2%
관 90
 
3.4%
범 87
 
3.3%
어 87
 
3.3%
교 86
 
3.3%
대 85
 
3.3%
동 83
 
3.2%
학 80
 
3.1%
Other values (170) 1499
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2438
93.4%
Space Separator 57
 
2.2%
Decimal Number 55
 
2.1%
Close Punctuation 22
 
0.8%
Open Punctuation 22
 
0.8%
Dash Punctuation 10
 
0.4%
Other Punctuation 5
 
0.2%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 239
 
9.8%
산 140
 
5.7%
부 135
 
5.5%
관 90
 
3.7%
범 87
 
3.6%
어 87
 
3.6%
교 86
 
3.5%
대 85
 
3.5%
동 83
 
3.4%
학 80
 
3.3%
Other values (155) 1326
54.4%
Decimal Number
ValueCountFrequency (%)
0 22
40.0%
2 13
23.6%
3 7
 
12.7%
1 6
 
10.9%
7 5
 
9.1%
9 1
 
1.8%
8 1
 
1.8%
Other Punctuation
ValueCountFrequency (%)
* 2
40.0%
, 2
40.0%
. 1
20.0%
Space Separator
ValueCountFrequency (%)
57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Uppercase Letter
ValueCountFrequency (%)
O 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2438
93.4%
Common 171
 
6.5%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 239
 
9.8%
산 140
 
5.7%
부 135
 
5.5%
관 90
 
3.7%
범 87
 
3.6%
어 87
 
3.6%
교 86
 
3.5%
대 85
 
3.5%
동 83
 
3.4%
학 80
 
3.3%
Other values (155) 1326
54.4%
Common
ValueCountFrequency (%)
57
33.3%
0 22
 
12.9%
) 22
 
12.9%
( 22
 
12.9%
2 13
 
7.6%
- 10
 
5.8%
3 7
 
4.1%
1 6
 
3.5%
7 5
 
2.9%
* 2
 
1.2%
Other values (4) 5
 
2.9%
Latin
ValueCountFrequency (%)
O 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2438
93.4%
ASCII 173
 
6.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 239
 
9.8%
산 140
 
5.7%
부 135
 
5.5%
관 90
 
3.7%
범 87
 
3.6%
어 87
 
3.6%
교 86
 
3.5%
대 85
 
3.5%
동 83
 
3.4%
학 80
 
3.3%
Other values (155) 1326
54.4%
ASCII
ValueCountFrequency (%)
57
32.9%
0 22
 
12.7%
) 22
 
12.7%
( 22
 
12.7%
2 13
 
7.5%
- 10
 
5.8%
3 7
 
4.0%
1 6
 
3.5%
7 5
 
2.9%
* 2
 
1.2%
Other values (5) 7
 
4.0%

number
Text

MISSING 

Distinct327
Distinct (%)64.6%
Missing13
Missing (%)2.5%
Memory size4.2 KiB
2024-04-17T07:16:43.357733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.4466403
Min length3

Characters and Unicode

Total characters2756
Distinct characters50
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique230 ?
Unique (%)45.5%

Sample

1st row제166호
2nd row제167호
3rd row제168호
4th row제173호
5th row제175호
ValueCountFrequency (%)
시지정 26
 
4.5%
유형문화재 15
 
2.6%
부산시 15
 
2.6%
문화재자료 15
 
2.6%
市지정 13
 
2.2%
부산광역시지정기념물 7
 
1.2%
제18호 6
 
1.0%
제9호 5
 
0.9%
보물 5
 
0.9%
제17호 5
 
0.9%
Other values (309) 468
80.7%
2024-04-17T07:16:43.798431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 445
16.1%
호 438
15.9%
1 264
 
9.6%
2 125
 
4.5%
118
 
4.3%
5 107
 
3.9%
4 103
 
3.7%
3 101
 
3.7%
9 96
 
3.5%
7 91
 
3.3%
Other values (40) 868
31.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1477
53.6%
Decimal Number 1131
41.0%
Space Separator 118
 
4.3%
Dash Punctuation 21
 
0.8%
Other Punctuation 5
 
0.2%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 445
30.1%
호 438
29.7%
정 66
 
4.5%
지 64
 
4.3%
시 60
 
4.1%
문 47
 
3.2%
재 43
 
2.9%
화 43
 
2.9%
산 29
 
2.0%
부 29
 
2.0%
Other values (25) 213
14.4%
Decimal Number
ValueCountFrequency (%)
1 264
23.3%
2 125
11.1%
5 107
9.5%
4 103
 
9.1%
3 101
 
8.9%
9 96
 
8.5%
7 91
 
8.0%
6 91
 
8.0%
8 83
 
7.3%
0 70
 
6.2%
Space Separator
ValueCountFrequency (%)
118
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1464
53.1%
Common 1279
46.4%
Han 13
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 445
30.4%
호 438
29.9%
정 66
 
4.5%
지 64
 
4.4%
시 60
 
4.1%
문 47
 
3.2%
재 43
 
2.9%
화 43
 
2.9%
산 29
 
2.0%
부 29
 
2.0%
Other values (24) 200
13.7%
Common
ValueCountFrequency (%)
1 264
20.6%
2 125
9.8%
118
9.2%
5 107
8.4%
4 103
 
8.1%
3 101
 
7.9%
9 96
 
7.5%
7 91
 
7.1%
6 91
 
7.1%
8 83
 
6.5%
Other values (5) 100
 
7.8%
Han
ValueCountFrequency (%)
市 13
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1464
53.1%
ASCII 1279
46.4%
CJK 13
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 445
30.4%
호 438
29.9%
정 66
 
4.5%
지 64
 
4.4%
시 60
 
4.1%
문 47
 
3.2%
재 43
 
2.9%
화 43
 
2.9%
산 29
 
2.0%
부 29
 
2.0%
Other values (24) 200
13.7%
ASCII
ValueCountFrequency (%)
1 264
20.6%
2 125
9.8%
118
9.2%
5 107
8.4%
4 103
 
8.1%
3 101
 
7.9%
9 96
 
7.5%
7 91
 
7.1%
6 91
 
7.1%
8 83
 
6.5%
Other values (5) 100
 
7.8%
CJK
ValueCountFrequency (%)
市 13
100.0%

dates
Text

MISSING 

Distinct183
Distinct (%)35.9%
Missing9
Missing (%)1.7%
Memory size4.2 KiB
2024-04-17T07:16:44.020206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length10
Mean length10.029412
Min length8

Characters and Unicode

Total characters5115
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)20.2%

Sample

1st row2015-09-16
2nd row2016-01-20
3rd row2016-03-16
4th row2016-09-21
5th row2016-09-21
ValueCountFrequency (%)
1972-06-26 39
 
7.5%
2003-09-16 23
 
4.4%
2012-10-30 13
 
2.5%
2006-11-25 12
 
2.3%
2012-05-17 12
 
2.3%
2007-09-07 11
 
2.1%
1999-09-03 11
 
2.1%
2013-05-08 11
 
2.1%
1999-11-19 10
 
1.9%
2008-04-02 10
 
1.9%
Other values (179) 367
70.7%
2024-04-17T07:16:44.336610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1122
21.9%
- 1002
19.6%
1 798
15.6%
2 758
14.8%
9 368
 
7.2%
6 224
 
4.4%
3 217
 
4.2%
5 183
 
3.6%
7 181
 
3.5%
8 127
 
2.5%
Other values (4) 135
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4084
79.8%
Dash Punctuation 1002
 
19.6%
Other Punctuation 15
 
0.3%
Space Separator 14
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1122
27.5%
1 798
19.5%
2 758
18.6%
9 368
 
9.0%
6 224
 
5.5%
3 217
 
5.3%
5 183
 
4.5%
7 181
 
4.4%
8 127
 
3.1%
4 106
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 13
86.7%
: 2
 
13.3%
Dash Punctuation
ValueCountFrequency (%)
- 1002
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5115
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1122
21.9%
- 1002
19.6%
1 798
15.6%
2 758
14.8%
9 368
 
7.2%
6 224
 
4.4%
3 217
 
4.2%
5 183
 
3.6%
7 181
 
3.5%
8 127
 
2.5%
Other values (4) 135
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5115
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1122
21.9%
- 1002
19.6%
1 798
15.6%
2 758
14.8%
9 368
 
7.2%
6 224
 
4.4%
3 217
 
4.2%
5 183
 
3.6%
7 181
 
3.5%
8 127
 
2.5%
Other values (4) 135
 
2.6%

era
Text

MISSING 

Distinct179
Distinct (%)40.6%
Missing78
Missing (%)15.0%
Memory size4.2 KiB
2024-04-17T07:16:44.594484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length4.3582766
Min length1

Characters and Unicode

Total characters1922
Distinct characters63
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique127 ?
Unique (%)28.8%

Sample

1st row조선후기
2nd row1861년
3rd row1583년
4th row조선후기
5th row통일신라
ValueCountFrequency (%)
조선시대 81
 
17.5%
조선후기 43
 
9.3%
18세기 13
 
2.8%
고려시대 11
 
2.4%
11
 
2.4%
17세기 10
 
2.2%
삼국시대 9
 
1.9%
근대 8
 
1.7%
조선 8
 
1.7%
통일신라 8
 
1.7%
Other values (170) 260
56.3%
2024-04-17T07:16:44.947569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 228
 
11.9%
조 152
 
7.9%
선 152
 
7.9%
년 148
 
7.7%
기 127
 
6.6%
대 119
 
6.2%
시 108
 
5.6%
8 80
 
4.2%
9 75
 
3.9%
7 68
 
3.5%
Other values (53) 665
34.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1142
59.4%
Decimal Number 722
37.6%
Space Separator 23
 
1.2%
Dash Punctuation 12
 
0.6%
Math Symbol 12
 
0.6%
Uppercase Letter 5
 
0.3%
Open Punctuation 2
 
0.1%
Lowercase Letter 2
 
0.1%
Close Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
조 152
13.3%
선 152
13.3%
년 148
13.0%
기 127
11.1%
대 119
10.4%
시 108
9.5%
후 54
 
4.7%
세 43
 
3.8%
려 27
 
2.4%
고 27
 
2.4%
Other values (35) 185
16.2%
Decimal Number
ValueCountFrequency (%)
1 228
31.6%
8 80
 
11.1%
9 75
 
10.4%
7 68
 
9.4%
6 57
 
7.9%
5 56
 
7.8%
0 49
 
6.8%
2 49
 
6.8%
4 36
 
5.0%
3 24
 
3.3%
Space Separator
ValueCountFrequency (%)
23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1142
59.4%
Common 773
40.2%
Latin 7
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
조 152
13.3%
선 152
13.3%
년 148
13.0%
기 127
11.1%
대 119
10.4%
시 108
9.5%
후 54
 
4.7%
세 43
 
3.8%
려 27
 
2.4%
고 27
 
2.4%
Other values (35) 185
16.2%
Common
ValueCountFrequency (%)
1 228
29.5%
8 80
 
10.3%
9 75
 
9.7%
7 68
 
8.8%
6 57
 
7.4%
5 56
 
7.2%
0 49
 
6.3%
2 49
 
6.3%
4 36
 
4.7%
3 24
 
3.1%
Other values (6) 51
 
6.6%
Latin
ValueCountFrequency (%)
C 5
71.4%
c 2
 
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1142
59.4%
ASCII 780
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 228
29.2%
8 80
 
10.3%
9 75
 
9.6%
7 68
 
8.7%
6 57
 
7.3%
5 56
 
7.2%
0 49
 
6.3%
2 49
 
6.3%
4 36
 
4.6%
3 24
 
3.1%
Other values (8) 58
 
7.4%
Hangul
ValueCountFrequency (%)
조 152
13.3%
선 152
13.3%
년 148
13.0%
기 127
11.1%
대 119
10.4%
시 108
9.5%
후 54
 
4.7%
세 43
 
3.8%
려 27
 
2.4%
고 27
 
2.4%
Other values (35) 185
16.2%

kind
Text

MISSING 

Distinct56
Distinct (%)11.1%
Missing13
Missing (%)2.5%
Memory size4.2 KiB
2024-04-17T07:16:45.116590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length11
Mean length5.416996
Min length2

Characters and Unicode

Total characters2741
Distinct characters73
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

Unique22 ?
Unique (%)4.3%

Sample

1st row유형문화재
2nd row유형문화재
3rd row유형문화재
4th row유형문화재
5th row유형문화재
ValueCountFrequency (%)
유형문화재 166
28.1%
문화재자료 53
 
9.0%
보물 43
 
7.3%
시지정 40
 
6.8%
기념물 33
 
5.6%
시지정유형문화재 32
 
5.4%
문화재 23
 
3.9%
민속자료 21
 
3.6%
무형문화재 20
 
3.4%
등록문화재 17
 
2.9%
Other values (43) 143
24.2%
2024-04-17T07:16:45.421730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
화 356
13.0%
문 350
12.8%
재 350
12.8%
형 224
 
8.2%
유 200
 
7.3%
시 112
 
4.1%
지 101
 
3.7%
정 99
 
3.6%
물 96
 
3.5%
자 91
 
3.3%
Other values (63) 762
27.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2528
92.2%
Decimal Number 102
 
3.7%
Space Separator 85
 
3.1%
Dash Punctuation 16
 
0.6%
Other Punctuation 10
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 356
14.1%
문 350
13.8%
재 350
13.8%
형 224
8.9%
유 200
 
7.9%
시 112
 
4.4%
지 101
 
4.0%
정 99
 
3.9%
물 96
 
3.8%
자 91
 
3.6%
Other values (52) 549
21.7%
Decimal Number
ValueCountFrequency (%)
0 25
24.5%
1 24
23.5%
2 21
20.6%
5 15
14.7%
4 5
 
4.9%
7 4
 
3.9%
6 4
 
3.9%
3 4
 
3.9%
Space Separator
ValueCountFrequency (%)
85
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Other Punctuation
ValueCountFrequency (%)
: 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2528
92.2%
Common 213
 
7.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
화 356
14.1%
문 350
13.8%
재 350
13.8%
형 224
8.9%
유 200
 
7.9%
시 112
 
4.4%
지 101
 
4.0%
정 99
 
3.9%
물 96
 
3.8%
자 91
 
3.6%
Other values (52) 549
21.7%
Common
ValueCountFrequency (%)
85
39.9%
0 25
 
11.7%
1 24
 
11.3%
2 21
 
9.9%
- 16
 
7.5%
5 15
 
7.0%
: 10
 
4.7%
4 5
 
2.3%
7 4
 
1.9%
6 4
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2528
92.2%
ASCII 213
 
7.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
화 356
14.1%
문 350
13.8%
재 350
13.8%
형 224
8.9%
유 200
 
7.9%
시 112
 
4.4%
지 101
 
4.0%
정 99
 
3.9%
물 96
 
3.8%
자 91
 
3.6%
Other values (52) 549
21.7%
ASCII
ValueCountFrequency (%)
85
39.9%
0 25
 
11.7%
1 24
 
11.3%
2 21
 
9.9%
- 16
 
7.5%
5 15
 
7.0%
: 10
 
4.7%
4 5
 
2.3%
7 4
 
1.9%
6 4
 
1.9%

main_agent
Categorical

IMBALANCE 

Distinct20
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
444 
-
 
23
해당없음
 
17
미상
 
9
국가
 
4
Other values (15)
 
22

Length

Max length13
Median length4
Mean length3.8863198
Min length1

Unique

Unique12 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 444
85.5%
- 23
 
4.4%
해당없음 17
 
3.3%
미상 9
 
1.7%
국가 4
 
0.8%
사하구 4
 
0.8%
35.1037380240 3
 
0.6%
운수사 3
 
0.6%
강서구,사상구,사하구 1
 
0.2%
(자연환경) 1
 
0.2%
Other values (10) 10
 
1.9%

Length

2024-04-17T07:16:45.528769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 444
85.2%
23
 
4.4%
해당없음 18
 
3.5%
미상 9
 
1.7%
국가 4
 
0.8%
사하구 4
 
0.8%
35.1037380240 3
 
0.6%
운수사 3
 
0.6%
화암사 1
 
0.2%
박만정 1
 
0.2%
Other values (11) 11
 
2.1%

installed_year
Text

MISSING 

Distinct123
Distinct (%)56.9%
Missing303
Missing (%)58.4%
Memory size4.2 KiB
2024-04-17T07:16:45.754517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length4.6481481
Min length1

Characters and Unicode

Total characters1004
Distinct characters55
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)43.1%

Sample

1st row1861년
2nd row1583년
3rd row1650년
4th row1678년
5th row18C 후반
ValueCountFrequency (%)
22
 
9.6%
해당없음 11
 
4.8%
조선후기 10
 
4.3%
조선시대 9
 
3.9%
18세기 8
 
3.5%
조선초기 6
 
2.6%
1882년 4
 
1.7%
조선중기 4
 
1.7%
1892년 4
 
1.7%
1934년 3
 
1.3%
Other values (119) 149
64.8%
2024-04-17T07:16:46.101824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 165
16.4%
년 111
 
11.1%
9 65
 
6.5%
8 56
 
5.6%
0 48
 
4.8%
기 46
 
4.6%
6 44
 
4.4%
5 41
 
4.1%
2 41
 
4.1%
7 40
 
4.0%
Other values (45) 347
34.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 553
55.1%
Other Letter 389
38.7%
Dash Punctuation 23
 
2.3%
Space Separator 15
 
1.5%
Math Symbol 10
 
1.0%
Uppercase Letter 5
 
0.5%
Other Punctuation 4
 
0.4%
Lowercase Letter 2
 
0.2%
Open Punctuation 2
 
0.2%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
년 111
28.5%
기 46
11.8%
선 33
 
8.5%
조 33
 
8.5%
세 19
 
4.9%
후 16
 
4.1%
대 12
 
3.1%
음 11
 
2.8%
없 11
 
2.8%
당 11
 
2.8%
Other values (26) 86
22.1%
Decimal Number
ValueCountFrequency (%)
1 165
29.8%
9 65
 
11.8%
8 56
 
10.1%
0 48
 
8.7%
6 44
 
8.0%
5 41
 
7.4%
2 41
 
7.4%
7 40
 
7.2%
4 35
 
6.3%
3 18
 
3.3%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
/ 1
 
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 608
60.6%
Hangul 389
38.7%
Latin 7
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
년 111
28.5%
기 46
11.8%
선 33
 
8.5%
조 33
 
8.5%
세 19
 
4.9%
후 16
 
4.1%
대 12
 
3.1%
음 11
 
2.8%
없 11
 
2.8%
당 11
 
2.8%
Other values (26) 86
22.1%
Common
ValueCountFrequency (%)
1 165
27.1%
9 65
 
10.7%
8 56
 
9.2%
0 48
 
7.9%
6 44
 
7.2%
5 41
 
6.7%
2 41
 
6.7%
7 40
 
6.6%
4 35
 
5.8%
- 23
 
3.8%
Other values (7) 50
 
8.2%
Latin
ValueCountFrequency (%)
C 5
71.4%
c 2
 
28.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 615
61.3%
Hangul 389
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 165
26.8%
9 65
 
10.6%
8 56
 
9.1%
0 48
 
7.8%
6 44
 
7.2%
5 41
 
6.7%
2 41
 
6.7%
7 40
 
6.5%
4 35
 
5.7%
- 23
 
3.7%
Other values (9) 57
 
9.3%
Hangul
ValueCountFrequency (%)
년 111
28.5%
기 46
11.8%
선 33
 
8.5%
조 33
 
8.5%
세 19
 
4.9%
후 16
 
4.1%
대 12
 
3.1%
음 11
 
2.8%
없 11
 
2.8%
당 11
 
2.8%
Other values (26) 86
22.1%

major_contents
Text

MISSING 

Distinct178
Distinct (%)69.8%
Missing264
Missing (%)50.9%
Memory size4.2 KiB
2024-04-17T07:16:46.339750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length250
Median length97
Mean length26.960784
Min length1

Characters and Unicode

Total characters6875
Distinct characters621
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique162 ?
Unique (%)63.5%

Sample

1st row목판각류
2nd row불화
3rd row병기류
4th row복장류
5th row석탑
ValueCountFrequency (%)
도서 21
 
1.3%
19
 
1.2%
불화 15
 
0.9%
있는 15
 
0.9%
불교 11
 
0.7%
조선 11
 
0.7%
제작된 10
 
0.6%
목판각류 8
 
0.5%
그린 8
 
0.5%
것으로 7
 
0.4%
Other values (1232) 1487
92.2%
2024-04-17T07:16:46.702229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1382
 
20.1%
의 137
 
2.0%
에 101
 
1.5%
기 100
 
1.5%
이 100
 
1.5%
조 83
 
1.2%
로 71
 
1.0%
한 69
 
1.0%
을 69
 
1.0%
1 67
 
1.0%
Other values (611) 4696
68.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4939
71.8%
Space Separator 1382
 
20.1%
Decimal Number 270
 
3.9%
Other Punctuation 77
 
1.1%
Close Punctuation 66
 
1.0%
Open Punctuation 65
 
0.9%
Math Symbol 33
 
0.5%
Dash Punctuation 18
 
0.3%
Lowercase Letter 18
 
0.3%
Other Symbol 3
 
< 0.1%
Other values (2) 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 137
 
2.8%
에 101
 
2.0%
기 100
 
2.0%
이 100
 
2.0%
조 83
 
1.7%
로 71
 
1.4%
한 69
 
1.4%
을 69
 
1.4%
도 65
 
1.3%
지 64
 
1.3%
Other values (570) 4080
82.6%
Lowercase Letter
ValueCountFrequency (%)
m 3
16.7%
c 3
16.7%
b 2
11.1%
e 2
11.1%
a 1
 
5.6%
s 1
 
5.6%
u 1
 
5.6%
l 1
 
5.6%
r 1
 
5.6%
i 1
 
5.6%
Other values (2) 2
11.1%
Decimal Number
ValueCountFrequency (%)
1 67
24.8%
9 32
11.9%
2 28
10.4%
6 25
 
9.3%
0 24
 
8.9%
3 23
 
8.5%
7 22
 
8.1%
5 21
 
7.8%
8 15
 
5.6%
4 13
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 54
70.1%
. 18
 
23.4%
· 4
 
5.2%
? 1
 
1.3%
Math Symbol
ValueCountFrequency (%)
> 14
42.4%
< 14
42.4%
~ 4
 
12.1%
∼ 1
 
3.0%
Close Punctuation
ValueCountFrequency (%)
) 62
93.9%
』 2
 
3.0%
」 2
 
3.0%
Open Punctuation
ValueCountFrequency (%)
( 61
93.8%
『 2
 
3.1%
「 2
 
3.1%
Space Separator
ValueCountFrequency (%)
1382
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 3
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 2
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4791
69.7%
Common 1918
27.9%
Han 148
 
2.2%
Latin 18
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 137
 
2.9%
에 101
 
2.1%
기 100
 
2.1%
이 100
 
2.1%
조 83
 
1.7%
로 71
 
1.5%
한 69
 
1.4%
을 69
 
1.4%
도 65
 
1.4%
지 64
 
1.3%
Other values (444) 3932
82.1%
Han
ValueCountFrequency (%)
形 3
 
2.0%
君 3
 
2.0%
山 3
 
2.0%
李 2
 
1.4%
文 2
 
1.4%
圖 2
 
1.4%
氏 2
 
1.4%
顧 2
 
1.4%
烈 2
 
1.4%
梯 2
 
1.4%
Other values (116) 125
84.5%
Common
ValueCountFrequency (%)
1382
72.1%
1 67
 
3.5%
) 62
 
3.2%
( 61
 
3.2%
, 54
 
2.8%
9 32
 
1.7%
2 28
 
1.5%
6 25
 
1.3%
0 24
 
1.3%
3 23
 
1.2%
Other values (19) 160
 
8.3%
Latin
ValueCountFrequency (%)
m 3
16.7%
c 3
16.7%
b 2
11.1%
e 2
11.1%
a 1
 
5.6%
s 1
 
5.6%
u 1
 
5.6%
l 1
 
5.6%
r 1
 
5.6%
i 1
 
5.6%
Other values (2) 2
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4791
69.7%
ASCII 1916
 
27.9%
CJK 139
 
2.0%
None 12
 
0.2%
CJK Compat Ideographs 9
 
0.1%
Punctuation 4
 
0.1%
CJK Compat 3
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1382
72.1%
1 67
 
3.5%
) 62
 
3.2%
( 61
 
3.2%
, 54
 
2.8%
9 32
 
1.7%
2 28
 
1.5%
6 25
 
1.3%
0 24
 
1.3%
3 23
 
1.2%
Other values (22) 158
 
8.2%
Hangul
ValueCountFrequency (%)
의 137
 
2.9%
에 101
 
2.1%
기 100
 
2.1%
이 100
 
2.1%
조 83
 
1.7%
로 71
 
1.5%
한 69
 
1.4%
을 69
 
1.4%
도 65
 
1.4%
지 64
 
1.3%
Other values (444) 3932
82.1%
None
ValueCountFrequency (%)
· 4
33.3%
『 2
16.7%
』 2
16.7%
」 2
16.7%
「 2
16.7%
CJK
ValueCountFrequency (%)
形 3
 
2.2%
君 3
 
2.2%
山 3
 
2.2%
文 2
 
1.4%
圖 2
 
1.4%
氏 2
 
1.4%
顧 2
 
1.4%
烈 2
 
1.4%
梯 2
 
1.4%
櫃 2
 
1.4%
Other values (109) 116
83.5%
CJK Compat
ValueCountFrequency (%)
㎡ 3
100.0%
Punctuation
ValueCountFrequency (%)
‘ 2
50.0%
’ 2
50.0%
CJK Compat Ideographs
ValueCountFrequency (%)
李 2
22.2%
金 2
22.2%
弄 1
11.1%
靈 1
11.1%
麟 1
11.1%
柳 1
11.1%
禮 1
11.1%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%

hompage
Categorical

Distinct24
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
187 
http://www.heritage.go.kr/heri/idx/index.do
122 
http://www.gijang.go.kr/tour/index.gijang
64 
www.cha.go.kr
54 
http://www.yeongdo.go.kr/tour.web
22 
Other values (19)
70 

Length

Max length104
Median length56
Mean length23.132948
Min length1

Unique

Unique11 ?
Unique (%)2.1%

Sample

1st rowhttp://www.heritage.go.kr/heri/idx/index.do
2nd rowhttp://www.heritage.go.kr/heri/idx/index.do
3rd rowhttp://www.heritage.go.kr/heri/idx/index.do
4th rowhttp://www.heritage.go.kr/heri/idx/index.do
5th rowhttp://www.heritage.go.kr/heri/idx/index.do

Common Values

ValueCountFrequency (%)
<NA> 187
36.0%
http://www.heritage.go.kr/heri/idx/index.do 122
23.5%
http://www.gijang.go.kr/tour/index.gijang 64
 
12.3%
www.cha.go.kr 54
 
10.4%
http://www.yeongdo.go.kr/tour.web 22
 
4.2%
해당없음 18
 
3.5%
- 16
 
3.1%
http://www.bsbukgu.go.kr/board/list.bsbukgu?boardId=LIFE&menuCd=DOM_000000107001006000&contentsSid=1864# 8
 
1.5%
http://www.sasang.go.kr 7
 
1.3%
2021-01-05 14:51:52 3
 
0.6%
Other values (14) 18
 
3.5%

Length

2024-04-17T07:16:46.818640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 187
35.8%
http://www.heritage.go.kr/heri/idx/index.do 122
23.4%
http://www.gijang.go.kr/tour/index.gijang 64
 
12.3%
www.cha.go.kr 54
 
10.3%
http://www.yeongdo.go.kr/tour.web 22
 
4.2%
해당없음 18
 
3.4%
16
 
3.1%
http://www.bsbukgu.go.kr/board/list.bsbukgu?boardid=life&menucd=dom_000000107001006000&contentssid=1864 8
 
1.5%
http://www.sasang.go.kr 7
 
1.3%
2021-01-05 3
 
0.6%
Other values (15) 21
 
4.0%

area
Text

MISSING 

Distinct51
Distinct (%)52.0%
Missing421
Missing (%)81.1%
Memory size4.2 KiB
2024-04-17T07:16:47.006292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length12
Mean length5.6836735
Min length1

Characters and Unicode

Total characters557
Distinct characters33
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)46.9%

Sample

1st row33필지 66,068㎡
2nd row7필지 22,933㎡
3rd row830370.24㎡
4th row1동 2631㎡
5th row1기 22㎡, 1동 51㎡
ValueCountFrequency (%)
18
 
14.2%
해당없음 16
 
12.6%
0 13
 
10.2%
3필지 4
 
3.1%
1필지 4
 
3.1%
4,023㎡ 3
 
2.4%
19,533 2
 
1.6%
높이 2
 
1.6%
2필지 2
 
1.6%
1동 2
 
1.6%
Other values (61) 61
48.0%
2024-04-17T07:16:47.313519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 51
 
9.2%
2 44
 
7.9%
㎡ 43
 
7.7%
, 42
 
7.5%
3 36
 
6.5%
4 30
 
5.4%
0 29
 
5.2%
29
 
5.2%
8 24
 
4.3%
- 22
 
3.9%
Other values (23) 207
37.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 287
51.5%
Other Letter 119
21.4%
Other Punctuation 50
 
9.0%
Other Symbol 43
 
7.7%
Space Separator 29
 
5.2%
Dash Punctuation 22
 
3.9%
Open Punctuation 3
 
0.5%
Lowercase Letter 2
 
0.4%
Close Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 22
18.5%
필 21
17.6%
음 16
13.4%
해 16
13.4%
당 16
13.4%
없 16
13.4%
이 2
 
1.7%
높 2
 
1.7%
동 2
 
1.7%
기 1
 
0.8%
Other values (5) 5
 
4.2%
Decimal Number
ValueCountFrequency (%)
1 51
17.8%
2 44
15.3%
3 36
12.5%
4 30
10.5%
0 29
10.1%
8 24
8.4%
5 20
 
7.0%
9 19
 
6.6%
6 19
 
6.6%
7 15
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 42
84.0%
. 8
 
16.0%
Other Symbol
ValueCountFrequency (%)
㎡ 43
100.0%
Space Separator
ValueCountFrequency (%)
29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 436
78.3%
Hangul 119
 
21.4%
Latin 2
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 51
11.7%
2 44
10.1%
㎡ 43
9.9%
, 42
9.6%
3 36
8.3%
4 30
 
6.9%
0 29
 
6.7%
29
 
6.7%
8 24
 
5.5%
- 22
 
5.0%
Other values (7) 86
19.7%
Hangul
ValueCountFrequency (%)
지 22
18.5%
필 21
17.6%
음 16
13.4%
해 16
13.4%
당 16
13.4%
없 16
13.4%
이 2
 
1.7%
높 2
 
1.7%
동 2
 
1.7%
기 1
 
0.8%
Other values (5) 5
 
4.2%
Latin
ValueCountFrequency (%)
m 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 395
70.9%
Hangul 119
 
21.4%
CJK Compat 43
 
7.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 51
12.9%
2 44
11.1%
, 42
10.6%
3 36
9.1%
4 30
7.6%
0 29
7.3%
29
7.3%
8 24
 
6.1%
- 22
 
5.6%
5 20
 
5.1%
Other values (7) 68
17.2%
CJK Compat
ValueCountFrequency (%)
㎡ 43
100.0%
Hangul
ValueCountFrequency (%)
지 22
18.5%
필 21
17.6%
음 16
13.4%
해 16
13.4%
당 16
13.4%
없 16
13.4%
이 2
 
1.7%
높 2
 
1.7%
동 2
 
1.7%
기 1
 
0.8%
Other values (5) 5
 
4.2%

tel
Categorical

Distinct40
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
051-519-4092
122 
051-709-3971
64 
051-607-4065
54 
051-200-8493
53 
051-550-4081
41 
Other values (35)
185 

Length

Max length12
Median length12
Mean length11.429672
Min length4

Unique

Unique17 ?
Unique (%)3.3%

Sample

1st row051-519-4092
2nd row051-519-4092
3rd row051-519-4092
4th row051-519-4092
5th row051-519-4092

Common Values

ValueCountFrequency (%)
051-519-4092 122
23.5%
051-709-3971 64
12.3%
051-607-4065 54
10.4%
051-200-8493 53
10.2%
051-550-4081 41
 
7.9%
<NA> 37
 
7.1%
051-605-4065 20
 
3.9%
051-610-4067 18
 
3.5%
051-419-4065 18
 
3.5%
051-440-4064 16
 
3.1%
Other values (30) 76
14.6%

Length

2024-04-17T07:16:47.425329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-519-4092 122
23.5%
051-709-3971 64
12.3%
051-607-4065 54
10.4%
051-200-8493 53
10.2%
051-550-4081 41
 
7.9%
na 37
 
7.1%
051-605-4065 20
 
3.9%
051-610-4067 18
 
3.5%
051-419-4065 18
 
3.5%
051-970-4065 16
 
3.1%
Other values (30) 76
14.6%

gugun
Categorical

Distinct16
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
부산광역시 금정구
122 
부산광역시 서구
70 
부산광역시 기장군
64 
부산광역시 남구
54 
부산광역시 동래구
41 
Other values (11)
168 

Length

Max length10
Median length9
Mean length8.5298651
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 금정구
2nd row부산광역시 금정구
3rd row부산광역시 금정구
4th row부산광역시 금정구
5th row부산광역시 금정구

Common Values

ValueCountFrequency (%)
부산광역시 금정구 122
23.5%
부산광역시 서구 70
13.5%
부산광역시 기장군 64
12.3%
부산광역시 남구 54
10.4%
부산광역시 동래구 41
 
7.9%
<NA> 27
 
5.2%
부산광역시 영도구 22
 
4.2%
부산광역시 부산진구 20
 
3.9%
부산광역시 해운대구 19
 
3.7%
부산광역시 수영구 18
 
3.5%
Other values (6) 62
11.9%

Length

2024-04-17T07:16:47.523413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산광역시 492
48.7%
금정구 122
 
12.1%
서구 70
 
6.9%
기장군 64
 
6.3%
남구 54
 
5.3%
동래구 41
 
4.1%
na 27
 
2.7%
영도구 22
 
2.2%
부산진구 20
 
2.0%
해운대구 19
 
1.9%
Other values (7) 80
 
7.9%

data_day
Date

MISSING 

Distinct7
Distinct (%)1.4%
Missing27
Missing (%)5.2%
Memory size4.2 KiB
Minimum2020-07-31 00:00:00
Maximum2020-09-02 00:00:00
2024-04-17T07:16:47.825756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:16:47.896250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

lat
Text

MISSING 

Distinct170
Distinct (%)35.0%
Missing33
Missing (%)6.4%
Memory size4.2 KiB
2024-04-17T07:16:48.105427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length8.9465021
Min length5

Characters and Unicode

Total characters4348
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)24.3%

Sample

1st row35.233
2nd row35.284
3rd row35.233
4th row35.284
5th row35.268
ValueCountFrequency (%)
35.284 84
 
17.3%
35.1037380240 53
 
10.9%
35.12957 24
 
4.9%
35.233 18
 
3.7%
35.12957n 18
 
3.7%
35.374403 16
 
3.3%
35.170952 9
 
1.9%
35.419956 8
 
1.6%
35.085661 8
 
1.6%
35.078566 8
 
1.6%
Other values (160) 240
49.4%
2024-04-17T07:16:48.440196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 819
18.8%
5 702
16.1%
. 486
11.2%
2 422
9.7%
1 365
8.4%
0 340
7.8%
4 293
 
6.7%
7 268
 
6.2%
8 267
 
6.1%
9 197
 
4.5%
Other values (3) 189
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3822
87.9%
Other Punctuation 486
 
11.2%
Uppercase Letter 24
 
0.6%
Space Separator 16
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 819
21.4%
5 702
18.4%
2 422
11.0%
1 365
9.5%
0 340
8.9%
4 293
 
7.7%
7 268
 
7.0%
8 267
 
7.0%
9 197
 
5.2%
6 149
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 486
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 24
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4324
99.4%
Latin 24
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
3 819
18.9%
5 702
16.2%
. 486
11.2%
2 422
9.8%
1 365
8.4%
0 340
7.9%
4 293
 
6.8%
7 268
 
6.2%
8 267
 
6.2%
9 197
 
4.6%
Other values (2) 165
 
3.8%
Latin
ValueCountFrequency (%)
N 24
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 819
18.8%
5 702
16.1%
. 486
11.2%
2 422
9.7%
1 365
8.4%
0 340
7.8%
4 293
 
6.7%
7 268
 
6.2%
8 267
 
6.1%
9 197
 
4.5%
Other values (3) 189
 
4.3%

lng
Text

MISSING 

Distinct170
Distinct (%)35.0%
Missing33
Missing (%)6.4%
Memory size4.2 KiB
2024-04-17T07:16:48.695179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length9.9279835
Min length6

Characters and Unicode

Total characters4825
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique117 ?
Unique (%)24.1%

Sample

1st row129.082
2nd row129.068
3rd row129.082
4th row129.068
5th row129.113
ValueCountFrequency (%)
129.068 82
 
16.9%
129.0194102944 53
 
10.9%
129.09416 24
 
4.9%
129.082 19
 
3.9%
129.09416e 18
 
3.7%
129.232923 16
 
3.3%
129.113983 9
 
1.9%
129.095995 8
 
1.6%
129.080249 8
 
1.6%
129.044144 8
 
1.6%
Other values (160) 241
49.6%
2024-04-17T07:16:49.059051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 849
17.6%
9 822
17.0%
2 785
16.3%
0 514
10.7%
. 486
10.1%
4 372
7.7%
8 307
 
6.4%
6 230
 
4.8%
3 179
 
3.7%
7 121
 
2.5%
Other values (3) 160
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4299
89.1%
Other Punctuation 486
 
10.1%
Uppercase Letter 24
 
0.5%
Space Separator 16
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 849
19.7%
9 822
19.1%
2 785
18.3%
0 514
12.0%
4 372
8.7%
8 307
 
7.1%
6 230
 
5.4%
3 179
 
4.2%
7 121
 
2.8%
5 120
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 486
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 24
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4801
99.5%
Latin 24
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 849
17.7%
9 822
17.1%
2 785
16.4%
0 514
10.7%
. 486
10.1%
4 372
7.7%
8 307
 
6.4%
6 230
 
4.8%
3 179
 
3.7%
7 121
 
2.5%
Other values (2) 136
 
2.8%
Latin
ValueCountFrequency (%)
E 24
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4825
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 849
17.6%
9 822
17.0%
2 785
16.3%
0 514
10.7%
. 486
10.1%
4 372
7.7%
8 307
 
6.4%
6 230
 
4.8%
3 179
 
3.7%
7 121
 
2.5%
Other values (3) 160
 
3.3%

apr_at
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
503 
 
16

Length

Max length4
Median length4
Mean length3.9075145
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 503
96.9%
16
 
3.1%

Length

2024-04-17T07:16:49.174169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:16:49.247967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 503
100.0%

last_load_dttm
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing27
Missing (%)5.2%
Memory size4.2 KiB
Minimum2021-01-05 14:51:52
Maximum2021-01-05 14:51:52
2024-04-17T07:16:49.313942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:16:49.382081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Sample

skeyinstt_codecult_herit_nmroad_addraddrorgan_managenumberdateserakindmain_agentinstalled_yearmajor_contentshompageareatelgugundata_daylatlngapr_atlast_load_dttm
031593350000훈몽자회 책판<NA>부산시 금정구 부산대학로 63번길 2 부산대학교박물관부산대학교제166호2015-09-16조선후기유형문화재<NA><NA>목판각류http://www.heritage.go.kr/heri/idx/index.do<NA>051-519-4092부산광역시 금정구2020-08-2135.233129.082<NA>2021-01-05 14:51:52
131603350000범어사 극락암 칠성도<NA>부산시 금정구 범어사로 250 금정산 범어사범어사제167호2016-01-201861년유형문화재<NA>1861년불화http://www.heritage.go.kr/heri/idx/index.do<NA>051-519-4092부산광역시 금정구2020-08-2135.284129.068<NA>2021-01-05 14:51:52
231613350000승자총통<NA>부산시 금정구 부산대학로 63번길 2 부산대학교박물관부산대학교제168호2016-03-161583년유형문화재<NA>1583년병기류http://www.heritage.go.kr/heri/idx/index.do<NA>051-519-4092부산광역시 금정구2020-08-2135.233129.082<NA>2021-01-05 14:51:52
331623350000범어사 원효암 목조관음보살좌상 복장유물 일괄<NA>부산시 금정구 범어사로 250 금정산 범어사범어사제173호2016-09-21조선후기유형문화재<NA><NA>복장류http://www.heritage.go.kr/heri/idx/index.do<NA>051-519-4092부산광역시 금정구2020-08-2135.284129.068<NA>2021-01-05 14:51:52
431633350000삼층석탑<NA>부산시 금정구 상현로 79번길 59-15금정구청제175호2016-09-21통일신라유형문화재<NA><NA>석탑http://www.heritage.go.kr/heri/idx/index.do<NA>051-519-4092부산광역시 금정구2020-08-2135.268129.113<NA>2021-01-05 14:51:52
531643350000범어사 목조팔각불감<NA>부산시 금정구 범어사로 250 금정산 범어사범어사제176호2016-11-23조선후기유형문화재<NA><NA>목판각류http://www.heritage.go.kr/heri/idx/index.do<NA>051-519-4092부산광역시 금정구2020-08-2135.284129.068<NA>2021-01-05 14:51:52
631653350000설뫼탐진안씨분재기<NA>부산시 금정구 부산대학로 63번길 2 부산대학교도서관부산대학교제177호2016-11-231650년유형문화재<NA>1650년도서http://www.heritage.go.kr/heri/idx/index.do<NA>051-519-4092부산광역시 금정구2020-08-2135.233129.082<NA>2021-01-05 14:51:52
730963350000불조삼경<NA>부산시 금정구 범어사로 250 금정산 범어사범어사제1224-2호2007-09-18고려말기보물<NA><NA>불교 경전http://www.heritage.go.kr/heri/idx/index.do<NA>051-519-4092부산광역시 금정구2020-08-2135.284129.068<NA>2021-01-05 14:51:52
830973350000부산 범어사 조계문<NA>부산시 금정구 범어사로 250 금정산 범어사범어사제1461호2006-02-0717세기보물<NA><NA>목조 건축물http://www.heritage.go.kr/heri/idx/index.do<NA>051-519-4092부산광역시 금정구2020-08-2135.284129.068<NA>2021-01-05 14:51:52
930983350000금장요집경 권1-2<NA>부산시 금정구 범어사로 250 금정산 범어사범어사제1525호2007-09-18고려말기보물<NA><NA>불교 경전http://www.heritage.go.kr/heri/idx/index.do<NA>051-519-4092부산광역시 금정구2020-08-2135.284129.068<NA>2021-01-05 14:51:52
skeyinstt_codecult_herit_nmroad_addraddrorgan_managenumberdateserakindmain_agentinstalled_yearmajor_contentshompageareatelgugundata_daylatlngapr_atlast_load_dttm
509한국 교량사(토목)에 있어서도 유례가 없어 근대 교량사를 연구하는 데에 대단히 중요한 교량으로 그 보존가치가 매우 높다.<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
510일제강점기부터 부산시민과 애환을 함께 해 온 영도대교는 8.15해방과 6.25전쟁http://www.bsjunggu.go.kr/tour/index.junggu폭 18.3m<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
511길이 214.7m051-600-4066부산광역시 중구2020-07-3135.092616129.038322<NA>2021-01-05 14:51:52<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51233613310000목조여래좌상(木造如來坐像)<NA>부산광역시 남구 대연동 948-1부산박물관제159호2015-07-1518C 후반시지정 유형문화재<NA>18C 후반차분하면서도 근엄한 인상, 긴 상반신에 낮은 무릎과 적당한 다리 폭 등 17세기 전반 불상의 특징www.cha.go.kr<NA>051-607-4065부산광역시 남구2020-07-3135.12957N129.09416E<NA>2021-01-05 14:51:52
51334463330000해운대석각<NA>부산광역시 해운대구 우동 710-4부산광역시 해운대구청부산시 지정기념물1999-03-09고려말 이전기념물최치원(추정)고려말 이전최치원이 쓴 것으로 추정되는 동백섬 내에 있는 바위에 새긴 글씨http://www.haeundae.go.kr/html/00_main/2,347㎡051-749-7605부산광역시 해운대구2020-08-3135.1528920966129.1528889828<NA>2021-01-05 14:51:52
51434473330000동백섬<NA>부산광역시 해운대구 우동 721외 83필지부산광역시 해운대구청부산시 지정기념물1999-03-09(자연환경)자연환경(자연환경)(자연환경)해운대 해수욕장 한편에 위치한 육계도http://www.haeundae.go.kr/html/00_main/151.545㎡051-749-7605부산광역시 해운대구2020-08-3135.1550859010129.1515809776<NA>2021-01-05 14:51:52
51534483330000장산 마고당, 천제당<NA>부산광역시 해운대구 우동 산148-1좌동향토문화보전사업회부산시 민속문화재2009-12-07조선후기민속문화재민간조선후기조선 후기 지역 수호신 마고할미를 모시는 제당과 천신·지신·산신을 모시는 제단<NA>1,698㎡051-703-1995부산광역시 해운대구2020-08-3135.1918466417129.1551087335<NA>2021-01-05 14:51:52
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