Overview

Dataset statistics

Number of variables22
Number of observations539
Missing cells1623
Missing cells (%)13.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory94.3 KiB
Average record size in memory179.2 B

Variable types

Numeric2
Text11
Unsupported1
DateTime3
Categorical4
Boolean1

Alerts

apr_at has constant value ""Constant
last_load_dttm has constant value ""Constant
main_agent is highly imbalanced (73.1%)Imbalance
road_addr has 539 (100.0%) missing valuesMissing
era has 67 (12.4%) missing valuesMissing
installed_year has 313 (58.1%) missing valuesMissing
major_contents has 259 (48.1%) missing valuesMissing
area has 413 (76.6%) missing valuesMissing
apr_at has 30 (5.6%) missing valuesMissing
skey has unique valuesUnique
road_addr is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-16 22:16:08.888096
Analysis finished2024-04-16 22:16:09.810447
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct539
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3867.6716
Minimum3081
Maximum4195
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2024-04-17T07:16:09.867434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3081
5-th percentile3446.9
Q13748.5
median3883
Q34017.5
95-th percentile4168.1
Maximum4195
Range1114
Interquartile range (IQR)269

Descriptive statistics

Standard deviation205.15056
Coefficient of variation (CV)0.053042394
Kurtosis2.7006387
Mean3867.6716
Median Absolute Deviation (MAD)135
Skewness-1.1617627
Sum2084675
Variance42086.753
MonotonicityNot monotonic
2024-04-17T07:16:09.971170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4125 1
 
0.2%
3867 1
 
0.2%
3881 1
 
0.2%
3880 1
 
0.2%
3879 1
 
0.2%
3878 1
 
0.2%
3877 1
 
0.2%
3876 1
 
0.2%
3875 1
 
0.2%
3874 1
 
0.2%
Other values (529) 529
98.1%
ValueCountFrequency (%)
3081 1
0.2%
3082 1
0.2%
3083 1
0.2%
3084 1
0.2%
3085 1
0.2%
3086 1
0.2%
3087 1
0.2%
3088 1
0.2%
3089 1
0.2%
3090 1
0.2%
ValueCountFrequency (%)
4195 1
0.2%
4194 1
0.2%
4193 1
0.2%
4192 1
0.2%
4191 1
0.2%
4190 1
0.2%
4189 1
0.2%
4188 1
0.2%
4187 1
0.2%
4186 1
0.2%

instt_code
Real number (ℝ)

Distinct16
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3328126.2
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2024-04-17T07:16:10.087883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13290000
median3330000
Q33350000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation44704.886
Coefficient of variation (CV)0.013432449
Kurtosis-1.0732214
Mean3328126.2
Median Absolute Deviation (MAD)30000
Skewness-0.061249399
Sum1.79386 × 109
Variance1.9985268 × 109
MonotonicityNot monotonic
2024-04-17T07:16:10.205451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3350000 122
22.6%
3260000 72
13.4%
3400000 60
11.1%
3310000 53
9.8%
3300000 43
 
8.0%
3330000 39
 
7.2%
3370000 33
 
6.1%
3280000 22
 
4.1%
3290000 20
 
3.7%
3380000 18
 
3.3%
Other values (6) 57
10.6%
ValueCountFrequency (%)
3250000 6
 
1.1%
3260000 72
13.4%
3270000 16
 
3.0%
3280000 22
 
4.1%
3290000 20
 
3.7%
3300000 43
8.0%
3310000 53
9.8%
3320000 8
 
1.5%
3330000 39
7.2%
3340000 4
 
0.7%
ValueCountFrequency (%)
3400000 60
11.1%
3390000 7
 
1.3%
3380000 18
 
3.3%
3370000 33
 
6.1%
3360000 16
 
3.0%
3350000 122
22.6%
3340000 4
 
0.7%
3330000 39
 
7.2%
3320000 8
 
1.5%
3310000 53
9.8%

cult_herit_nm
Text

Distinct492
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-04-17T07:16:10.388140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length24
Mean length10.319109
Min length2

Characters and Unicode

Total characters5562
Distinct characters594
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique456 ?
Unique (%)84.6%

Sample

1st row다대진동헌
2nd row청동북(靑銅金鼓)
3rd row칠보사 목조관음보살좌상
4th row흑유호 및 흑유정병
5th row홍현주 필 산수도
ValueCountFrequency (%)
범어사 79
 
6.8%
부산 27
 
2.3%
마하사 21
 
1.8%
응진전 17
 
1.5%
묘법연화경 16
 
1.4%
및 15
 
1.3%
장안사 14
 
1.2%
영산회상도 13
 
1.1%
기장 12
 
1.0%
대웅전 12
 
1.0%
Other values (670) 936
80.6%
2024-04-17T07:16:10.691111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
627
 
11.3%
사 270
 
4.9%
도 116
 
2.1%
상 112
 
2.0%
어 92
 
1.7%
산 91
 
1.6%
범 89
 
1.6%
조 89
 
1.6%
동 87
 
1.6%
장 72
 
1.3%
Other values (584) 3917
70.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4712
84.7%
Space Separator 627
 
11.3%
Close Punctuation 70
 
1.3%
Open Punctuation 70
 
1.3%
Decimal Number 57
 
1.0%
Other Punctuation 10
 
0.2%
Dash Punctuation 8
 
0.1%
Math Symbol 6
 
0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 270
 
5.7%
도 116
 
2.5%
상 112
 
2.4%
어 92
 
2.0%
산 91
 
1.9%
범 89
 
1.9%
조 89
 
1.9%
동 87
 
1.8%
장 72
 
1.5%
전 67
 
1.4%
Other values (564) 3627
77.0%
Decimal Number
ValueCountFrequency (%)
1 13
22.8%
2 11
19.3%
4 9
15.8%
7 7
12.3%
6 5
 
8.8%
3 5
 
8.8%
0 3
 
5.3%
5 3
 
5.3%
8 1
 
1.8%
Other Punctuation
ValueCountFrequency (%)
, 7
70.0%
· 1
 
10.0%
. 1
 
10.0%
? 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
N 1
50.0%
U 1
50.0%
Space Separator
ValueCountFrequency (%)
627
100.0%
Close Punctuation
ValueCountFrequency (%)
) 70
100.0%
Open Punctuation
ValueCountFrequency (%)
( 70
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4271
76.8%
Common 848
 
15.2%
Han 441
 
7.9%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 270
 
6.3%
도 116
 
2.7%
상 112
 
2.6%
어 92
 
2.2%
산 91
 
2.1%
범 89
 
2.1%
조 89
 
2.1%
동 87
 
2.0%
장 72
 
1.7%
전 67
 
1.6%
Other values (325) 3186
74.6%
Han
ValueCountFrequency (%)
圖 16
 
3.6%
像 12
 
2.7%
坐 8
 
1.8%
山 8
 
1.8%
括 7
 
1.6%
一 7
 
1.6%
碑 7
 
1.6%
造 7
 
1.6%
薩 6
 
1.4%
石 6
 
1.4%
Other values (229) 357
81.0%
Common
ValueCountFrequency (%)
627
73.9%
) 70
 
8.3%
( 70
 
8.3%
1 13
 
1.5%
2 11
 
1.3%
4 9
 
1.1%
- 8
 
0.9%
7 7
 
0.8%
, 7
 
0.8%
~ 6
 
0.7%
Other values (8) 20
 
2.4%
Latin
ValueCountFrequency (%)
N 1
50.0%
U 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4271
76.8%
ASCII 849
 
15.3%
CJK 424
 
7.6%
CJK Compat Ideographs 17
 
0.3%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
627
73.9%
) 70
 
8.2%
( 70
 
8.2%
1 13
 
1.5%
2 11
 
1.3%
4 9
 
1.1%
- 8
 
0.9%
7 7
 
0.8%
, 7
 
0.8%
~ 6
 
0.7%
Other values (9) 21
 
2.5%
Hangul
ValueCountFrequency (%)
사 270
 
6.3%
도 116
 
2.7%
상 112
 
2.6%
어 92
 
2.2%
산 91
 
2.1%
범 89
 
2.1%
조 89
 
2.1%
동 87
 
2.0%
장 72
 
1.7%
전 67
 
1.6%
Other values (325) 3186
74.6%
CJK
ValueCountFrequency (%)
圖 16
 
3.8%
像 12
 
2.8%
坐 8
 
1.9%
山 8
 
1.9%
括 7
 
1.7%
一 7
 
1.7%
碑 7
 
1.7%
造 7
 
1.7%
薩 6
 
1.4%
石 6
 
1.4%
Other values (219) 340
80.2%
CJK Compat Ideographs
ValueCountFrequency (%)
金 5
29.4%
李 3
17.6%
柳 2
 
11.8%
琉 1
 
5.9%
沈 1
 
5.9%
龍 1
 
5.9%
列 1
 
5.9%
禮 1
 
5.9%
蠟 1
 
5.9%
立 1
 
5.9%
None
ValueCountFrequency (%)
· 1
100.0%

road_addr
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing539
Missing (%)100.0%
Memory size4.9 KiB

addr
Text

Distinct186
Distinct (%)34.5%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-04-17T07:16:10.924038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length33
Mean length20.115028
Min length7

Characters and Unicode

Total characters10842
Distinct characters178
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

Unique116 ?
Unique (%)21.5%

Sample

1st row부산광역시 사하구 다대동 산144
2nd row부산광역시 서구 부민동2가 1
3rd row부산광역시 서구 남부민동 93-1
4th row부산광역시 서구 부민동2가 1
5th row부산광역시 서구 부민동2가 2
ValueCountFrequency (%)
부산광역시 303
 
12.4%
부산시 155
 
6.3%
금정구 128
 
5.2%
범어사로 93
 
3.8%
범어사 91
 
3.7%
250 88
 
3.6%
금정산 82
 
3.4%
서구 72
 
2.9%
부민동2가 57
 
2.3%
1 56
 
2.3%
Other values (369) 1316
53.9%
2024-04-17T07:16:11.292563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1908
 
17.6%
산 686
 
6.3%
부 601
 
5.5%
구 484
 
4.5%
시 470
 
4.3%
동 367
 
3.4%
1 334
 
3.1%
광 317
 
2.9%
역 306
 
2.8%
2 286
 
2.6%
Other values (168) 5083
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6915
63.8%
Space Separator 1908
 
17.6%
Decimal Number 1700
 
15.7%
Dash Punctuation 151
 
1.4%
Close Punctuation 68
 
0.6%
Open Punctuation 68
 
0.6%
Other Punctuation 32
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 686
 
9.9%
부 601
 
8.7%
구 484
 
7.0%
시 470
 
6.8%
동 367
 
5.3%
광 317
 
4.6%
역 306
 
4.4%
로 248
 
3.6%
사 243
 
3.5%
정 229
 
3.3%
Other values (153) 2964
42.9%
Decimal Number
ValueCountFrequency (%)
1 334
19.6%
2 286
16.8%
5 181
10.6%
3 174
10.2%
4 154
9.1%
0 147
8.6%
6 121
 
7.1%
8 120
 
7.1%
9 108
 
6.4%
7 75
 
4.4%
Space Separator
ValueCountFrequency (%)
1908
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 151
100.0%
Close Punctuation
ValueCountFrequency (%)
) 68
100.0%
Open Punctuation
ValueCountFrequency (%)
( 68
100.0%
Other Punctuation
ValueCountFrequency (%)
, 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6915
63.8%
Common 3927
36.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 686
 
9.9%
부 601
 
8.7%
구 484
 
7.0%
시 470
 
6.8%
동 367
 
5.3%
광 317
 
4.6%
역 306
 
4.4%
로 248
 
3.6%
사 243
 
3.5%
정 229
 
3.3%
Other values (153) 2964
42.9%
Common
ValueCountFrequency (%)
1908
48.6%
1 334
 
8.5%
2 286
 
7.3%
5 181
 
4.6%
3 174
 
4.4%
4 154
 
3.9%
- 151
 
3.8%
0 147
 
3.7%
6 121
 
3.1%
8 120
 
3.1%
Other values (5) 351
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6915
63.8%
ASCII 3927
36.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1908
48.6%
1 334
 
8.5%
2 286
 
7.3%
5 181
 
4.6%
3 174
 
4.4%
4 154
 
3.9%
- 151
 
3.8%
0 147
 
3.7%
6 121
 
3.1%
8 120
 
3.1%
Other values (5) 351
 
8.9%
Hangul
ValueCountFrequency (%)
산 686
 
9.9%
부 601
 
8.7%
구 484
 
7.0%
시 470
 
6.8%
동 367
 
5.3%
광 317
 
4.6%
역 306
 
4.4%
로 248
 
3.6%
사 243
 
3.5%
정 229
 
3.3%
Other values (153) 2964
42.9%

organ_manage
Text

Distinct127
Distinct (%)23.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-04-17T07:16:11.457242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length5.1280148
Min length2

Characters and Unicode

Total characters2764
Distinct characters172
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)11.1%

Sample

1st row사하구
2nd row동아대학교
3rd row칠보사
4th row동아대학교
5th row동아대학교
ValueCountFrequency (%)
범어사 91
 
15.2%
동아대학교 57
 
9.5%
부산박물관 45
 
7.5%
부산광역시 30
 
5.0%
동래구청장 18
 
3.0%
부산대학교 18
 
3.0%
장안사 15
 
2.5%
마하사 15
 
2.5%
수영구청 11
 
1.8%
기장군 9
 
1.5%
Other values (126) 290
48.4%
2024-04-17T07:16:11.750844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 269
 
9.7%
산 143
 
5.2%
부 139
 
5.0%
관 96
 
3.5%
범 91
 
3.3%
어 91
 
3.3%
대 87
 
3.1%
교 87
 
3.1%
동 86
 
3.1%
구 83
 
3.0%
Other values (162) 1592
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2642
95.6%
Space Separator 60
 
2.2%
Close Punctuation 24
 
0.9%
Open Punctuation 24
 
0.9%
Decimal Number 6
 
0.2%
Other Punctuation 6
 
0.2%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 269
 
10.2%
산 143
 
5.4%
부 139
 
5.3%
관 96
 
3.6%
범 91
 
3.4%
어 91
 
3.4%
대 87
 
3.3%
교 87
 
3.3%
동 86
 
3.3%
구 83
 
3.1%
Other values (155) 1470
55.6%
Other Punctuation
ValueCountFrequency (%)
* 4
66.7%
, 2
33.3%
Space Separator
ValueCountFrequency (%)
60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Decimal Number
ValueCountFrequency (%)
0 6
100.0%
Uppercase Letter
ValueCountFrequency (%)
O 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2642
95.6%
Common 120
 
4.3%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 269
 
10.2%
산 143
 
5.4%
부 139
 
5.3%
관 96
 
3.6%
범 91
 
3.4%
어 91
 
3.4%
대 87
 
3.3%
교 87
 
3.3%
동 86
 
3.3%
구 83
 
3.1%
Other values (155) 1470
55.6%
Common
ValueCountFrequency (%)
60
50.0%
) 24
 
20.0%
( 24
 
20.0%
0 6
 
5.0%
* 4
 
3.3%
, 2
 
1.7%
Latin
ValueCountFrequency (%)
O 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2642
95.6%
ASCII 122
 
4.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 269
 
10.2%
산 143
 
5.4%
부 139
 
5.3%
관 96
 
3.6%
범 91
 
3.4%
어 91
 
3.4%
대 87
 
3.3%
교 87
 
3.3%
동 86
 
3.3%
구 83
 
3.1%
Other values (155) 1470
55.6%
ASCII
ValueCountFrequency (%)
60
49.2%
) 24
 
19.7%
( 24
 
19.7%
0 6
 
4.9%
* 4
 
3.3%
O 2
 
1.6%
, 2
 
1.6%

number
Text

Distinct324
Distinct (%)60.1%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-04-17T07:16:12.069831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.5139147
Min length3

Characters and Unicode

Total characters2972
Distinct characters49
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique219 ?
Unique (%)40.6%

Sample

1st row시지정유형문화재 제
2nd row제140호
3rd row제126호
4th row제101호
5th row제213호
ValueCountFrequency (%)
부산시 31
 
4.9%
시지정 26
 
4.1%
유형문화재 22
 
3.5%
문화재자료 20
 
3.2%
市지정 13
 
2.1%
제18호 8
 
1.3%
보물 8
 
1.3%
제4호 7
 
1.1%
부산광역시지정기념물 7
 
1.1%
제16호 7
 
1.1%
Other values (303) 485
76.5%
2024-04-17T07:16:12.494825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 467
15.7%
호 459
15.4%
1 270
 
9.1%
145
 
4.9%
2 128
 
4.3%
5 112
 
3.8%
9 103
 
3.5%
4 101
 
3.4%
3 95
 
3.2%
6 90
 
3.0%
Other values (39) 1002
33.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1658
55.8%
Decimal Number 1143
38.5%
Space Separator 145
 
4.9%
Dash Punctuation 22
 
0.7%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 467
28.2%
호 459
27.7%
시 76
 
4.6%
정 68
 
4.1%
지 66
 
4.0%
문 62
 
3.7%
재 58
 
3.5%
화 58
 
3.5%
산 45
 
2.7%
부 45
 
2.7%
Other values (25) 254
15.3%
Decimal Number
ValueCountFrequency (%)
1 270
23.6%
2 128
11.2%
5 112
9.8%
9 103
 
9.0%
4 101
 
8.8%
3 95
 
8.3%
6 90
 
7.9%
7 90
 
7.9%
8 84
 
7.3%
0 70
 
6.1%
Space Separator
ValueCountFrequency (%)
145
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1645
55.3%
Common 1314
44.2%
Han 13
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 467
28.4%
호 459
27.9%
시 76
 
4.6%
정 68
 
4.1%
지 66
 
4.0%
문 62
 
3.8%
재 58
 
3.5%
화 58
 
3.5%
산 45
 
2.7%
부 45
 
2.7%
Other values (24) 241
14.7%
Common
ValueCountFrequency (%)
1 270
20.5%
145
11.0%
2 128
9.7%
5 112
8.5%
9 103
 
7.8%
4 101
 
7.7%
3 95
 
7.2%
6 90
 
6.8%
7 90
 
6.8%
8 84
 
6.4%
Other values (4) 96
 
7.3%
Han
ValueCountFrequency (%)
市 13
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1645
55.3%
ASCII 1314
44.2%
CJK 13
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 467
28.4%
호 459
27.9%
시 76
 
4.6%
정 68
 
4.1%
지 66
 
4.0%
문 62
 
3.8%
재 58
 
3.5%
화 58
 
3.5%
산 45
 
2.7%
부 45
 
2.7%
Other values (24) 241
14.7%
ASCII
ValueCountFrequency (%)
1 270
20.5%
145
11.0%
2 128
9.7%
5 112
8.5%
9 103
 
7.8%
4 101
 
7.7%
3 95
 
7.2%
6 90
 
6.8%
7 90
 
6.8%
8 84
 
6.4%
Other values (4) 96
 
7.3%
CJK
ValueCountFrequency (%)
市 13
100.0%

dates
Date

Distinct174
Distinct (%)32.3%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum1962-12-20 00:00:00
Maximum2020-10-21 00:00:00
2024-04-17T07:16:12.605973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:16:12.712325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

era
Text

MISSING 

Distinct178
Distinct (%)37.7%
Missing67
Missing (%)12.4%
Memory size4.3 KiB
2024-04-17T07:16:12.973603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9.5
Mean length4.4173729
Min length1

Characters and Unicode

Total characters2085
Distinct characters60
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique121 ?
Unique (%)25.6%

Sample

1st row1825년
2nd row고려시대
3rd row1730년대
4th row12세기
5th row19세기
ValueCountFrequency (%)
조선시대 82
 
16.6%
조선후기 51
 
10.3%
삼국시대 13
 
2.6%
18세기 13
 
2.6%
조선초기 12
 
2.4%
고려시대 11
 
2.2%
1910년 11
 
2.2%
17세기 10
 
2.0%
조선중기 9
 
1.8%
19세기 8
 
1.6%
Other values (170) 274
55.5%
2024-04-17T07:16:13.320457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 247
 
11.8%
조 172
 
8.2%
선 172
 
8.2%
년 160
 
7.7%
기 148
 
7.1%
대 126
 
6.0%
시 110
 
5.3%
9 88
 
4.2%
8 80
 
3.8%
7 70
 
3.4%
Other values (50) 712
34.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1250
60.0%
Decimal Number 772
37.0%
Space Separator 29
 
1.4%
Math Symbol 14
 
0.7%
Dash Punctuation 6
 
0.3%
Uppercase Letter 5
 
0.2%
Open Punctuation 4
 
0.2%
Close Punctuation 2
 
0.1%
Lowercase Letter 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
조 172
13.8%
선 172
13.8%
년 160
12.8%
기 148
11.8%
대 126
10.1%
시 110
8.8%
후 62
 
5.0%
세 44
 
3.5%
고 29
 
2.3%
려 28
 
2.2%
Other values (31) 199
15.9%
Decimal Number
ValueCountFrequency (%)
1 247
32.0%
9 88
 
11.4%
8 80
 
10.4%
7 70
 
9.1%
6 59
 
7.6%
5 58
 
7.5%
0 58
 
7.5%
2 53
 
6.9%
4 36
 
4.7%
3 23
 
3.0%
Math Symbol
ValueCountFrequency (%)
~ 13
92.9%
～ 1
 
7.1%
Space Separator
ValueCountFrequency (%)
29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 2
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1250
60.0%
Common 828
39.7%
Latin 7
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
조 172
13.8%
선 172
13.8%
년 160
12.8%
기 148
11.8%
대 126
10.1%
시 110
8.8%
후 62
 
5.0%
세 44
 
3.5%
고 29
 
2.3%
려 28
 
2.2%
Other values (31) 199
15.9%
Common
ValueCountFrequency (%)
1 247
29.8%
9 88
 
10.6%
8 80
 
9.7%
7 70
 
8.5%
6 59
 
7.1%
5 58
 
7.0%
0 58
 
7.0%
2 53
 
6.4%
4 36
 
4.3%
29
 
3.5%
Other values (7) 50
 
6.0%
Latin
ValueCountFrequency (%)
C 5
71.4%
c 2
 
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1250
60.0%
ASCII 834
40.0%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 247
29.6%
9 88
 
10.6%
8 80
 
9.6%
7 70
 
8.4%
6 59
 
7.1%
5 58
 
7.0%
0 58
 
7.0%
2 53
 
6.4%
4 36
 
4.3%
29
 
3.5%
Other values (8) 56
 
6.7%
Hangul
ValueCountFrequency (%)
조 172
13.8%
선 172
13.8%
년 160
12.8%
기 148
11.8%
대 126
10.1%
시 110
8.8%
후 62
 
5.0%
세 44
 
3.5%
고 29
 
2.3%
려 28
 
2.2%
Other values (31) 199
15.9%
None
ValueCountFrequency (%)
～ 1
100.0%

kind
Text

Distinct55
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-04-17T07:16:13.489235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.2077922
Min length2

Characters and Unicode

Total characters2807
Distinct characters68
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

Unique20 ?
Unique (%)3.7%

Sample

1st row유형문화재
2nd row시지정유형문화재
3rd row시지정유형문화재
4th row시지정유형문화재
5th row시지정유형문화재
ValueCountFrequency (%)
유형문화재 182
28.8%
문화재자료 53
 
8.4%
보물 45
 
7.1%
시지정 39
 
6.2%
문화재 37
 
5.9%
기념물 36
 
5.7%
시지정유형문화재 33
 
5.2%
자료 22
 
3.5%
민속자료 21
 
3.3%
무형문화재 18
 
2.8%
Other values (41) 146
23.1%
2024-04-17T07:16:13.743739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
화 384
13.7%
문 378
13.5%
재 378
13.5%
형 238
 
8.5%
유 217
 
7.7%
시 113
 
4.0%
자 106
 
3.8%
물 105
 
3.7%
료 104
 
3.7%
지 102
 
3.6%
Other values (58) 682
24.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2706
96.4%
Space Separator 93
 
3.3%
Decimal Number 8
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 384
14.2%
문 378
14.0%
재 378
14.0%
형 238
8.8%
유 217
 
8.0%
시 113
 
4.2%
자 106
 
3.9%
물 105
 
3.9%
료 104
 
3.8%
지 102
 
3.8%
Other values (52) 581
21.5%
Decimal Number
ValueCountFrequency (%)
6 4
50.0%
7 1
 
12.5%
0 1
 
12.5%
1 1
 
12.5%
3 1
 
12.5%
Space Separator
ValueCountFrequency (%)
93
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2706
96.4%
Common 101
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
화 384
14.2%
문 378
14.0%
재 378
14.0%
형 238
8.8%
유 217
 
8.0%
시 113
 
4.2%
자 106
 
3.9%
물 105
 
3.9%
료 104
 
3.8%
지 102
 
3.8%
Other values (52) 581
21.5%
Common
ValueCountFrequency (%)
93
92.1%
6 4
 
4.0%
7 1
 
1.0%
0 1
 
1.0%
1 1
 
1.0%
3 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2706
96.4%
ASCII 101
 
3.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
화 384
14.2%
문 378
14.0%
재 378
14.0%
형 238
8.8%
유 217
 
8.0%
시 113
 
4.2%
자 106
 
3.9%
물 105
 
3.9%
료 104
 
3.8%
지 102
 
3.8%
Other values (52) 581
21.5%
ASCII
ValueCountFrequency (%)
93
92.1%
6 4
 
4.0%
7 1
 
1.0%
0 1
 
1.0%
1 1
 
1.0%
3 1
 
1.0%

main_agent
Categorical

IMBALANCE 

Distinct19
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
455 
미상
 
18
해당없음
 
17
-
 
16
국가
 
8
Other values (14)
 
25

Length

Max length11
Median length4
Mean length3.8441558
Min length1

Unique

Unique6 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 455
84.4%
미상 18
 
3.3%
해당없음 17
 
3.2%
- 16
 
3.0%
국가 8
 
1.5%
사하구 4
 
0.7%
운수사 3
 
0.6%
최치원(추정) 2
 
0.4%
고산 불명산 화암사 2
 
0.4%
동래부 2
 
0.4%
Other values (9) 12
 
2.2%

Length

2024-04-17T07:16:13.851265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 455
83.8%
해당없음 18
 
3.3%
미상 18
 
3.3%
16
 
2.9%
국가 8
 
1.5%
사하구 4
 
0.7%
운수사 3
 
0.6%
동래부 2
 
0.4%
박만정 2
 
0.4%
민간 2
 
0.4%
Other values (10) 15
 
2.8%

installed_year
Text

MISSING 

Distinct122
Distinct (%)54.0%
Missing313
Missing (%)58.1%
Memory size4.3 KiB
2024-04-17T07:16:14.062634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.5840708
Min length1

Characters and Unicode

Total characters1036
Distinct characters54
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

Unique87 ?
Unique (%)38.5%

Sample

1st row1825년
2nd row조선후기
3rd row-
4th row-
5th row1879년
ValueCountFrequency (%)
17
 
7.1%
조선후기 15
 
6.2%
해당없음 11
 
4.6%
조선초기 11
 
4.6%
조선시대 8
 
3.3%
조선중기 8
 
3.3%
18세기 8
 
3.3%
1882년 4
 
1.7%
1892년 4
 
1.7%
1906년 3
 
1.2%
Other values (118) 152
63.1%
2024-04-17T07:16:14.404946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 157
15.2%
년 112
 
10.8%
기 62
 
6.0%
9 57
 
5.5%
8 56
 
5.4%
선 47
 
4.5%
조 47
 
4.5%
6 44
 
4.2%
0 43
 
4.2%
5 41
 
4.0%
Other values (44) 370
35.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 518
50.0%
Other Letter 460
44.4%
Dash Punctuation 18
 
1.7%
Space Separator 17
 
1.6%
Math Symbol 10
 
1.0%
Uppercase Letter 5
 
0.5%
Open Punctuation 3
 
0.3%
Lowercase Letter 2
 
0.2%
Close Punctuation 2
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
년 112
24.3%
기 62
13.5%
선 47
10.2%
조 47
10.2%
후 21
 
4.6%
세 19
 
4.1%
초 14
 
3.0%
대 12
 
2.6%
음 11
 
2.4%
없 11
 
2.4%
Other values (26) 104
22.6%
Decimal Number
ValueCountFrequency (%)
1 157
30.3%
9 57
 
11.0%
8 56
 
10.8%
6 44
 
8.5%
0 43
 
8.3%
5 41
 
7.9%
7 40
 
7.7%
2 35
 
6.8%
4 27
 
5.2%
3 18
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 569
54.9%
Hangul 460
44.4%
Latin 7
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
년 112
24.3%
기 62
13.5%
선 47
10.2%
조 47
10.2%
후 21
 
4.6%
세 19
 
4.1%
초 14
 
3.0%
대 12
 
2.6%
음 11
 
2.4%
없 11
 
2.4%
Other values (26) 104
22.6%
Common
ValueCountFrequency (%)
1 157
27.6%
9 57
 
10.0%
8 56
 
9.8%
6 44
 
7.7%
0 43
 
7.6%
5 41
 
7.2%
7 40
 
7.0%
2 35
 
6.2%
4 27
 
4.7%
3 18
 
3.2%
Other values (6) 51
 
9.0%
Latin
ValueCountFrequency (%)
C 5
71.4%
c 2
 
28.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 576
55.6%
Hangul 460
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 157
27.3%
9 57
 
9.9%
8 56
 
9.7%
6 44
 
7.6%
0 43
 
7.5%
5 41
 
7.1%
7 40
 
6.9%
2 35
 
6.1%
4 27
 
4.7%
3 18
 
3.1%
Other values (8) 58
 
10.1%
Hangul
ValueCountFrequency (%)
년 112
24.3%
기 62
13.5%
선 47
10.2%
조 47
10.2%
후 21
 
4.6%
세 19
 
4.1%
초 14
 
3.0%
대 12
 
2.6%
음 11
 
2.4%
없 11
 
2.4%
Other values (26) 104
22.6%

major_contents
Text

MISSING 

Distinct178
Distinct (%)63.6%
Missing259
Missing (%)48.1%
Memory size4.3 KiB
2024-04-17T07:16:14.946940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length250
Median length85.5
Mean length31.778571
Min length1

Characters and Unicode

Total characters8898
Distinct characters657
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

Unique142 ?
Unique (%)50.7%

Sample

1st row동헌은 조선시대 지방관서에서 첨사가 정무를 보던 건물로 아사(衙舍)·군아(郡衙)·현아(縣衙)·시사청(視事廳) 등으로 부르기도 하였고 다대진성 내에 있던 관아건물 중에서 유일한 건축유구(建築遺構)로 지금은 몰운대 내의 부산광역시 사하구 몰운대1길 73(다대동 산144)에 옮겨져 있다.부산광역시 지정 유형문화재 제3호(1972. 6. 26)로 지정될 당시 다대포 객사라는 이름이 사용되었다가 2020년 7월 부산시 문화재 위원회 심의에서 다대진 동헌
2nd row불교 목공예품
3rd row-
4th row-
5th row삼세불부각
ValueCountFrequency (%)
도서 21
 
1.0%
있는 20
 
1.0%
19
 
0.9%
불화 16
 
0.8%
조선 16
 
0.8%
불교 15
 
0.7%
제작된 12
 
0.6%
것으로 9
 
0.4%
조선시대 9
 
0.4%
목판각류 8
 
0.4%
Other values (1415) 1907
92.9%
2024-04-17T07:16:15.402323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1819
 
20.4%
의 176
 
2.0%
에 135
 
1.5%
이 132
 
1.5%
기 126
 
1.4%
조 111
 
1.2%
로 97
 
1.1%
1 90
 
1.0%
사 89
 
1.0%
는 86
 
1.0%
Other values (647) 6037
67.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6365
71.5%
Space Separator 1819
 
20.4%
Decimal Number 371
 
4.2%
Other Punctuation 96
 
1.1%
Close Punctuation 83
 
0.9%
Open Punctuation 81
 
0.9%
Math Symbol 34
 
0.4%
Dash Punctuation 18
 
0.2%
Lowercase Letter 18
 
0.2%
Initial Punctuation 5
 
0.1%
Other values (2) 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 176
 
2.8%
에 135
 
2.1%
이 132
 
2.1%
기 126
 
2.0%
조 111
 
1.7%
로 97
 
1.5%
사 89
 
1.4%
는 86
 
1.4%
을 85
 
1.3%
한 84
 
1.3%
Other values (606) 5244
82.4%
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 90
24.3%
9 44
11.9%
6 36
 
9.7%
2 36
 
9.7%
0 33
 
8.9%
3 32
 
8.6%
7 32
 
8.6%
5 26
 
7.0%
4 22
 
5.9%
8 20
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 56
58.3%
. 30
31.2%
· 8
 
8.3%
? 2
 
2.1%
Math Symbol
ValueCountFrequency (%)
< 14
41.2%
> 14
41.2%
~ 4
 
11.8%
∼ 2
 
5.9%
Close Punctuation
ValueCountFrequency (%)
) 79
95.2%
』 2
 
2.4%
」 2
 
2.4%
Open Punctuation
ValueCountFrequency (%)
( 77
95.1%
『 2
 
2.5%
「 2
 
2.5%
Space Separator
ValueCountFrequency (%)
1819
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 5
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 5
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6189
69.6%
Common 2515
28.3%
Han 176
 
2.0%
Latin 18
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 176
 
2.8%
에 135
 
2.2%
이 132
 
2.1%
기 126
 
2.0%
조 111
 
1.8%
로 97
 
1.6%
사 89
 
1.4%
는 86
 
1.4%
을 85
 
1.4%
한 84
 
1.4%
Other values (469) 5068
81.9%
Han
ValueCountFrequency (%)
山 5
 
2.8%
君 4
 
2.3%
花 3
 
1.7%
形 3
 
1.7%
衙 3
 
1.7%
佛 2
 
1.1%
宗 2
 
1.1%
金 2
 
1.1%
氏 2
 
1.1%
韓 2
 
1.1%
Other values (127) 148
84.1%
Common
ValueCountFrequency (%)
1819
72.3%
1 90
 
3.6%
) 79
 
3.1%
( 77
 
3.1%
, 56
 
2.2%
9 44
 
1.7%
6 36
 
1.4%
2 36
 
1.4%
0 33
 
1.3%
3 32
 
1.3%
Other values (19) 213
 
8.5%
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 6189
69.6%
ASCII 2502
28.1%
CJK 167
 
1.9%
None 16
 
0.2%
Punctuation 10
 
0.1%
CJK Compat Ideographs 9
 
0.1%
CJK Compat 3
 
< 0.1%
Math Operators 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1819
72.7%
1 90
 
3.6%
) 79
 
3.2%
( 77
 
3.1%
, 56
 
2.2%
9 44
 
1.8%
6 36
 
1.4%
2 36
 
1.4%
0 33
 
1.3%
3 32
 
1.3%
Other values (22) 200
 
8.0%
Hangul
ValueCountFrequency (%)
의 176
 
2.8%
에 135
 
2.2%
이 132
 
2.1%
기 126
 
2.0%
조 111
 
1.8%
로 97
 
1.6%
사 89
 
1.4%
는 86
 
1.4%
을 85
 
1.4%
한 84
 
1.4%
Other values (469) 5068
81.9%
None
ValueCountFrequency (%)
· 8
50.0%
『 2
 
12.5%
』 2
 
12.5%
「 2
 
12.5%
」 2
 
12.5%
Punctuation
ValueCountFrequency (%)
‘ 5
50.0%
’ 5
50.0%
CJK
ValueCountFrequency (%)
山 5
 
3.0%
君 4
 
2.4%
花 3
 
1.8%
形 3
 
1.8%
衙 3
 
1.8%
佛 2
 
1.2%
宗 2
 
1.2%
氏 2
 
1.2%
韓 2
 
1.2%
寺 2
 
1.2%
Other values (120) 139
83.2%
CJK Compat
ValueCountFrequency (%)
㎡ 3
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
金 2
22.2%
李 2
22.2%
弄 1
11.1%
柳 1
11.1%
麟 1
11.1%
靈 1
11.1%
禮 1
11.1%
Math Operators
ValueCountFrequency (%)
∼ 2
100.0%

hompage
Categorical

Distinct31
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
190 
http://www.heritage.go.kr/heri/idx/index.do
122 
http://www.gijang.go.kr/tour/index.gijang
60 
www.cha.go.kr
53 
http://www.yeongdo.go.kr/tour.web
22 
Other values (26)
92 

Length

Max length153
Median length56
Mean length24.617811
Min length1

Unique

Unique12 ?
Unique (%)2.2%

Sample

1st rowhttp://www.saha.go.kr/tour/contents.do?mId=0301020000
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 190
35.3%
http://www.heritage.go.kr/heri/idx/index.do 122
22.6%
http://www.gijang.go.kr/tour/index.gijang 60
 
11.1%
www.cha.go.kr 53
 
9.8%
http://www.yeongdo.go.kr/tour.web 22
 
4.1%
해당없음 18
 
3.3%
- 16
 
3.0%
http://www.sasang.go.kr 7
 
1.3%
http://www.bsjunggu.go.kr/tour/index.junggu 6
 
1.1%
http://www.seon.or.kr/ 6
 
1.1%
Other values (21) 39
 
7.2%

Length

2024-04-17T07:16:15.516870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 190
35.3%
http://www.heritage.go.kr/heri/idx/index.do 122
22.6%
http://www.gijang.go.kr/tour/index.gijang 60
 
11.1%
www.cha.go.kr 53
 
9.8%
http://www.yeongdo.go.kr/tour.web 22
 
4.1%
해당없음 18
 
3.3%
16
 
3.0%
http://www.sasang.go.kr 7
 
1.3%
http://www.bsjunggu.go.kr/tour/index.junggu 6
 
1.1%
http://www.seon.or.kr 6
 
1.1%
Other values (21) 39
 
7.2%

area
Text

MISSING 

Distinct58
Distinct (%)46.0%
Missing413
Missing (%)76.6%
Memory size4.3 KiB
2024-04-17T07:16:15.710251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length14
Mean length5.5793651
Min length1

Characters and Unicode

Total characters703
Distinct characters35
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

Unique45 ?
Unique (%)35.7%

Sample

1st row3필지 1,322㎡
2nd row-
3rd row-
4th row0
5th row0
ValueCountFrequency (%)
0 27
 
16.9%
해당없음 16
 
10.0%
16
 
10.0%
3필지 4
 
2.5%
1필지 4
 
2.5%
4,023㎡ 3
 
1.9%
33필지 3
 
1.9%
66,068㎡ 3
 
1.9%
19,533 2
 
1.2%
1동 2
 
1.2%
Other values (71) 80
50.0%
2024-04-17T07:16:16.017313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 66
 
9.4%
㎡ 58
 
8.3%
, 52
 
7.4%
2 51
 
7.3%
3 48
 
6.8%
0 47
 
6.7%
4 39
 
5.5%
35
 
5.0%
8 32
 
4.6%
6 30
 
4.3%
Other values (25) 245
34.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 382
54.3%
Other Letter 130
 
18.5%
Other Punctuation 69
 
9.8%
Other Symbol 58
 
8.3%
Space Separator 35
 
5.0%
Dash Punctuation 20
 
2.8%
Lowercase Letter 4
 
0.6%
Open Punctuation 3
 
0.4%
Close Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 26
20.0%
필 25
19.2%
음 16
12.3%
없 16
12.3%
당 16
12.3%
해 16
12.3%
이 3
 
2.3%
높 2
 
1.5%
동 2
 
1.5%
길 1
 
0.8%
Other values (7) 7
 
5.4%
Decimal Number
ValueCountFrequency (%)
1 66
17.3%
2 51
13.4%
3 48
12.6%
0 47
12.3%
4 39
10.2%
8 32
8.4%
6 30
7.9%
5 27
7.1%
9 24
 
6.3%
7 18
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 52
75.4%
. 17
 
24.6%
Other Symbol
ValueCountFrequency (%)
㎡ 58
100.0%
Space Separator
ValueCountFrequency (%)
35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 569
80.9%
Hangul 130
 
18.5%
Latin 4
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 66
11.6%
㎡ 58
10.2%
, 52
9.1%
2 51
9.0%
3 48
8.4%
0 47
8.3%
4 39
 
6.9%
35
 
6.2%
8 32
 
5.6%
6 30
 
5.3%
Other values (7) 111
19.5%
Hangul
ValueCountFrequency (%)
지 26
20.0%
필 25
19.2%
음 16
12.3%
없 16
12.3%
당 16
12.3%
해 16
12.3%
이 3
 
2.3%
높 2
 
1.5%
동 2
 
1.5%
길 1
 
0.8%
Other values (7) 7
 
5.4%
Latin
ValueCountFrequency (%)
m 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 515
73.3%
Hangul 130
 
18.5%
CJK Compat 58
 
8.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 66
12.8%
, 52
10.1%
2 51
9.9%
3 48
9.3%
0 47
9.1%
4 39
7.6%
35
 
6.8%
8 32
 
6.2%
6 30
 
5.8%
5 27
 
5.2%
Other values (7) 88
17.1%
CJK Compat
ValueCountFrequency (%)
㎡ 58
100.0%
Hangul
ValueCountFrequency (%)
지 26
20.0%
필 25
19.2%
음 16
12.3%
없 16
12.3%
당 16
12.3%
해 16
12.3%
이 3
 
2.3%
높 2
 
1.5%
동 2
 
1.5%
길 1
 
0.8%
Other values (7) 7
 
5.4%

tel
Categorical

Distinct41
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
051-519-4092
122 
051-709-3971
60 
051-200-8493
57 
051-607-4067
53 
051-550-4081
43 
Other values (36)
204 

Length

Max length12
Median length12
Mean length11.599258
Min length4

Unique

Unique9 ?
Unique (%)1.7%

Sample

1st row051-220-4082
2nd row051-200-8493
3rd row051-244-2040
4th row051-200-8493
5th row051-200-8493

Common Values

ValueCountFrequency (%)
051-519-4092 122
22.6%
051-709-3971 60
11.1%
051-200-8493 57
10.6%
051-607-4067 53
9.8%
051-550-4081 43
 
8.0%
<NA> 27
 
5.0%
051-605-4065 20
 
3.7%
051-419-4065 18
 
3.3%
051-610-4067 18
 
3.3%
051-440-4064 16
 
3.0%
Other values (31) 105
19.5%

Length

2024-04-17T07:16:16.127879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-519-4092 122
22.6%
051-709-3971 60
11.1%
051-200-8493 57
10.6%
051-607-4067 53
9.8%
051-550-4081 43
 
8.0%
na 27
 
5.0%
051-605-4065 20
 
3.7%
051-419-4065 18
 
3.3%
051-610-4067 18
 
3.3%
051-970-4065 16
 
3.0%
Other values (31) 105
19.5%

gugun
Categorical

Distinct16
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
부산광역시 금정구
122 
부산광역시 서구
72 
부산광역시 기장군
60 
부산광역시 남구
53 
부산광역시 동래구
43 
Other values (11)
189 

Length

Max length10
Median length9
Mean length8.8218924
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 사하구
2nd row부산광역시 서구
3rd row부산광역시 서구
4th row부산광역시 서구
5th row부산광역시 서구

Common Values

ValueCountFrequency (%)
부산광역시 금정구 122
22.6%
부산광역시 서구 72
13.4%
부산광역시 기장군 60
11.1%
부산광역시 남구 53
9.8%
부산광역시 동래구 43
 
8.0%
부산광역시 해운대구 39
 
7.2%
부산광역시 연제구 33
 
6.1%
부산광역시 영도구 22
 
4.1%
부산광역시 부산진구 20
 
3.7%
부산광역시 수영구 18
 
3.3%
Other values (6) 57
10.6%

Length

2024-04-17T07:16:16.233567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산광역시 539
50.0%
금정구 122
 
11.3%
서구 72
 
6.7%
기장군 60
 
5.6%
남구 53
 
4.9%
동래구 43
 
4.0%
해운대구 39
 
3.6%
연제구 33
 
3.1%
영도구 22
 
2.0%
부산진구 20
 
1.9%
Other values (7) 75
 
7.0%

data_day
Date

Distinct8
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum2020-08-20 00:00:00
Maximum2021-01-15 00:00:00
2024-04-17T07:16:16.319548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:16:16.409084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)

lat
Text

Distinct196
Distinct (%)36.4%
Missing1
Missing (%)0.2%
Memory size4.3 KiB
2024-04-17T07:16:16.644206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length10.964684
Min length6

Characters and Unicode

Total characters5899
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique137 ?
Unique (%)25.5%

Sample

1st row35.039083
2nd row35.1043540124
3rd row35.0890167388
4th row35.1043540124
5th row35.10373802
ValueCountFrequency (%)
35.2830426366 82
 
15.2%
35.1043540124 56
 
10.4%
35.12957 24
 
4.5%
35.2322427972 18
 
3.3%
35.12957n 18
 
3.3%
35.374403 15
 
2.8%
35.163827 15
 
2.8%
35.1712117064 9
 
1.7%
35.0785634153 8
 
1.5%
35.085661 8
 
1.5%
Other values (186) 285
53.0%
2024-04-17T07:16:17.005404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 1058
17.9%
5 871
14.8%
2 669
11.3%
1 553
9.4%
. 538
9.1%
4 477
8.1%
6 454
7.7%
0 423
 
7.2%
7 304
 
5.2%
8 289
 
4.9%
Other values (2) 263
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5337
90.5%
Other Punctuation 538
 
9.1%
Uppercase Letter 24
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1058
19.8%
5 871
16.3%
2 669
12.5%
1 553
10.4%
4 477
8.9%
6 454
8.5%
0 423
 
7.9%
7 304
 
5.7%
8 289
 
5.4%
9 239
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 538
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5875
99.6%
Latin 24
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
3 1058
18.0%
5 871
14.8%
2 669
11.4%
1 553
9.4%
. 538
9.2%
4 477
8.1%
6 454
7.7%
0 423
 
7.2%
7 304
 
5.2%
8 289
 
4.9%
Latin
ValueCountFrequency (%)
N 24
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5899
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 1058
17.9%
5 871
14.8%
2 669
11.3%
1 553
9.4%
. 538
9.1%
4 477
8.1%
6 454
7.7%
0 423
 
7.2%
7 304
 
5.2%
8 289
 
4.9%
Other values (2) 263
 
4.5%

lng
Text

Distinct196
Distinct (%)36.4%
Missing1
Missing (%)0.2%
Memory size4.3 KiB
2024-04-17T07:16:17.270308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length11.953532
Min length7

Characters and Unicode

Total characters6431
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique137 ?
Unique (%)25.5%

Sample

1st row128.970978
2nd row129.0193362768
3rd row129.0211012230
4th row129.0193362768
5th row129.0194103
ValueCountFrequency (%)
129.0676207876 82
 
15.2%
129.0193362768 56
 
10.4%
129.09416 24
 
4.5%
129.0838244536 18
 
3.3%
129.09416e 18
 
3.3%
129.232923 15
 
2.8%
129.087579 15
 
2.8%
129.1139531446 9
 
1.7%
129.0802448645 8
 
1.5%
129.044144 8
 
1.5%
Other values (186) 285
53.0%
2024-04-17T07:16:17.637285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 958
14.9%
1 926
14.4%
9 894
13.9%
0 636
9.9%
6 608
9.5%
. 538
8.4%
7 487
7.6%
8 412
6.4%
3 392
6.1%
4 332
 
5.2%
Other values (2) 248
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5869
91.3%
Other Punctuation 538
 
8.4%
Uppercase Letter 24
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 958
16.3%
1 926
15.8%
9 894
15.2%
0 636
10.8%
6 608
10.4%
7 487
8.3%
8 412
7.0%
3 392
6.7%
4 332
 
5.7%
5 224
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 538
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6407
99.6%
Latin 24
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
2 958
15.0%
1 926
14.5%
9 894
14.0%
0 636
9.9%
6 608
9.5%
. 538
8.4%
7 487
7.6%
8 412
6.4%
3 392
6.1%
4 332
 
5.2%
Latin
ValueCountFrequency (%)
E 24
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6431
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 958
14.9%
1 926
14.4%
9 894
13.9%
0 636
9.9%
6 608
9.5%
. 538
8.4%
7 487
7.6%
8 412
6.4%
3 392
6.1%
4 332
 
5.2%
Other values (2) 248
 
3.9%

apr_at
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing30
Missing (%)5.6%
Memory size1.2 KiB
False
509 
(Missing)
 
30
ValueCountFrequency (%)
False 509
94.4%
(Missing) 30
 
5.6%
2024-04-17T07:16:17.730814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

last_load_dttm
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum2021-04-01 05:46:03
Maximum2021-04-01 05:46:03
2024-04-17T07:16:17.788716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:16:17.854625image/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
041253340000다대진동헌<NA>부산광역시 사하구 다대동 산144사하구시지정유형문화재 제1972-06-261825년유형문화재사하구1825년동헌은 조선시대 지방관서에서 첨사가 정무를 보던 건물로 아사(衙舍)·군아(郡衙)·현아(縣衙)·시사청(視事廳) 등으로 부르기도 하였고 다대진성 내에 있던 관아건물 중에서 유일한 건축유구(建築遺構)로 지금은 몰운대 내의 부산광역시 사하구 몰운대1길 73(다대동 산144)에 옮겨져 있다.부산광역시 지정 유형문화재 제3호(1972. 6. 26)로 지정될 당시 다대포 객사라는 이름이 사용되었다가 2020년 7월 부산시 문화재 위원회 심의에서 다대진 동헌http://www.saha.go.kr/tour/contents.do?mId=0301020000<NA>051-220-4082부산광역시 사하구2020-12-3135.039083128.970978N2021-04-01 05:46:03
138823260000청동북(靑銅金鼓)<NA>부산광역시 서구 부민동2가 1동아대학교제140호2014-03-19고려시대시지정유형문화재<NA><NA><NA><NA><NA>051-200-8493부산광역시 서구2020-12-3135.1043540124129.0193362768N2021-04-01 05:46:03
238833260000칠보사 목조관음보살좌상<NA>부산광역시 서구 남부민동 93-1칠보사제126호2013-05-081730년대시지정유형문화재<NA><NA><NA><NA><NA>051-244-2040부산광역시 서구2020-12-3135.0890167388129.0211012230N2021-04-01 05:46:03
338843260000흑유호 및 흑유정병<NA>부산광역시 서구 부민동2가 1동아대학교제101호2010-09-2012세기시지정유형문화재<NA><NA><NA><NA><NA>051-200-8493부산광역시 서구2020-12-3135.1043540124129.0193362768N2021-04-01 05:46:03
438853260000홍현주 필 산수도<NA>부산광역시 서구 부민동2가 2동아대학교제213호2020-07-2919세기시지정유형문화재<NA><NA><NA><NA><NA>051-200-8493부산광역시 서구2020-12-3135.10373802129.0194103N2021-04-01 05:46:03
539263300000송공단<NA>부산광역시 동래구 동래시장길 27(복천동)동래구청장제11호1972-06-26<NA>기념물<NA><NA><NA><NA>3필지 1,322㎡051-550-4081부산광역시 동래구2021-01-1535.204294129.08601N2021-04-01 05:46:03
639273300000동래지신밟기<NA>부산광역시 동래구 우장춘로 195-46(온천동)부산민속예술보존협회제4호1977-11-13<NA>무형문화재<NA><NA><NA><NA><NA>051-550-4081부산광역시 동래구2021-01-1535.222579129.07539N2021-04-01 05:46:03
739283300000충렬사제향<NA>부산광역시 동래구 충렬대로 345(충렬사)(재)충렬사 안락서원제5호1979-02-02<NA>무형문화재<NA><NA><NA><NA><NA>051-550-4081부산광역시 동래구2021-01-1535.419956129.095995N2021-04-01 05:46:03
840103280000해련사 장업의식구<NA>부산광역시 영도구 벚꽃길 117, (청학동)해련사시지정 민속문화재2015-08-26조선후기공예<NA>조선후기불교 목공예품http://www.yeongdo.go.kr/tour.web<NA>051-419-4065부산광역시 영도구2020-12-3135.0836023165129.0572054072N2021-04-01 05:46:03
940253360000생곡동 가달고분군<NA>부산광역시 강서구 생곡동 산93-1부산광역시 강서구청부산광역시지정기념물1996-05-25삼국시대부산광역시지정 문화재-----051-970-4065부산광역시 강서구2020-12-3135.136092128.875891N2021-04-01 05:46:03
skeyinstt_codecult_herit_nmroad_addraddrorgan_managenumberdateserakindmain_agentinstalled_yearmajor_contentshompageareatelgugundata_daylatlngapr_atlast_load_dttm
52941693380000옥련선원 마애지장보살좌상<NA>부산광역시 수영구 광남로257번길 58옥련선원市지정 제7호2001-05-16조선시대문화재 자료해당없음해당없음돌에 그린 부처의 그림해당없음해당없음051-610-4067부산광역시 수영구2020-12-3135.1613694042129.1265849144N2021-04-01 05:46:03
53041703380000고려 십육나한도(제7 가리가존자)<NA>부산광역시 수영구 남천동개인보물 제1882-12016-01-07고려시대보물해당없음해당없음석가모니 제자를 그린 그림해당없음해당없음051-610-4067부산광역시 수영구2020-12-3135.1427566803129.1103763659N2021-04-01 05:46:03
53141713380000정과정유적지<NA>부산광역시 수영구 망미동 산6-2번지 일원부산광역시 수영구청市지정 제54호2003-05-06고려시대기념물해당없음해당없음정서의 정과정곡 유래된 곳해당없음해당없음051-610-4067부산광역시 수영구2020-12-3135.1817057227129.1153849072N2021-04-01 05:46:03
53241723380000수영농청놀이<NA>부산광역시 수영구 수영성로 43부산광역시 수영구청市지정 제2호1972-02-18조선시대무형문화재해당없음해당없음어민의 민속놀이해당없음해당없음051-610-4067부산광역시 수영구2020-12-3135.1712117064129.1139531446N2021-04-01 05:46:03
53341733380000선화<NA>부산광역시 수영구 수영로521번길 63부산광역시 수영구청市지정 제19호2013-05-13현대무형문화재해당없음해당없음불교의 수행내용을 그림으로 표현해당없음해당없음051-610-4067부산광역시 수영구2020-12-3135.1526164463129.1057390774N2021-04-01 05:46:03
53441743380000수영야류<NA>부산광역시 수영구 수영성로 43부산광역시 수영구청국가지정 제43호1971-02-24조선시대무형문화재해당없음해당없음양반을 비하한 민속극해당없음해당없음051-610-4067부산광역시 수영구2020-12-3135.1712117064129.1139531446N2021-04-01 05:46:03
53541753380000좌수영어방놀이<NA>부산광역시 수영구 수영성로 43부산광역시 수영구청국가지정 제62호1978-05-09조선시대무형문화재해당없음해당없음수군과 어민의 합동 민속놀이해당없음해당없음051-610-4067부산광역시 수영구2020-12-3135.1712117064129.1139531446N2021-04-01 05:46:03
53641763380000부산 좌수영성지 곰솔<NA>부산광역시 수영구 수영성로 43부산광역시 수영구청국가지정 제270호1982-11-09조선시대천연기념물해당없음약400년전 추정천연기념물(수목)해당없음높이 22m051-610-4067부산광역시 수영구2020-12-3135.1712117064129.1139531446N2021-04-01 05:46:03
53741773380000부산 좌수영성지 푸조나무<NA>부산광역시 수영구 수영성로 43부산광역시 수영구청국가지정 제311호1982-11-09조선시대천연기념물해당없음약500년전 추정천연기념물(수목)해당없음높이 17.2m051-610-4067부산광역시 수영구2020-12-3135.1712117064129.1139531446N2021-04-01 05:46:03
5384178338000025의용단<NA>부산광역시 수영구 수영성로 43부산광역시 수영구청市지정 제12호1972-06-26조선시대기념물해당없음해당없음임진왜란 당시 수영성민 25인의 위패를 모신 곳해당없음해당없음051-610-4067부산광역시 수영구2020-12-3135.1712117064129.1139531446N2021-04-01 05:46:03