Overview

Dataset statistics

Number of variables19
Number of observations10000
Missing cells18294
Missing cells (%)9.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 MiB
Average record size in memory165.0 B

Variable types

Numeric4
Categorical8
Text6
DateTime1

Dataset

Description전라남도 관광자원 드론사진 파일 데이터는 전남관광재단(http://www.namdoskyview.or.kr/openapi) 홈페이지에서 관리되는 전라남도 관광/랜드마크/축제 자원 데이터를, 전남관광재단에서 운영하는 데이터 클라우드 서버 에서 고화질 항공사진을 다운로드 할 수 있는 다운로드 URL 제공
Author재단법인전라남도관광재단
URLhttps://www.data.go.kr/data/15098247/fileData.do

Alerts

분류1 has constant value ""Constant
추천 has constant value ""Constant
전화 has constant value ""Constant
홈페이지 has constant value ""Constant
시군명 is highly overall correlated with No and 1 other fieldsHigh correlation
코드 is highly overall correlated with No and 1 other fieldsHigh correlation
No is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
대분류코드 is highly overall correlated with 분류2High correlation
분류2 is highly overall correlated with 대분류코드 and 1 other fieldsHigh correlation
주차장 is highly overall correlated with 분류2High correlation
소분류 has 7548 (75.5%) missing valuesMissing
소분류코드 has 7316 (73.2%) missing valuesMissing
키워드 has 770 (7.7%) missing valuesMissing
주소 has 2620 (26.2%) missing valuesMissing
No has unique valuesUnique
대분류코드 has 1292 (12.9%) zerosZeros

Reproduction

Analysis started2023-12-12 03:16:47.944720
Analysis finished2023-12-12 03:16:53.995321
Duration6.05 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

No
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10306.982
Minimum3
Maximum20658
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:16:54.108176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile1073.75
Q15175.75
median10289
Q315442.25
95-th percentile19635.05
Maximum20658
Range20655
Interquartile range (IQR)10266.5

Descriptive statistics

Standard deviation5962.4383
Coefficient of variation (CV)0.57848535
Kurtosis-1.1995877
Mean10306.982
Median Absolute Deviation (MAD)5135.5
Skewness0.0067884615
Sum1.0306982 × 108
Variance35550670
MonotonicityNot monotonic
2023-12-12T12:16:54.340835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16118 1
 
< 0.1%
13965 1
 
< 0.1%
16036 1
 
< 0.1%
10328 1
 
< 0.1%
14969 1
 
< 0.1%
11724 1
 
< 0.1%
3809 1
 
< 0.1%
6283 1
 
< 0.1%
18275 1
 
< 0.1%
16599 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
3 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
15 1
< 0.1%
16 1
< 0.1%
17 1
< 0.1%
19 1
< 0.1%
21 1
< 0.1%
ValueCountFrequency (%)
20658 1
< 0.1%
20656 1
< 0.1%
20654 1
< 0.1%
20653 1
< 0.1%
20650 1
< 0.1%
20649 1
< 0.1%
20648 1
< 0.1%
20647 1
< 0.1%
20645 1
< 0.1%
20638 1
< 0.1%

시군명
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
목포시
2787 
신안군
1147 
해남군
865 
무안군
770 
나주시
687 
Other values (17)
3744 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row완도군
2nd row신안군
3rd row광양시
4th row목포시
5th row나주시

Common Values

ValueCountFrequency (%)
목포시 2787
27.9%
신안군 1147
11.5%
해남군 865
 
8.6%
무안군 770
 
7.7%
나주시 687
 
6.9%
진도군 499
 
5.0%
영암군 446
 
4.5%
강진군 418
 
4.2%
순천시 387
 
3.9%
장흥군 275
 
2.8%
Other values (12) 1719
17.2%

Length

2023-12-12T12:16:54.515080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
목포시 2787
27.9%
신안군 1147
11.5%
해남군 865
 
8.6%
무안군 770
 
7.7%
나주시 687
 
6.9%
진도군 499
 
5.0%
영암군 446
 
4.5%
강진군 418
 
4.2%
순천시 387
 
3.9%
장흥군 275
 
2.8%
Other values (12) 1719
17.2%

코드
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Mokpo_si
2787 
Shinan_gun
1147 
Haenam_gun
865 
Muan_gun
770 
Naju_si
687 
Other values (17)
3744 

Length

Max length14
Median length13
Mean length9.3994
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWando_gun
2nd rowShinan_gun
3rd rowGwangyang_si
4th rowMokpo_si
5th rowNaju_si

Common Values

ValueCountFrequency (%)
Mokpo_si 2787
27.9%
Shinan_gun 1147
11.5%
Haenam_gun 865
 
8.6%
Muan_gun 770
 
7.7%
Naju_si 687
 
6.9%
Jindo_gun 499
 
5.0%
Yeongam_gun 446
 
4.5%
Gangjin_gun 418
 
4.2%
Suncheon_si 387
 
3.9%
Jangheung_gun 275
 
2.8%
Other values (12) 1719
17.2%

Length

2023-12-12T12:16:54.706110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
mokpo_si 2787
27.9%
shinan_gun 1147
11.5%
haenam_gun 865
 
8.6%
muan_gun 770
 
7.7%
naju_si 687
 
6.9%
jindo_gun 499
 
5.0%
yeongam_gun 446
 
4.5%
gangjin_gun 418
 
4.2%
suncheon_si 387
 
3.9%
jangheung_gun 275
 
2.8%
Other values (12) 1719
17.2%

대분류
Text

Distinct350
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:16:55.187154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length5.0952
Min length2

Characters and Unicode

Total characters50952
Distinct characters332
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

Unique3 ?
Unique (%)< 0.1%

Sample

1st row고금 충무사
2nd row자은도
3rd row광양항 컨테이너부두
4th row축제목포
5th row나주시
ValueCountFrequency (%)
동별 694
 
6.2%
목포시 545
 
4.9%
유달산 306
 
2.7%
축제 284
 
2.5%
해남평야 271
 
2.4%
대교 243
 
2.2%
나주시 219
 
2.0%
목포 192
 
1.7%
전남도청 184
 
1.7%
해상케이블카 166
 
1.5%
Other values (354) 8043
72.2%
2023-12-12T12:16:55.876593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 2007
 
3.9%
_ 1729
 
3.4%
남 1444
 
2.8%
대 1232
 
2.4%
전 1174
 
2.3%
1147
 
2.3%
포 1142
 
2.2%
장 1120
 
2.2%
목 1099
 
2.2%
산 1066
 
2.1%
Other values (322) 37792
74.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47278
92.8%
Connector Punctuation 1729
 
3.4%
Space Separator 1147
 
2.3%
Decimal Number 634
 
1.2%
Uppercase Letter 83
 
0.2%
Close Punctuation 34
 
0.1%
Open Punctuation 34
 
0.1%
Other Punctuation 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 2007
 
4.2%
남 1444
 
3.1%
대 1232
 
2.6%
전 1174
 
2.5%
포 1142
 
2.4%
장 1120
 
2.4%
목 1099
 
2.3%
산 1066
 
2.3%
동 898
 
1.9%
해 892
 
1.9%
Other values (311) 35204
74.5%
Decimal Number
ValueCountFrequency (%)
1 220
34.7%
0 208
32.8%
5 206
32.5%
Uppercase Letter
ValueCountFrequency (%)
C 33
39.8%
R 25
30.1%
P 25
30.1%
Connector Punctuation
ValueCountFrequency (%)
_ 1729
100.0%
Space Separator
ValueCountFrequency (%)
1147
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Other Punctuation
ValueCountFrequency (%)
, 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47278
92.8%
Common 3591
 
7.0%
Latin 83
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 2007
 
4.2%
남 1444
 
3.1%
대 1232
 
2.6%
전 1174
 
2.5%
포 1142
 
2.4%
장 1120
 
2.4%
목 1099
 
2.3%
산 1066
 
2.3%
동 898
 
1.9%
해 892
 
1.9%
Other values (311) 35204
74.5%
Common
ValueCountFrequency (%)
_ 1729
48.1%
1147
31.9%
1 220
 
6.1%
0 208
 
5.8%
5 206
 
5.7%
) 34
 
0.9%
( 34
 
0.9%
, 13
 
0.4%
Latin
ValueCountFrequency (%)
C 33
39.8%
R 25
30.1%
P 25
30.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47278
92.8%
ASCII 3674
 
7.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 2007
 
4.2%
남 1444
 
3.1%
대 1232
 
2.6%
전 1174
 
2.5%
포 1142
 
2.4%
장 1120
 
2.4%
목 1099
 
2.3%
산 1066
 
2.3%
동 898
 
1.9%
해 892
 
1.9%
Other values (311) 35204
74.5%
ASCII
ValueCountFrequency (%)
_ 1729
47.1%
1147
31.2%
1 220
 
6.0%
0 208
 
5.7%
5 206
 
5.6%
) 34
 
0.9%
( 34
 
0.9%
C 33
 
0.9%
R 25
 
0.7%
P 25
 
0.7%

대분류코드
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct86
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean119.8748
Minimum0
Maximum800
Zeros1292
Zeros (%)12.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:16:56.065073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median37
Q369
95-th percentile800
Maximum800
Range800
Interquartile range (IQR)60

Descriptive statistics

Standard deviation224.08773
Coefficient of variation (CV)1.8693481
Kurtosis4.1214941
Mean119.8748
Median Absolute Deviation (MAD)31
Skewness2.3710655
Sum1198748
Variance50215.31
MonotonicityNot monotonic
2023-12-12T12:16:56.232246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1292
 
12.9%
100 694
 
6.9%
800 694
 
6.9%
42 385
 
3.9%
19 322
 
3.2%
68 320
 
3.2%
200 262
 
2.6%
16 250
 
2.5%
700 243
 
2.4%
6 237
 
2.4%
Other values (76) 5301
53.0%
ValueCountFrequency (%)
0 1292
12.9%
1 188
 
1.9%
2 113
 
1.1%
3 167
 
1.7%
4 117
 
1.2%
5 42
 
0.4%
6 237
 
2.4%
7 173
 
1.7%
8 74
 
0.7%
9 150
 
1.5%
ValueCountFrequency (%)
800 694
6.9%
700 243
 
2.4%
500 92
 
0.9%
400 85
 
0.9%
300 206
 
2.1%
200 262
 
2.6%
100 694
6.9%
83 3
 
< 0.1%
80 11
 
0.1%
79 12
 
0.1%

중분류
Text

Distinct519
Distinct (%)5.2%
Missing20
Missing (%)0.2%
Memory size156.2 KiB
2023-12-12T12:16:56.574359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length5.0256513
Min length2

Characters and Unicode

Total characters50156
Distinct characters387
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

Unique6 ?
Unique (%)0.1%

Sample

1st row약산 묘당도
2nd row자은 풍력발전소 길
3rd row광양항 컨테이너부두
4th row국제파워보트대회
5th row풍경
ValueCountFrequency (%)
풍경 799
 
7.1%
유달산 278
 
2.5%
천사대교 225
 
2.0%
해남평야 223
 
2.0%
학교 168
 
1.5%
해남대흥사 158
 
1.4%
공공기관 153
 
1.4%
평화광장 148
 
1.3%
삼학도 141
 
1.3%
서산동 130
 
1.2%
Other values (541) 8809
78.4%
2023-12-12T12:16:57.111713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 2103
 
4.2%
대 1336
 
2.7%
해 1283
 
2.6%
1252
 
2.5%
산 1158
 
2.3%
경 1148
 
2.3%
남 1110
 
2.2%
장 1100
 
2.2%
풍 989
 
2.0%
사 922
 
1.8%
Other values (377) 37755
75.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47471
94.6%
Space Separator 1252
 
2.5%
Connector Punctuation 638
 
1.3%
Decimal Number 354
 
0.7%
Uppercase Letter 227
 
0.5%
Lowercase Letter 123
 
0.2%
Open Punctuation 28
 
0.1%
Close Punctuation 28
 
0.1%
Dash Punctuation 24
 
< 0.1%
Other Punctuation 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 2103
 
4.4%
대 1336
 
2.8%
해 1283
 
2.7%
산 1158
 
2.4%
경 1148
 
2.4%
남 1110
 
2.3%
장 1100
 
2.3%
풍 989
 
2.1%
사 922
 
1.9%
교 767
 
1.6%
Other values (350) 35555
74.9%
Uppercase Letter
ValueCountFrequency (%)
F 94
41.4%
P 42
18.5%
C 33
 
14.5%
R 25
 
11.0%
W 14
 
6.2%
Z 13
 
5.7%
S 3
 
1.3%
U 3
 
1.3%
Lowercase Letter
ValueCountFrequency (%)
o 40
32.5%
t 14
 
11.4%
a 14
 
11.4%
y 14
 
11.4%
i 14
 
11.4%
n 14
 
11.4%
m 13
 
10.6%
Decimal Number
ValueCountFrequency (%)
5 164
46.3%
1 122
34.5%
0 32
 
9.0%
2 13
 
3.7%
4 13
 
3.7%
3 10
 
2.8%
Space Separator
ValueCountFrequency (%)
1252
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 638
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47471
94.6%
Common 2335
 
4.7%
Latin 350
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 2103
 
4.4%
대 1336
 
2.8%
해 1283
 
2.7%
산 1158
 
2.4%
경 1148
 
2.4%
남 1110
 
2.3%
장 1100
 
2.3%
풍 989
 
2.1%
사 922
 
1.9%
교 767
 
1.6%
Other values (350) 35555
74.9%
Latin
ValueCountFrequency (%)
F 94
26.9%
P 42
12.0%
o 40
11.4%
C 33
 
9.4%
R 25
 
7.1%
t 14
 
4.0%
W 14
 
4.0%
a 14
 
4.0%
y 14
 
4.0%
i 14
 
4.0%
Other values (5) 46
13.1%
Common
ValueCountFrequency (%)
1252
53.6%
_ 638
27.3%
5 164
 
7.0%
1 122
 
5.2%
0 32
 
1.4%
( 28
 
1.2%
) 28
 
1.2%
- 24
 
1.0%
2 13
 
0.6%
4 13
 
0.6%
Other values (2) 21
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47471
94.6%
ASCII 2685
 
5.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 2103
 
4.4%
대 1336
 
2.8%
해 1283
 
2.7%
산 1158
 
2.4%
경 1148
 
2.4%
남 1110
 
2.3%
장 1100
 
2.3%
풍 989
 
2.1%
사 922
 
1.9%
교 767
 
1.6%
Other values (350) 35555
74.9%
ASCII
ValueCountFrequency (%)
1252
46.6%
_ 638
23.8%
5 164
 
6.1%
1 122
 
4.5%
F 94
 
3.5%
P 42
 
1.6%
o 40
 
1.5%
C 33
 
1.2%
0 32
 
1.2%
( 28
 
1.0%
Other values (17) 240
 
8.9%

중분류코드
Real number (ℝ)

Distinct24
Distinct (%)0.2%
Missing20
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean3.7452906
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:16:57.300025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile12
Maximum24
Range23
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.8970175
Coefficient of variation (CV)1.0405114
Kurtosis4.5317842
Mean3.7452906
Median Absolute Deviation (MAD)1
Skewness2.078459
Sum37378
Variance15.186745
MonotonicityNot monotonic
2023-12-12T12:16:57.445010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 3405
34.1%
2 2424
24.2%
3 834
 
8.3%
4 654
 
6.5%
5 525
 
5.2%
6 463
 
4.6%
10 339
 
3.4%
7 259
 
2.6%
9 202
 
2.0%
8 196
 
2.0%
Other values (14) 679
 
6.8%
ValueCountFrequency (%)
1 3405
34.1%
2 2424
24.2%
3 834
 
8.3%
4 654
 
6.5%
5 525
 
5.2%
6 463
 
4.6%
7 259
 
2.6%
8 196
 
2.0%
9 202
 
2.0%
10 339
 
3.4%
ValueCountFrequency (%)
24 1
 
< 0.1%
23 11
 
0.1%
22 13
 
0.1%
21 18
 
0.2%
20 37
0.4%
19 32
0.3%
18 46
0.5%
17 41
0.4%
16 58
0.6%
15 43
0.4%

소분류
Text

MISSING 

Distinct204
Distinct (%)8.3%
Missing7548
Missing (%)75.5%
Memory size156.2 KiB
2023-12-12T12:16:57.761252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length14
Mean length6.4653344
Min length2

Characters and Unicode

Total characters15853
Distinct characters250
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

Unique31 ?
Unique (%)1.3%

Sample

1st row나주_배꽃
2nd row목포경찰서
3rd row목포노을
4th row목포시석현동
5th row눈내린영광
ValueCountFrequency (%)
천사대교 197
 
6.4%
목포 93
 
3.0%
목포대학교 76
 
2.5%
해남군청 64
 
2.1%
개통식 63
 
2.0%
나주혁신도시 53
 
1.7%
해양경찰청 52
 
1.7%
진도군청 50
 
1.6%
서산동 50
 
1.6%
삼학도 49
 
1.6%
Other values (213) 2331
75.7%
2023-12-12T12:16:58.209263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
목 882
 
5.6%
포 881
 
5.6%
도 656
 
4.1%
626
 
3.9%
동 494
 
3.1%
대 473
 
3.0%
교 393
 
2.5%
해 315
 
2.0%
청 291
 
1.8%
군 290
 
1.8%
Other values (240) 10552
66.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14787
93.3%
Space Separator 626
 
3.9%
Decimal Number 131
 
0.8%
Connector Punctuation 102
 
0.6%
Open Punctuation 89
 
0.6%
Close Punctuation 89
 
0.6%
Dash Punctuation 29
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
목 882
 
6.0%
포 881
 
6.0%
도 656
 
4.4%
동 494
 
3.3%
대 473
 
3.2%
교 393
 
2.7%
해 315
 
2.1%
청 291
 
2.0%
군 290
 
2.0%
시 287
 
1.9%
Other values (225) 9825
66.4%
Decimal Number
ValueCountFrequency (%)
3 43
32.8%
9 17
 
13.0%
8 17
 
13.0%
4 15
 
11.5%
1 13
 
9.9%
0 12
 
9.2%
2 6
 
4.6%
5 4
 
3.1%
7 2
 
1.5%
6 2
 
1.5%
Space Separator
ValueCountFrequency (%)
626
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 102
100.0%
Open Punctuation
ValueCountFrequency (%)
( 89
100.0%
Close Punctuation
ValueCountFrequency (%)
) 89
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14787
93.3%
Common 1066
 
6.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
목 882
 
6.0%
포 881
 
6.0%
도 656
 
4.4%
동 494
 
3.3%
대 473
 
3.2%
교 393
 
2.7%
해 315
 
2.1%
청 291
 
2.0%
군 290
 
2.0%
시 287
 
1.9%
Other values (225) 9825
66.4%
Common
ValueCountFrequency (%)
626
58.7%
_ 102
 
9.6%
( 89
 
8.3%
) 89
 
8.3%
3 43
 
4.0%
- 29
 
2.7%
9 17
 
1.6%
8 17
 
1.6%
4 15
 
1.4%
1 13
 
1.2%
Other values (5) 26
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14787
93.3%
ASCII 1066
 
6.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
목 882
 
6.0%
포 881
 
6.0%
도 656
 
4.4%
동 494
 
3.3%
대 473
 
3.2%
교 393
 
2.7%
해 315
 
2.1%
청 291
 
2.0%
군 290
 
2.0%
시 287
 
1.9%
Other values (225) 9825
66.4%
ASCII
ValueCountFrequency (%)
626
58.7%
_ 102
 
9.6%
( 89
 
8.3%
) 89
 
8.3%
3 43
 
4.0%
- 29
 
2.7%
9 17
 
1.6%
8 17
 
1.6%
4 15
 
1.4%
1 13
 
1.2%
Other values (5) 26
 
2.4%

소분류코드
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)0.9%
Missing7316
Missing (%)73.2%
Infinite0
Infinite (%)0.0%
Mean5.0935171
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:16:58.327553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q37
95-th percentile15
Maximum24
Range23
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.7837129
Coefficient of variation (CV)0.93917675
Kurtosis2.7082105
Mean5.0935171
Median Absolute Deviation (MAD)3
Skewness1.6724687
Sum13671
Variance22.883909
MonotonicityNot monotonic
2023-12-12T12:16:58.452363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 652
 
6.5%
2 401
 
4.0%
3 275
 
2.8%
4 273
 
2.7%
5 221
 
2.2%
6 160
 
1.6%
7 142
 
1.4%
8 72
 
0.7%
10 69
 
0.7%
9 56
 
0.6%
Other values (13) 363
 
3.6%
(Missing) 7316
73.2%
ValueCountFrequency (%)
1 652
6.5%
2 401
4.0%
3 275
2.8%
4 273
2.7%
5 221
 
2.2%
6 160
 
1.6%
7 142
 
1.4%
8 72
 
0.7%
9 56
 
0.6%
10 69
 
0.7%
ValueCountFrequency (%)
24 19
 
0.2%
23 14
 
0.1%
21 14
 
0.1%
20 10
 
0.1%
19 9
 
0.1%
18 19
 
0.2%
17 17
 
0.2%
16 14
 
0.1%
15 35
0.4%
14 53
0.5%

촬영일자
Date

Distinct606
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2014-06-17 00:00:00
Maximum2021-11-29 00:00:00
2023-12-12T12:16:58.594980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:16:58.778417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

분류1
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
photo
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
photo 10000
100.0%

Length

2023-12-12T12:16:58.933414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:16:59.024130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
photo 10000
100.0%

분류2
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
관광지
3423 
랜드마크
3405 
기타
2351 
축제
694 
<NA>
 
94

Length

Max length5
Median length4
Mean length3.052
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row랜드마크
2nd row랜드마크
3rd row랜드마크
4th row축제
5th row기타

Common Values

ValueCountFrequency (%)
관광지 3423
34.2%
랜드마크 3405
34.1%
기타 2351
23.5%
축제 694
 
6.9%
<NA> 94
 
0.9%
전통5일장 33
 
0.3%

Length

2023-12-12T12:16:59.134166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:16:59.338016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광지 3423
34.2%
랜드마크 3405
34.1%
기타 2351
23.5%
축제 694
 
6.9%
na 94
 
0.9%
전통5일장 33
 
0.3%

키워드
Text

MISSING 

Distinct500
Distinct (%)5.4%
Missing770
Missing (%)7.7%
Memory size156.2 KiB
2023-12-12T12:16:59.623385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length10.593716
Min length3

Characters and Unicode

Total characters97780
Distinct characters383
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)0.1%

Sample

1st row완도군,고금충무사,약산묘당도,이충무공유적
2nd row신안군,자은도,풍력발전소
3rd row광양시,광양항 컨테이너부두
4th row목포시,국제파워보트대회
5th row나주시,배꽃
ValueCountFrequency (%)
해남군,해남평야 271
 
2.7%
목포시,유달산 216
 
2.2%
목포시 185
 
1.9%
목포시,해상케이블카 166
 
1.7%
해남군,해남대흥사 158
 
1.6%
순천시,순천만국가정원,전남으뜸경관10선 149
 
1.5%
평화광장 141
 
1.4%
목포시,서산동 130
 
1.3%
목포시,삼학도 129
 
1.3%
목포시,용해동 124
 
1.3%
Other values (509) 8207
83.1%
2023-12-12T12:17:00.146440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 12236
 
12.5%
군 5178
 
5.3%
시 4321
 
4.4%
포 3505
 
3.6%
목 3478
 
3.6%
도 3185
 
3.3%
남 2485
 
2.5%
해 2093
 
2.1%
대 2033
 
2.1%
진 1644
 
1.7%
Other values (373) 57622
58.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 83422
85.3%
Other Punctuation 12236
 
12.5%
Decimal Number 1248
 
1.3%
Space Separator 646
 
0.7%
Uppercase Letter 182
 
0.2%
Connector Punctuation 46
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 5178
 
6.2%
시 4321
 
5.2%
포 3505
 
4.2%
목 3478
 
4.2%
도 3185
 
3.8%
남 2485
 
3.0%
해 2093
 
2.5%
대 2033
 
2.4%
진 1644
 
2.0%
장 1534
 
1.8%
Other values (359) 53966
64.7%
Uppercase Letter
ValueCountFrequency (%)
F 94
51.6%
C 29
 
15.9%
P 28
 
15.4%
R 25
 
13.7%
S 3
 
1.6%
U 3
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 595
47.7%
0 498
39.9%
5 132
 
10.6%
2 13
 
1.0%
3 10
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 12236
100.0%
Space Separator
ValueCountFrequency (%)
646
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 83422
85.3%
Common 14176
 
14.5%
Latin 182
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 5178
 
6.2%
시 4321
 
5.2%
포 3505
 
4.2%
목 3478
 
4.2%
도 3185
 
3.8%
남 2485
 
3.0%
해 2093
 
2.5%
대 2033
 
2.4%
진 1644
 
2.0%
장 1534
 
1.8%
Other values (359) 53966
64.7%
Common
ValueCountFrequency (%)
, 12236
86.3%
646
 
4.6%
1 595
 
4.2%
0 498
 
3.5%
5 132
 
0.9%
_ 46
 
0.3%
2 13
 
0.1%
3 10
 
0.1%
Latin
ValueCountFrequency (%)
F 94
51.6%
C 29
 
15.9%
P 28
 
15.4%
R 25
 
13.7%
S 3
 
1.6%
U 3
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 83422
85.3%
ASCII 14358
 
14.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 12236
85.2%
646
 
4.5%
1 595
 
4.1%
0 498
 
3.5%
5 132
 
0.9%
F 94
 
0.7%
_ 46
 
0.3%
C 29
 
0.2%
P 28
 
0.2%
R 25
 
0.2%
Other values (4) 29
 
0.2%
Hangul
ValueCountFrequency (%)
군 5178
 
6.2%
시 4321
 
5.2%
포 3505
 
4.2%
목 3478
 
4.2%
도 3185
 
3.8%
남 2485
 
3.0%
해 2093
 
2.5%
대 2033
 
2.4%
진 1644
 
2.0%
장 1534
 
1.8%
Other values (359) 53966
64.7%

사진URL
Text

Distinct9989
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:17:00.605404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length91
Median length87
Mean length77.4997
Min length64

Characters and Unicode

Total characters774997
Distinct characters48
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9978 ?
Unique (%)99.8%

Sample

1st rowhttp://open.namdogeo.com:9090/Wando_gun/5/5_01_20170530/Photo/photo4.JPG
2nd rowhttp://open.namdogeo.com:9090/Shinan_gun/69/69_04_20210309/Photo/photo2.JPG
3rd rowhttp://open.namdogeo.com:9090/Gwangyang_si/13/13_01_20160512/Photo/photo17.JPG
4th rowhttp://open.namdogeo.com:9090/Mokpo_si/100/100_05_20170910/Photo/photo14.JPG
5th rowhttp://open.namdogeo.com:9090/Naju_si/0/0_02/0_02_06_20190417/Photo/photo21.JPG
ValueCountFrequency (%)
http://open.namdogeo.com:9090/mokpo_si/0/0_05/0_05_16_20181023/photo/photo3.jpg 2
 
< 0.1%
http://open.namdogeo.com:9090/mokpo_si/0/0_05/0_05_16_20181023/photo/photo4.jpg 2
 
< 0.1%
http://open.namdogeo.com:9090/shinan_gun/100/100_16_20190920/photo/photo3.jpg 2
 
< 0.1%
http://open.namdogeo.com:9090/shinan_gun/100/100_16_20190920/photo/photo12.jpg 2
 
< 0.1%
http://open.namdogeo.com:9090/yeongam_gun/9/9_02_20170125/photo/photo1.jpg 2
 
< 0.1%
http://open.namdogeo.com:9090/shinan_gun/100/100_16_20190920/photo/photo11.jpg 2
 
< 0.1%
http://open.namdogeo.com:9090/shinan_gun/100/100_16_20190920/photo/photo6.jpg 2
 
< 0.1%
http://open.namdogeo.com:9090/shinan_gun/100/100_16_20190920/photo/photo14.jpg 2
 
< 0.1%
http://open.namdogeo.com:9090/shinan_gun/62/62_03_20200124/photo/photo2.jpeg 2
 
< 0.1%
http://open.namdogeo.com:9090/mokpo_si/16/16_02_20180226/photo/photo6.jpg 2
 
< 0.1%
Other values (9979) 9980
99.8%
2023-12-12T12:17:01.283883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 88304
 
11.4%
0 76862
 
9.9%
/ 72619
 
9.4%
t 39983
 
5.2%
_ 35256
 
4.5%
n 34769
 
4.5%
p 33586
 
4.3%
1 33233
 
4.3%
h 31946
 
4.1%
. 30000
 
3.9%
Other values (38) 298439
38.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 360613
46.5%
Decimal Number 211472
27.3%
Other Punctuation 122619
 
15.8%
Uppercase Letter 44938
 
5.8%
Connector Punctuation 35256
 
4.5%
Dash Punctuation 99
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 88304
24.5%
t 39983
11.1%
n 34769
 
9.6%
p 33586
 
9.3%
h 31946
 
8.9%
e 24570
 
6.8%
m 21564
 
6.0%
g 21130
 
5.9%
a 16762
 
4.6%
d 10733
 
3.0%
Other values (10) 37266
10.3%
Uppercase Letter
ValueCountFrequency (%)
P 19348
43.1%
G 8690
19.3%
J 8639
19.2%
M 3557
 
7.9%
S 1534
 
3.4%
H 1223
 
2.7%
Y 753
 
1.7%
N 687
 
1.5%
W 248
 
0.6%
B 179
 
0.4%
Other values (3) 80
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 76862
36.3%
1 33233
15.7%
2 28980
 
13.7%
9 26410
 
12.5%
8 8487
 
4.0%
4 8051
 
3.8%
6 7904
 
3.7%
3 7812
 
3.7%
7 7059
 
3.3%
5 6674
 
3.2%
Other Punctuation
ValueCountFrequency (%)
/ 72619
59.2%
. 30000
24.5%
: 20000
 
16.3%
Connector Punctuation
ValueCountFrequency (%)
_ 35256
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 405551
52.3%
Common 369446
47.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 88304
21.8%
t 39983
9.9%
n 34769
 
8.6%
p 33586
 
8.3%
h 31946
 
7.9%
e 24570
 
6.1%
m 21564
 
5.3%
g 21130
 
5.2%
P 19348
 
4.8%
a 16762
 
4.1%
Other values (23) 73589
18.1%
Common
ValueCountFrequency (%)
0 76862
20.8%
/ 72619
19.7%
_ 35256
9.5%
1 33233
9.0%
. 30000
 
8.1%
2 28980
 
7.8%
9 26410
 
7.1%
: 20000
 
5.4%
8 8487
 
2.3%
4 8051
 
2.2%
Other values (5) 29548
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 774997
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 88304
 
11.4%
0 76862
 
9.9%
/ 72619
 
9.4%
t 39983
 
5.2%
_ 35256
 
4.5%
n 34769
 
4.5%
p 33586
 
4.3%
1 33233
 
4.3%
h 31946
 
4.1%
. 30000
 
3.9%
Other values (38) 298439
38.5%

추천
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2023-12-12T12:17:01.479873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:17:01.981819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

주소
Text

MISSING 

Distinct338
Distinct (%)4.6%
Missing2620
Missing (%)26.2%
Memory size156.2 KiB
2023-12-12T12:17:02.457726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length25
Mean length18.085908
Min length8

Characters and Unicode

Total characters133474
Distinct characters242
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)0.2%

Sample

1st row전라남도 완도군 고금면 충무사길 86-31
2nd row전라남도 신안군 자은면
3rd row전라남도 광양시 항만대로 755
4th row전라남도 나주시
5th row전라남도 목포시 연산동
ValueCountFrequency (%)
전라남도 7143
 
22.4%
목포시 1516
 
4.8%
해남군 855
 
2.7%
무안군 702
 
2.2%
나주시 687
 
2.2%
신안군 562
 
1.8%
영암군 410
 
1.3%
순천시 387
 
1.2%
진도군 377
 
1.2%
강진군 344
 
1.1%
Other values (635) 18918
59.3%
2023-12-12T12:17:03.164239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24521
18.4%
도 9140
 
6.8%
남 8748
 
6.6%
전 7464
 
5.6%
라 7153
 
5.4%
군 4965
 
3.7%
1 3260
 
2.4%
면 2916
 
2.2%
길 2911
 
2.2%
시 2910
 
2.2%
Other values (232) 59486
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89285
66.9%
Space Separator 24521
 
18.4%
Decimal Number 18170
 
13.6%
Dash Punctuation 1468
 
1.1%
Open Punctuation 15
 
< 0.1%
Close Punctuation 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 9140
 
10.2%
남 8748
 
9.8%
전 7464
 
8.4%
라 7153
 
8.0%
군 4965
 
5.6%
면 2916
 
3.3%
길 2911
 
3.3%
시 2910
 
3.3%
로 2639
 
3.0%
안 1891
 
2.1%
Other values (218) 38548
43.2%
Decimal Number
ValueCountFrequency (%)
1 3260
17.9%
2 2725
15.0%
3 2088
11.5%
5 1874
10.3%
4 1851
10.2%
0 1651
9.1%
7 1444
7.9%
6 1224
 
6.7%
8 1221
 
6.7%
9 832
 
4.6%
Space Separator
ValueCountFrequency (%)
24521
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1468
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89285
66.9%
Common 44189
33.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 9140
 
10.2%
남 8748
 
9.8%
전 7464
 
8.4%
라 7153
 
8.0%
군 4965
 
5.6%
면 2916
 
3.3%
길 2911
 
3.3%
시 2910
 
3.3%
로 2639
 
3.0%
안 1891
 
2.1%
Other values (218) 38548
43.2%
Common
ValueCountFrequency (%)
24521
55.5%
1 3260
 
7.4%
2 2725
 
6.2%
3 2088
 
4.7%
5 1874
 
4.2%
4 1851
 
4.2%
0 1651
 
3.7%
- 1468
 
3.3%
7 1444
 
3.3%
6 1224
 
2.8%
Other values (4) 2083
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89285
66.9%
ASCII 44189
33.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24521
55.5%
1 3260
 
7.4%
2 2725
 
6.2%
3 2088
 
4.7%
5 1874
 
4.2%
4 1851
 
4.2%
0 1651
 
3.7%
- 1468
 
3.3%
7 1444
 
3.3%
6 1224
 
2.8%
Other values (4) 2083
 
4.7%
Hangul
ValueCountFrequency (%)
도 9140
 
10.2%
남 8748
 
9.8%
전 7464
 
8.4%
라 7153
 
8.0%
군 4965
 
5.6%
면 2916
 
3.3%
길 2911
 
3.3%
시 2910
 
3.3%
로 2639
 
3.0%
안 1891
 
2.1%
Other values (218) 38548
43.2%

주차장
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
O
5218 
X
4782 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowO
2nd rowX
3rd rowO
4th rowX
5th rowX

Common Values

ValueCountFrequency (%)
O 5218
52.2%
X 4782
47.8%

Length

2023-12-12T12:17:03.369961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:17:03.530691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 5218
52.2%
x 4782
47.8%

전화
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
X
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
X 10000
100.0%

Length

2023-12-12T12:17:03.676940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:17:03.791541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
x 10000
100.0%

홈페이지
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
X
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
X 10000
100.0%

Length

2023-12-12T12:17:03.936700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:17:04.077255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
x 10000
100.0%

Interactions

2023-12-12T12:16:52.172299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:16:50.316584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:16:50.935187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:16:51.585713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:16:52.339300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:16:50.438144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:16:51.072633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:16:51.739536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:16:52.488299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:16:50.629191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:16:51.256562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:16:51.911543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:16:52.954775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:16:50.775067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:16:51.405577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:16:52.044662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:17:04.179818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
No시군명코드대분류코드중분류코드소분류코드분류2주차장
No1.0000.9640.9640.6420.5830.6420.7110.578
시군명0.9641.0001.0000.7050.4560.4680.6600.546
코드0.9641.0001.0000.7050.4560.4680.6600.546
대분류코드0.6420.7050.7051.0000.4730.4780.7820.649
중분류코드0.5830.4560.4560.4731.0000.3060.3290.213
소분류코드0.6420.4680.4680.4780.3061.0000.4620.489
분류20.7110.6600.6600.7820.3290.4621.0000.440
주차장0.5780.5460.5460.6490.2130.4890.4401.000
2023-12-12T12:17:04.366842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명분류2주차장코드
시군명1.0000.4000.4351.000
분류20.4001.0000.5350.400
주차장0.4350.5351.0000.435
코드1.0000.4000.4351.000
2023-12-12T12:17:04.502035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
No대분류코드중분류코드소분류코드시군명코드분류2주차장
No1.0000.210-0.103-0.3350.8140.8140.3730.446
대분류코드0.2101.0000.081-0.0750.3800.3800.6350.495
중분류코드-0.1030.0811.0000.1600.1870.1870.1430.163
소분류코드-0.335-0.0750.1601.0000.1920.1920.3130.376
시군명0.8140.3800.1870.1921.0001.0000.4000.435
코드0.8140.3800.1870.1921.0001.0000.4000.435
분류20.3730.6350.1430.3130.4000.4001.0000.535
주차장0.4460.4950.1630.3760.4350.4350.5351.000

Missing values

2023-12-12T12:16:53.184760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:16:53.568206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T12:16:53.847950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

No시군명코드대분류대분류코드중분류중분류코드소분류소분류코드촬영일자분류1분류2키워드사진URL추천주소주차장전화홈페이지
1579516118완도군Wando_gun고금 충무사5약산 묘당도1<NA><NA>2017-05-30photo랜드마크완도군,고금충무사,약산묘당도,이충무공유적http://open.namdogeo.com:9090/Wando_gun/5/5_01_20170530/Photo/photo4.JPG0전라남도 완도군 고금면 충무사길 86-31OXX
1262212808신안군Shinan_gun자은도69자은 풍력발전소 길4<NA><NA>2021-03-09photo랜드마크신안군,자은도,풍력발전소http://open.namdogeo.com:9090/Shinan_gun/69/69_04_20210309/Photo/photo2.JPG0전라남도 신안군 자은면XXX
13651408광양시Gwangyang_si광양항 컨테이너부두13광양항 컨테이너부두1<NA><NA>2016-05-12photo랜드마크광양시,광양항 컨테이너부두http://open.namdogeo.com:9090/Gwangyang_si/13/13_01_20160512/Photo/photo17.JPG0전라남도 광양시 항만대로 755OXX
74677622목포시Mokpo_si축제목포100국제파워보트대회5<NA><NA>2017-09-10photo축제목포시,국제파워보트대회http://open.namdogeo.com:9090/Mokpo_si/100/100_05_20170910/Photo/photo14.JPG0<NA>XXX
19882031나주시Naju_si나주시0풍경2나주_배꽃62019-04-17photo기타나주시,배꽃http://open.namdogeo.com:9090/Naju_si/0/0_02/0_02_06_20190417/Photo/photo21.JPG0전라남도 나주시XXX
68136926목포시Mokpo_si전남대교압해대교58압해대교노을3<NA><NA>2021-09-18photo관광지목포시,전남대교,압해대교http://open.namdogeo.com:9090/Mokpo_si/58/58_03_20210918/Photo/photo4.jpeg0전라남도 목포시 연산동OXX
1653916867장흥군Jangheung_gun축제_장흥100장흥물축제1<NA>52019-07-28photo축제장흥군,장흥물축제http://open.namdogeo.com:9090/Jangheung_gun/100/100_01_05_20190728/Photo/photo11.JPG0<NA>XXX
774817강진군Gangjin_gun가을들녘 강진200강진가을들녘2<NA><NA>2017-09-27photo기타강진군,으뜸경관,강진가을들녘http://open.namdogeo.com:9090/Gangjin_gun/200/200_02_20170929/Photo/photo49.JPG0<NA>XXX
29402983나주시Naju_si영산강둔치체육공원40영산강둔치체육공원1<NA><NA>2021-08-05photo기타나주시,영산강둔치체육공원http://open.namdogeo.com:9090/Naju_si/40/40_01_20210805/Photo/photo2.JPG0전라남도 나주시 삼영1길 9-42OXX
1678017108장흥군Jangheung_gun전라남도_전통_5일장_장흥300장흥5일장1<NA><NA>2014-11-08photo기타장흥군,장흥5일장http://open.namdogeo.com:9090/Jangheung_gun/300/300_01_20141108/Photo/Photo173.JPG0<NA>XXX
No시군명코드대분류대분류코드중분류중분류코드소분류소분류코드촬영일자분류1분류2키워드사진URL추천주소주차장전화홈페이지
73487502목포시Mokpo_si목포수협위판장65목포수협위판장경매풍경1<NA><NA>2015-10-28photo기타목포시,목포수협위판장http://open.namdogeo.com:9090/Mokpo_si/65/65_01_20151028/Photo/photo36.JPG0전라남도 목포시 고하대로 641-21OXX
52085321목포시Mokpo_si외달도41외달도1<NA><NA>2015-06-19photo관광지목포시,외달도http://open.namdogeo.com:9090/Mokpo_si/41/41_01_20150619/Photo/photo62.JPG0전라남도 목포시 외달도길 72XXX
79898174목포시Mokpo_si동별800삼학도3삼학도튤립62019-04-18photo기타목포시,삼학도http://open.namdogeo.com:9090/Mokpo_si/800/800_03/800_03_06_20190418/Photo/photo1.JPG0<NA>XXX
1322713413신안군Shinan_gun별도부속섬400반월도 박지도1반월도 박지도22019-08-30photo랜드마크신안군,반월도,박지도http://open.namdogeo.com:9090/Shinan_gun/400/400_01/400_01_02_20190830/Photo/photo1.JPG0<NA>XXX
84058590목포시Mokpo_si동별800만호동6목포만호동12019-01-21photo기타목포시,만호동http://open.namdogeo.com:9090/Mokpo_si/800/800_06/800_06_01_20190121/Photo/photo7.JPG0<NA>XXX
95089694무안군Muan_gun탄도4탄도2<NA><NA>2020-06-08photo관광지<NA>http://open.namdogeo.com:9090/Muan_gun/4/4_02_20200608/Photo/photo87.jpeg0전라남도 무안군 망운면 탄도길 12-22XXX
95639749무안군Muan_gun탄도4탄도2<NA><NA>2020-06-08photo관광지<NA>http://open.namdogeo.com:9090/Muan_gun/4/4_02_20200608/Photo/photo142.jpeg0전라남도 무안군 망운면 탄도길 12-22XXX
1876619122해남군Haenam_gun땅끝_송호해변28해남송호리해수욕장1<NA><NA>2021-07-19photo관광지해남군,송호리해수욕장http://open.namdogeo.com:9090/Haenam_gun/28/28_01_20210719/Photo/Photo30.JPG0전라남도 해남군 송지면 땅끝해안로 1827OXX
1811518471함평군Hampyeong_gun전라남도_전통_5일장_함평300함평전통5일장1<NA><NA>2014-06-17photo기타함평군,함평가을들녘http://open.namdogeo.com:9090/Hampyeong_gun/300/300_01_20140617/Photo/Helicam/G0083800.JPG0<NA>XXX
66076720목포시Mokpo_si고하도54고하도2<NA><NA>2019-02-12photo관광지목포시,고하도http://open.namdogeo.com:9090/Mokpo_si/54/54_02_20190212/Photo/photo1.JPG0전라남도 목포시 달동XXX