Overview

Dataset statistics

Number of variables11
Number of observations248
Missing cells331
Missing cells (%)12.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.2 KiB
Average record size in memory91.5 B

Variable types

Numeric2
Text4
Categorical3
Unsupported1
DateTime1

Alerts

region has constant value ""Constant
last_load_dttm has constant value ""Constant
insti_gubun is highly overall correlated with gubunHigh correlation
gubun is highly overall correlated with skey and 2 other fieldsHigh correlation
skey is highly overall correlated with reg_no and 1 other fieldsHigh correlation
reg_no is highly overall correlated with skey and 1 other fieldsHigh correlation
company_reg_no has 248 (100.0%) missing valuesMissing
target_country has 83 (33.5%) missing valuesMissing
skey has unique valuesUnique
reg_no has unique valuesUnique
company_reg_no is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-17 16:37:41.636197
Analysis finished2024-04-17 16:37:42.781242
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct248
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1459.5
Minimum1336
Maximum1583
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-18T01:37:42.838840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1336
5-th percentile1348.35
Q11397.75
median1459.5
Q31521.25
95-th percentile1570.65
Maximum1583
Range247
Interquartile range (IQR)123.5

Descriptive statistics

Standard deviation71.735626
Coefficient of variation (CV)0.049150823
Kurtosis-1.2
Mean1459.5
Median Absolute Deviation (MAD)62
Skewness0
Sum361956
Variance5146
MonotonicityNot monotonic
2024-04-18T01:37:42.941318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1559 1
 
0.4%
1389 1
 
0.4%
1376 1
 
0.4%
1377 1
 
0.4%
1378 1
 
0.4%
1379 1
 
0.4%
1380 1
 
0.4%
1381 1
 
0.4%
1382 1
 
0.4%
1383 1
 
0.4%
Other values (238) 238
96.0%
ValueCountFrequency (%)
1336 1
0.4%
1337 1
0.4%
1338 1
0.4%
1339 1
0.4%
1340 1
0.4%
1341 1
0.4%
1342 1
0.4%
1343 1
0.4%
1344 1
0.4%
1345 1
0.4%
ValueCountFrequency (%)
1583 1
0.4%
1582 1
0.4%
1581 1
0.4%
1580 1
0.4%
1579 1
0.4%
1578 1
0.4%
1577 1
0.4%
1576 1
0.4%
1575 1
0.4%
1574 1
0.4%

reg_no
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct248
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean124.5
Minimum1
Maximum248
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-18T01:37:43.048241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.35
Q162.75
median124.5
Q3186.25
95-th percentile235.65
Maximum248
Range247
Interquartile range (IQR)123.5

Descriptive statistics

Standard deviation71.735626
Coefficient of variation (CV)0.57618976
Kurtosis-1.2
Mean124.5
Median Absolute Deviation (MAD)62
Skewness0
Sum30876
Variance5146
MonotonicityNot monotonic
2024-04-18T01:37:43.154953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
224 1
 
0.4%
54 1
 
0.4%
41 1
 
0.4%
42 1
 
0.4%
43 1
 
0.4%
44 1
 
0.4%
45 1
 
0.4%
46 1
 
0.4%
47 1
 
0.4%
48 1
 
0.4%
Other values (238) 238
96.0%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
248 1
0.4%
247 1
0.4%
246 1
0.4%
245 1
0.4%
244 1
0.4%
243 1
0.4%
242 1
0.4%
241 1
0.4%
240 1
0.4%
239 1
0.4%

business_nm
Text

Distinct247
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-04-18T01:37:43.359833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length8.1975806
Min length3

Characters and Unicode

Total characters2033
Distinct characters326
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique246 ?
Unique (%)99.2%

Sample

1st row주식회사 메티스
2nd row㈜ 새부산관광투어
3rd row주식회사 금곡국제여행사
4th row세정글로벌 주식회사
5th row드림무역
ValueCountFrequency (%)
주식회사 30
 
9.0%
㈜ 13
 
3.9%
의원 3
 
0.9%
성형외과의원 2
 
0.6%
부민병원 2
 
0.6%
인제대학교 2
 
0.6%
굿윌치과병원 2
 
0.6%
의료법인 1
 
0.3%
청맥병원 1
 
0.3%
일신기독병원 1
 
0.3%
Other values (278) 278
83.0%
2024-04-18T01:37:43.671708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 151
 
7.4%
의 98
 
4.8%
88
 
4.3%
과 81
 
4.0%
병 55
 
2.7%
이 54
 
2.7%
스 47
 
2.3%
부 45
 
2.2%
사 44
 
2.2%
주 39
 
1.9%
Other values (316) 1331
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1764
86.8%
Space Separator 88
 
4.3%
Uppercase Letter 71
 
3.5%
Lowercase Letter 35
 
1.7%
Other Symbol 28
 
1.4%
Open Punctuation 18
 
0.9%
Close Punctuation 18
 
0.9%
Decimal Number 7
 
0.3%
Other Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 151
 
8.6%
의 98
 
5.6%
과 81
 
4.6%
병 55
 
3.1%
이 54
 
3.1%
스 47
 
2.7%
부 45
 
2.6%
사 44
 
2.5%
주 39
 
2.2%
회 38
 
2.2%
Other values (272) 1112
63.0%
Uppercase Letter
ValueCountFrequency (%)
S 8
11.3%
E 7
 
9.9%
B 6
 
8.5%
A 6
 
8.5%
N 5
 
7.0%
T 5
 
7.0%
M 5
 
7.0%
C 4
 
5.6%
I 4
 
5.6%
P 3
 
4.2%
Other values (10) 18
25.4%
Lowercase Letter
ValueCountFrequency (%)
e 5
14.3%
a 5
14.3%
i 4
11.4%
n 3
8.6%
s 3
8.6%
d 3
8.6%
v 2
 
5.7%
c 2
 
5.7%
t 2
 
5.7%
m 2
 
5.7%
Other values (4) 4
11.4%
Decimal Number
ValueCountFrequency (%)
3 2
28.6%
6 2
28.6%
5 2
28.6%
2 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
. 2
50.0%
Space Separator
ValueCountFrequency (%)
88
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1785
87.8%
Common 135
 
6.6%
Latin 106
 
5.2%
Han 7
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 151
 
8.5%
의 98
 
5.5%
과 81
 
4.5%
병 55
 
3.1%
이 54
 
3.0%
스 47
 
2.6%
부 45
 
2.5%
사 44
 
2.5%
주 39
 
2.2%
회 38
 
2.1%
Other values (266) 1133
63.5%
Latin
ValueCountFrequency (%)
S 8
 
7.5%
E 7
 
6.6%
B 6
 
5.7%
A 6
 
5.7%
e 5
 
4.7%
N 5
 
4.7%
a 5
 
4.7%
T 5
 
4.7%
M 5
 
4.7%
i 4
 
3.8%
Other values (24) 50
47.2%
Common
ValueCountFrequency (%)
88
65.2%
( 18
 
13.3%
) 18
 
13.3%
, 2
 
1.5%
. 2
 
1.5%
3 2
 
1.5%
6 2
 
1.5%
5 2
 
1.5%
2 1
 
0.7%
Han
ValueCountFrequency (%)
社 1
14.3%
會 1
14.3%
式 1
14.3%
株 1
14.3%
園 1
14.3%
盛 1
14.3%
韓 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1757
86.4%
ASCII 241
 
11.9%
None 28
 
1.4%
CJK 7
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 151
 
8.6%
의 98
 
5.6%
과 81
 
4.6%
병 55
 
3.1%
이 54
 
3.1%
스 47
 
2.7%
부 45
 
2.6%
사 44
 
2.5%
주 39
 
2.2%
회 38
 
2.2%
Other values (265) 1105
62.9%
ASCII
ValueCountFrequency (%)
88
36.5%
( 18
 
7.5%
) 18
 
7.5%
S 8
 
3.3%
E 7
 
2.9%
B 6
 
2.5%
A 6
 
2.5%
e 5
 
2.1%
N 5
 
2.1%
a 5
 
2.1%
Other values (33) 75
31.1%
None
ValueCountFrequency (%)
㈜ 28
100.0%
CJK
ValueCountFrequency (%)
社 1
14.3%
會 1
14.3%
式 1
14.3%
株 1
14.3%
園 1
14.3%
盛 1
14.3%
韓 1
14.3%

insti_gubun
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
88 
의원
73 
병원
26 
치과의원
19 
종합병원
14 
Other values (4)
28 

Length

Max length6
Median length4
Mean length3.1814516
Min length2

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> 88
35.5%
의원 73
29.4%
병원 26
 
10.5%
치과의원 19
 
7.7%
종합병원 14
 
5.6%
한의원 13
 
5.2%
치과병원 9
 
3.6%
상급종합병원 4
 
1.6%
한방병원 2
 
0.8%

Length

2024-04-18T01:37:43.797890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:37:43.920822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 88
35.5%
의원 73
29.4%
병원 26
 
10.5%
치과의원 19
 
7.7%
종합병원 14
 
5.6%
한의원 13
 
5.2%
치과병원 9
 
3.6%
상급종합병원 4
 
1.6%
한방병원 2
 
0.8%

region
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
부산
248 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산 248
100.0%

Length

2024-04-18T01:37:44.024244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:37:44.089124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산 248
100.0%

representative
Text

Distinct243
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-04-18T01:37:44.313892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length3
Mean length4.0241935
Min length2

Characters and Unicode

Total characters998
Distinct characters176
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

Unique238 ?
Unique (%)96.0%

Sample

1st row김춘웅
2nd row정판덕
3rd row이송아
4th row장연희
5th row장은숙
ValueCountFrequency (%)
1명 16
 
5.3%
외 14
 
4.6%
2명 3
 
1.0%
정선윤 2
 
0.7%
김영철 2
 
0.7%
elena 2
 
0.7%
김춘웅 2
 
0.7%
정흥태 2
 
0.7%
구영수 2
 
0.7%
이순형 2
 
0.7%
Other values (256) 256
84.5%
2024-04-18T01:37:44.678807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
57
 
5.7%
김 43
 
4.3%
이 41
 
4.1%
정 40
 
4.0%
A 29
 
2.9%
박 29
 
2.9%
명 26
 
2.6%
영 23
 
2.3%
N 22
 
2.2%
외 21
 
2.1%
Other values (166) 667
66.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 753
75.5%
Uppercase Letter 161
 
16.1%
Space Separator 57
 
5.7%
Decimal Number 21
 
2.1%
Open Punctuation 2
 
0.2%
Other Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 43
 
5.7%
이 41
 
5.4%
정 40
 
5.3%
박 29
 
3.9%
명 26
 
3.5%
영 23
 
3.1%
외 21
 
2.8%
성 18
 
2.4%
희 14
 
1.9%
진 12
 
1.6%
Other values (138) 486
64.5%
Uppercase Letter
ValueCountFrequency (%)
A 29
18.0%
N 22
13.7%
E 15
9.3%
I 12
 
7.5%
O 11
 
6.8%
L 10
 
6.2%
T 7
 
4.3%
V 6
 
3.7%
S 6
 
3.7%
K 6
 
3.7%
Other values (11) 37
23.0%
Decimal Number
ValueCountFrequency (%)
1 17
81.0%
2 3
 
14.3%
4 1
 
4.8%
Space Separator
ValueCountFrequency (%)
57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 753
75.5%
Latin 161
 
16.1%
Common 84
 
8.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 43
 
5.7%
이 41
 
5.4%
정 40
 
5.3%
박 29
 
3.9%
명 26
 
3.5%
영 23
 
3.1%
외 21
 
2.8%
성 18
 
2.4%
희 14
 
1.9%
진 12
 
1.6%
Other values (138) 486
64.5%
Latin
ValueCountFrequency (%)
A 29
18.0%
N 22
13.7%
E 15
9.3%
I 12
 
7.5%
O 11
 
6.8%
L 10
 
6.2%
T 7
 
4.3%
V 6
 
3.7%
S 6
 
3.7%
K 6
 
3.7%
Other values (11) 37
23.0%
Common
ValueCountFrequency (%)
57
67.9%
1 17
 
20.2%
2 3
 
3.6%
( 2
 
2.4%
, 2
 
2.4%
) 2
 
2.4%
4 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 753
75.5%
ASCII 245
 
24.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
57
23.3%
A 29
11.8%
N 22
 
9.0%
1 17
 
6.9%
E 15
 
6.1%
I 12
 
4.9%
O 11
 
4.5%
L 10
 
4.1%
T 7
 
2.9%
V 6
 
2.4%
Other values (18) 59
24.1%
Hangul
ValueCountFrequency (%)
김 43
 
5.7%
이 41
 
5.4%
정 40
 
5.3%
박 29
 
3.9%
명 26
 
3.5%
영 23
 
3.1%
외 21
 
2.8%
성 18
 
2.4%
희 14
 
1.9%
진 12
 
1.6%
Other values (138) 486
64.5%

company_reg_no
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing248
Missing (%)100.0%
Memory size2.3 KiB

addr
Text

Distinct247
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-04-18T01:37:44.925348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length49
Mean length35.657258
Min length22

Characters and Unicode

Total characters8843
Distinct characters293
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

Unique246 ?
Unique (%)99.2%

Sample

1st row부산광역시 수영구 망미번영로70번길 26(수영동)
2nd row부산광역시 연제구 고분로 5, 9층(연산동, 현우빌딩)
3rd row부산광역시 해운대구 해운대해변로 203, 7층 17호(우동, 오션타워)
4th row부산광역시 부산진구 황령대로 13, 705(범천동, 한라시그마타워)
5th row부산광역시 동구 홍곡로 50, 103동 1104호(초량동, e편한세상 부산항)
ValueCountFrequency (%)
부산광역시 232
 
15.8%
부산진구 74
 
5.0%
해운대구 62
 
4.2%
중앙대로 26
 
1.8%
동구 23
 
1.6%
가야대로 19
 
1.3%
서면로 19
 
1.3%
동래구 16
 
1.1%
부산 16
 
1.1%
해운대로 14
 
1.0%
Other values (665) 968
65.9%
2024-04-18T01:37:45.285632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1690
 
19.1%
부 410
 
4.6%
산 345
 
3.9%
동 317
 
3.6%
, 316
 
3.6%
1 290
 
3.3%
구 252
 
2.8%
( 248
 
2.8%
) 248
 
2.8%
로 247
 
2.8%
Other values (283) 4480
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4847
54.8%
Space Separator 1690
 
19.1%
Decimal Number 1406
 
15.9%
Other Punctuation 319
 
3.6%
Open Punctuation 248
 
2.8%
Close Punctuation 248
 
2.8%
Dash Punctuation 35
 
0.4%
Uppercase Letter 30
 
0.3%
Math Symbol 15
 
0.2%
Lowercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 410
 
8.5%
산 345
 
7.1%
동 317
 
6.5%
구 252
 
5.2%
로 247
 
5.1%
시 245
 
5.1%
광 239
 
4.9%
역 233
 
4.8%
대 203
 
4.2%
층 138
 
2.8%
Other values (246) 2218
45.8%
Uppercase Letter
ValueCountFrequency (%)
A 6
20.0%
F 4
13.3%
B 3
10.0%
C 3
10.0%
S 2
 
6.7%
K 2
 
6.7%
E 2
 
6.7%
V 1
 
3.3%
P 1
 
3.3%
W 1
 
3.3%
Other values (5) 5
16.7%
Decimal Number
ValueCountFrequency (%)
1 290
20.6%
0 188
13.4%
2 187
13.3%
4 143
10.2%
3 125
8.9%
7 114
 
8.1%
5 112
 
8.0%
6 98
 
7.0%
8 76
 
5.4%
9 73
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
l 2
40.0%
e 1
20.0%
s 1
20.0%
i 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 316
99.1%
. 2
 
0.6%
/ 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1690
100.0%
Open Punctuation
ValueCountFrequency (%)
( 248
100.0%
Close Punctuation
ValueCountFrequency (%)
) 248
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4847
54.8%
Common 3961
44.8%
Latin 35
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 410
 
8.5%
산 345
 
7.1%
동 317
 
6.5%
구 252
 
5.2%
로 247
 
5.1%
시 245
 
5.1%
광 239
 
4.9%
역 233
 
4.8%
대 203
 
4.2%
층 138
 
2.8%
Other values (246) 2218
45.8%
Latin
ValueCountFrequency (%)
A 6
17.1%
F 4
11.4%
B 3
 
8.6%
C 3
 
8.6%
S 2
 
5.7%
l 2
 
5.7%
K 2
 
5.7%
E 2
 
5.7%
V 1
 
2.9%
P 1
 
2.9%
Other values (9) 9
25.7%
Common
ValueCountFrequency (%)
1690
42.7%
, 316
 
8.0%
1 290
 
7.3%
( 248
 
6.3%
) 248
 
6.3%
0 188
 
4.7%
2 187
 
4.7%
4 143
 
3.6%
3 125
 
3.2%
7 114
 
2.9%
Other values (8) 412
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4847
54.8%
ASCII 3996
45.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1690
42.3%
, 316
 
7.9%
1 290
 
7.3%
( 248
 
6.2%
) 248
 
6.2%
0 188
 
4.7%
2 187
 
4.7%
4 143
 
3.6%
3 125
 
3.1%
7 114
 
2.9%
Other values (27) 447
 
11.2%
Hangul
ValueCountFrequency (%)
부 410
 
8.5%
산 345
 
7.1%
동 317
 
6.5%
구 252
 
5.2%
로 247
 
5.1%
시 245
 
5.1%
광 239
 
4.9%
역 233
 
4.8%
대 203
 
4.2%
층 138
 
2.8%
Other values (246) 2218
45.8%

target_country
Text

MISSING 

Distinct80
Distinct (%)48.5%
Missing83
Missing (%)33.5%
Memory size2.1 KiB
2024-04-18T01:37:45.480562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length23
Mean length10.454545
Min length1

Characters and Unicode

Total characters1725
Distinct characters59
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

Unique58 ?
Unique (%)35.2%

Sample

1st row러시아
2nd row중국/베트남/인도네시아,미얀마
3rd row중국
4th row몽골
5th row중국/러시아/카자르스탄
ValueCountFrequency (%)
러시아 34
14.0%
중국 34
14.0%
일본 23
 
9.5%
베트남 18
 
7.4%
몽골 15
 
6.2%
미국/일본/중국/러시아 8
 
3.3%
미국/일본/중국 8
 
3.3%
미국/일본/중국/몽골/러시아 7
 
2.9%
미국 6
 
2.5%
러시아(cis연합 6
 
2.5%
Other values (58) 84
34.6%
2024-04-18T01:37:45.784006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 234
13.6%
국 170
 
9.9%
아 122
 
7.1%
중 116
 
6.7%
시 113
 
6.6%
러 107
 
6.2%
일 95
 
5.5%
본 94
 
5.4%
78
 
4.5%
, 75
 
4.3%
Other values (49) 521
30.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1205
69.9%
Other Punctuation 309
 
17.9%
Space Separator 78
 
4.5%
Uppercase Letter 69
 
4.0%
Open Punctuation 31
 
1.8%
Close Punctuation 31
 
1.8%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 170
14.1%
아 122
10.1%
중 116
9.6%
시 113
9.4%
러 107
8.9%
일 95
7.9%
본 94
 
7.8%
미 67
 
5.6%
남 47
 
3.9%
베 37
 
3.1%
Other values (40) 237
19.7%
Uppercase Letter
ValueCountFrequency (%)
C 23
33.3%
I 23
33.3%
S 23
33.3%
Other Punctuation
ValueCountFrequency (%)
/ 234
75.7%
, 75
 
24.3%
Space Separator
ValueCountFrequency (%)
78
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1205
69.9%
Common 451
 
26.1%
Latin 69
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 170
14.1%
아 122
10.1%
중 116
9.6%
시 113
9.4%
러 107
8.9%
일 95
7.9%
본 94
 
7.8%
미 67
 
5.6%
남 47
 
3.9%
베 37
 
3.1%
Other values (40) 237
19.7%
Common
ValueCountFrequency (%)
/ 234
51.9%
78
 
17.3%
, 75
 
16.6%
( 31
 
6.9%
) 31
 
6.9%
- 2
 
0.4%
Latin
ValueCountFrequency (%)
C 23
33.3%
I 23
33.3%
S 23
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1205
69.9%
ASCII 520
30.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 234
45.0%
78
 
15.0%
, 75
 
14.4%
( 31
 
6.0%
) 31
 
6.0%
C 23
 
4.4%
I 23
 
4.4%
S 23
 
4.4%
- 2
 
0.4%
Hangul
ValueCountFrequency (%)
국 170
14.1%
아 122
10.1%
중 116
9.6%
시 113
9.4%
러 107
8.9%
일 95
7.9%
본 94
 
7.8%
미 67
 
5.6%
남 47
 
3.9%
베 37
 
3.1%
Other values (40) 237
19.7%

gubun
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
의료기관
160 
유치업자
88 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
의료기관 160
64.5%
유치업자 88
35.5%

Length

2024-04-18T01:37:45.882964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:37:45.951358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의료기관 160
64.5%
유치업자 88
35.5%

last_load_dttm
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2020-12-22 13:36:07
Maximum2020-12-22 13:36:07
2024-04-18T01:37:46.009404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:37:46.076086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-18T01:37:42.466071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:37:42.342333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:37:42.526148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:37:42.403025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-18T01:37:46.131579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
skeyreg_noinsti_gubuntarget_countrygubun
skey1.0001.0000.1300.8140.992
reg_no1.0001.0000.1300.8100.991
insti_gubun0.1300.1301.0000.000NaN
target_country0.8140.8100.0001.0000.851
gubun0.9920.991NaN0.8511.000
2024-04-18T01:37:46.208814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
insti_gubungubun
insti_gubun1.0001.000
gubun1.0001.000
2024-04-18T01:37:46.272627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
skeyreg_noinsti_gubungubun
skey1.0001.0000.0680.903
reg_no1.0001.0000.0680.903
insti_gubun0.0680.0681.0001.000
gubun0.9030.9031.0001.000

Missing values

2024-04-18T01:37:42.612996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T01:37:42.732986image/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.

Sample

skeyreg_nobusiness_nminsti_gubunregionrepresentativecompany_reg_noaddrtarget_countrygubunlast_load_dttm
01559224주식회사 메티스<NA>부산김춘웅<NA>부산광역시 수영구 망미번영로70번길 26(수영동)러시아유치업자2020-12-22 13:36:07
11560225㈜ 새부산관광투어<NA>부산정판덕<NA>부산광역시 연제구 고분로 5, 9층(연산동, 현우빌딩)중국/베트남/인도네시아,미얀마유치업자2020-12-22 13:36:07
21561226주식회사 금곡국제여행사<NA>부산이송아<NA>부산광역시 해운대구 해운대해변로 203, 7층 17호(우동, 오션타워)중국유치업자2020-12-22 13:36:07
31562227세정글로벌 주식회사<NA>부산장연희<NA>부산광역시 부산진구 황령대로 13, 705(범천동, 한라시그마타워)몽골유치업자2020-12-22 13:36:07
41563228드림무역<NA>부산장은숙<NA>부산광역시 동구 홍곡로 50, 103동 1104호(초량동, e편한세상 부산항)중국/러시아/카자르스탄유치업자2020-12-22 13:36:07
51564229주식회사 하나메디컬서비스<NA>부산노정범<NA>부산광역시 해운대구 APEC로 17, 4007(우동, 센텀 리더스마크)중국/카자흐스탄유치업자2020-12-22 13:36:07
61565230삼에스개발㈜<NA>부산구자성<NA>부산광역시 연제구 월드컵대로 83, 109호, 401호(연산동, 케이티엔지부산본부)미국/일본/중국/러시아(CIS연합)유치업자2020-12-22 13:36:07
71566231아리스타쉬핑 주식회사<NA>부산박기태<NA>부산광역시 동구 중앙대로 228, 901(초량동, 조선일보사사옥)러시아(CIS연합)유치업자2020-12-22 13:36:07
81567232주식회사 알코르메드라인<NA>부산MAZURIK ELENA<NA>부산광역시 동구 중앙대로 263, 906(초량동,국제오피스텔)<NA>유치업자2020-12-22 13:36:07
91568233에메랄드 마린 주식회사<NA>부산송길호<NA>부산광역시 중구 구덕로 87-1. 702(남포동6가, 하버타워 )미국유치업자2020-12-22 13:36:07
skeyreg_nobusiness_nminsti_gubunregionrepresentativecompany_reg_noaddrtarget_countrygubunlast_load_dttm
238135722센텀이룸여성의원의원부산최종열 외 1명<NA>부산광역시 해운대구 센텀2로 20, 10층 1003호, 11층 1103호러시아, 몽골, 베트남의료기관2020-12-22 13:36:07
239135823우리원병원병원부산유권열<NA>부산광역시 사하구 다대로 565(다대동)<NA>의료기관2020-12-22 13:36:07
240135924부산숨이비인후과의원의원부산정재훈<NA>부산광역시 사하구 낙동남로 1412, 7-8층(하단동, 경부빌딩)중국의료기관2020-12-22 13:36:07
241136025제우스남성의원의원부산이석영<NA>부산광역시 부산진구 서면문화로 10, 10층(부전동)미국, 일본, 중국, 러시아, 중동, 몽골, 베트남의료기관2020-12-22 13:36:07
242136126명지엘치과치과의원부산박성준<NA>부산광역시 강서구 명지국제8로 230, 403-404호(명지동)<NA>의료기관2020-12-22 13:36:07
243136227의료법인 정선의료재단 온종합병원종합병원부산윤선희<NA>부산광역시 부산진구 가야대로 721, 1층(당감동)<NA>의료기관2020-12-22 13:36:07
244136328힘내라 병원병원부산김문찬 외 1명<NA>부산광역시 동구 범일로 85, 지상2-5층, 지하1-2층(범일동)일본, 중국, 필리핀, 대만의료기관2020-12-22 13:36:07
245136429명제한의원한의원부산이수칠<NA>부산광역시 동래구 충렬대로 108번길 16(온천동)일본, 중국, 베트남의료기관2020-12-22 13:36:07
246136530시원항병원병원부산조현언<NA>부산광역시 북구 금곡대로 27, 5층~10층(덕천동, 더청명빌딩)<NA>의료기관2020-12-22 13:36:07
247136631이노의원의원부산이상윤<NA>부산광역시 해운대구 해운대로 620, 305호~309호(우동, 해운대 라뮤에뜨)<NA>의료기관2020-12-22 13:36:07