Overview

Dataset statistics

Number of variables12
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.2 KiB
Average record size in memory104.3 B

Variable types

Text2
Numeric5
Categorical5

Alerts

FILE_NAME has constant value ""Constant
base_ymd has constant value ""Constant
ctprvn_nm is highly overall correlated with x and 5 other fieldsHigh correlation
signgu_nm is highly overall correlated with x and 6 other fieldsHigh correlation
ctprvn_cd is highly overall correlated with x and 5 other fieldsHigh correlation
x is highly overall correlated with y and 5 other fieldsHigh correlation
y is highly overall correlated with x and 4 other fieldsHigh correlation
signgu_cd is highly overall correlated with x and 5 other fieldsHigh correlation
pop_cnt is highly overall correlated with x and 5 other fieldsHigh correlation
mrck_cnt is highly overall correlated with pop_cnt and 1 other fieldsHigh correlation
mrhst_nm has unique valuesUnique
addr has unique valuesUnique

Reproduction

Analysis started2023-12-10 09:57:15.492660
Analysis finished2023-12-10 09:57:23.115014
Duration7.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

mrhst_nm
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:57:23.550547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length6.57
Min length2

Characters and Unicode

Total characters657
Distinct characters227
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row센트럴땡큐사진관
2nd row행복한책방
3rd row베이비 스튜디오 자스민
4th row기린나라(주 우강그린)
5th row우주서점문구
ValueCountFrequency (%)
놀숲 3
 
2.4%
베이비 2
 
1.6%
스튜디오 2
 
1.6%
정류소 2
 
1.6%
센트럴땡큐사진관 1
 
0.8%
현우당 1
 
0.8%
알지(rg)호텔 1
 
0.8%
솔체압화 1
 
0.8%
드림북(키움북 1
 
0.8%
썬프라자 1
 
0.8%
Other values (109) 109
87.9%
2023-12-10T18:57:24.644764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24
 
3.7%
스 21
 
3.2%
점 18
 
2.7%
서 17
 
2.6%
오 13
 
2.0%
사 12
 
1.8%
디 12
 
1.8%
튜 12
 
1.8%
이 11
 
1.7%
( 11
 
1.7%
Other values (217) 506
77.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 584
88.9%
Space Separator 24
 
3.7%
Uppercase Letter 13
 
2.0%
Open Punctuation 11
 
1.7%
Close Punctuation 11
 
1.7%
Lowercase Letter 7
 
1.1%
Decimal Number 6
 
0.9%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 21
 
3.6%
점 18
 
3.1%
서 17
 
2.9%
오 13
 
2.2%
사 12
 
2.1%
디 12
 
2.1%
튜 12
 
2.1%
이 11
 
1.9%
천 11
 
1.9%
관 10
 
1.7%
Other values (192) 447
76.5%
Uppercase Letter
ValueCountFrequency (%)
G 2
15.4%
R 1
7.7%
I 1
7.7%
B 1
7.7%
H 1
7.7%
C 1
7.7%
M 1
7.7%
A 1
7.7%
D 1
7.7%
E 1
7.7%
Other values (2) 2
15.4%
Lowercase Letter
ValueCountFrequency (%)
o 3
42.9%
m 1
 
14.3%
l 1
 
14.3%
e 1
 
14.3%
t 1
 
14.3%
Decimal Number
ValueCountFrequency (%)
3 2
33.3%
1 2
33.3%
5 1
16.7%
7 1
16.7%
Space Separator
ValueCountFrequency (%)
24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 585
89.0%
Common 52
 
7.9%
Latin 20
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 21
 
3.6%
점 18
 
3.1%
서 17
 
2.9%
오 13
 
2.2%
사 12
 
2.1%
디 12
 
2.1%
튜 12
 
2.1%
이 11
 
1.9%
천 11
 
1.9%
관 10
 
1.7%
Other values (193) 448
76.6%
Latin
ValueCountFrequency (%)
o 3
15.0%
G 2
 
10.0%
R 1
 
5.0%
I 1
 
5.0%
m 1
 
5.0%
B 1
 
5.0%
l 1
 
5.0%
e 1
 
5.0%
t 1
 
5.0%
H 1
 
5.0%
Other values (7) 7
35.0%
Common
ValueCountFrequency (%)
24
46.2%
( 11
21.2%
) 11
21.2%
3 2
 
3.8%
1 2
 
3.8%
5 1
 
1.9%
7 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 584
88.9%
ASCII 72
 
11.0%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24
33.3%
( 11
15.3%
) 11
15.3%
o 3
 
4.2%
3 2
 
2.8%
1 2
 
2.8%
G 2
 
2.8%
5 1
 
1.4%
R 1
 
1.4%
I 1
 
1.4%
Other values (14) 14
19.4%
Hangul
ValueCountFrequency (%)
스 21
 
3.6%
점 18
 
3.1%
서 17
 
2.9%
오 13
 
2.2%
사 12
 
2.1%
디 12
 
2.1%
튜 12
 
2.1%
이 11
 
1.9%
천 11
 
1.9%
관 10
 
1.7%
Other values (192) 447
76.5%
None
ValueCountFrequency (%)
㈜ 1
100.0%

addr
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:57:25.373933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length31
Mean length21.5
Min length12

Characters and Unicode

Total characters2150
Distinct characters169
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row경기 의정부시 시민로 80,191호
2nd row경기 고양시 일산서구 일산로 741번길 13, 1층(대화동)
3rd row경기 의정부시 청사로47번길 18 209호
4th row경기 과천시 대공원광장로 80 (서울대공원 기린나라)
5th row전남 순천시 우석로 191-4 (인제동)
ValueCountFrequency (%)
경기 56
 
11.4%
전남 43
 
8.7%
순천시 41
 
8.3%
의정부시 28
 
5.7%
구리시 13
 
2.6%
일산서구 10
 
2.0%
고양시 10
 
2.0%
의정부동 7
 
1.4%
과천시 6
 
1.2%
연향동 6
 
1.2%
Other values (229) 272
55.3%
2023-12-10T18:57:26.276958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
396
 
18.4%
1 126
 
5.9%
시 100
 
4.7%
동 67
 
3.1%
기 61
 
2.8%
2 59
 
2.7%
경 59
 
2.7%
로 50
 
2.3%
천 48
 
2.2%
전 47
 
2.2%
Other values (159) 1137
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1195
55.6%
Decimal Number 430
 
20.0%
Space Separator 396
 
18.4%
Dash Punctuation 42
 
2.0%
Open Punctuation 35
 
1.6%
Close Punctuation 35
 
1.6%
Other Punctuation 16
 
0.7%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 100
 
8.4%
동 67
 
5.6%
기 61
 
5.1%
경 59
 
4.9%
로 50
 
4.2%
천 48
 
4.0%
전 47
 
3.9%
남 46
 
3.8%
부 43
 
3.6%
정 43
 
3.6%
Other values (143) 631
52.8%
Decimal Number
ValueCountFrequency (%)
1 126
29.3%
2 59
13.7%
0 39
 
9.1%
3 36
 
8.4%
4 33
 
7.7%
7 30
 
7.0%
5 29
 
6.7%
9 27
 
6.3%
8 27
 
6.3%
6 24
 
5.6%
Space Separator
ValueCountFrequency (%)
396
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1195
55.6%
Common 955
44.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 100
 
8.4%
동 67
 
5.6%
기 61
 
5.1%
경 59
 
4.9%
로 50
 
4.2%
천 48
 
4.0%
전 47
 
3.9%
남 46
 
3.8%
부 43
 
3.6%
정 43
 
3.6%
Other values (143) 631
52.8%
Common
ValueCountFrequency (%)
396
41.5%
1 126
 
13.2%
2 59
 
6.2%
- 42
 
4.4%
0 39
 
4.1%
3 36
 
3.8%
( 35
 
3.7%
) 35
 
3.7%
4 33
 
3.5%
7 30
 
3.1%
Other values (6) 124
 
13.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1195
55.6%
ASCII 955
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
396
41.5%
1 126
 
13.2%
2 59
 
6.2%
- 42
 
4.4%
0 39
 
4.1%
3 36
 
3.8%
( 35
 
3.7%
) 35
 
3.7%
4 33
 
3.5%
7 30
 
3.1%
Other values (6) 124
 
13.0%
Hangul
ValueCountFrequency (%)
시 100
 
8.4%
동 67
 
5.6%
기 61
 
5.1%
경 59
 
4.9%
로 50
 
4.2%
천 48
 
4.0%
전 47
 
3.9%
남 46
 
3.8%
부 43
 
3.6%
정 43
 
3.6%
Other values (143) 631
52.8%

x
Real number (ℝ)

HIGH CORRELATION 

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.497393
Minimum34.888062
Maximum37.758991
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:57:26.570562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.888062
5-th percentile34.940079
Q134.953215
median37.588688
Q337.730123
95-th percentile37.746604
Maximum37.758991
Range2.870929
Interquartile range (IQR)2.7769075

Descriptive statistics

Standard deviation1.3533782
Coefficient of variation (CV)0.037081504
Kurtosis-1.9500848
Mean36.497393
Median Absolute Deviation (MAD)0.1591625
Skewness-0.27823674
Sum3649.7393
Variance1.8316326
MonotonicityNot monotonic
2023-12-10T18:57:26.937540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.946052 2
 
2.0%
34.953071 2
 
2.0%
37.737918 1
 
1.0%
37.738691 1
 
1.0%
37.74253 1
 
1.0%
34.973428 1
 
1.0%
34.9368 1
 
1.0%
37.741711 1
 
1.0%
34.953263 1
 
1.0%
37.42684 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
34.888062 1
1.0%
34.897208 1
1.0%
34.913144 1
1.0%
34.9368 1
1.0%
34.937434 1
1.0%
34.940218 1
1.0%
34.940615 1
1.0%
34.940655 1
1.0%
34.942345 1
1.0%
34.945025 1
1.0%
ValueCountFrequency (%)
37.758991 1
1.0%
37.752522 1
1.0%
37.752162 1
1.0%
37.750452 1
1.0%
37.746621 1
1.0%
37.746603 1
1.0%
37.74577 1
1.0%
37.743825 1
1.0%
37.74253 1
1.0%
37.742518 1
1.0%

y
Real number (ℝ)

HIGH CORRELATION 

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.19952
Minimum126.13543
Maximum127.52743
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:57:27.250925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.13543
5-th percentile126.75341
Q1127.04375
median127.13377
Q3127.49031
95-th percentile127.5228
Maximum127.52743
Range1.392003
Interquartile range (IQR)0.446568

Descriptive statistics

Standard deviation0.29266185
Coefficient of variation (CV)0.0023008095
Kurtosis0.70957294
Mean127.19952
Median Absolute Deviation (MAD)0.348731
Skewness-0.70839582
Sum12719.952
Variance0.085650961
MonotonicityNot monotonic
2023-12-10T18:57:27.573135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.48765 2
 
2.0%
127.519851 2
 
2.0%
127.044037 1
 
1.0%
127.044946 1
 
1.0%
127.049379 1
 
1.0%
127.493831 1
 
1.0%
127.489141 1
 
1.0%
127.049526 1
 
1.0%
127.520539 1
 
1.0%
126.992554 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
126.13543 1
1.0%
126.33565 1
1.0%
126.729996 1
1.0%
126.735547 1
1.0%
126.751496 1
1.0%
126.753508 1
1.0%
126.757411 1
1.0%
126.75778 1
1.0%
126.763719 1
1.0%
126.76658 1
1.0%
ValueCountFrequency (%)
127.527433 1
1.0%
127.527282 1
1.0%
127.524927 1
1.0%
127.523605 1
1.0%
127.52293 1
1.0%
127.522793 1
1.0%
127.522318 1
1.0%
127.522229 1
1.0%
127.520539 1
1.0%
127.519851 2
2.0%

ctprvn_cd
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
31
57 
36
43 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row31
2nd row31
3rd row31
4th row31
5th row36

Common Values

ValueCountFrequency (%)
31 57
57.0%
36 43
43.0%

Length

2023-12-10T18:57:28.080128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:28.363394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
31 57
57.0%
36 43
43.0%

ctprvn_nm
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경기도
57 
전라남도
43 

Length

Max length4
Median length3
Mean length3.43
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도
2nd row경기도
3rd row경기도
4th row경기도
5th row전라남도

Common Values

ValueCountFrequency (%)
경기도 57
57.0%
전라남도 43
43.0%

Length

2023-12-10T18:57:28.804267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:29.685103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 57
57.0%
전라남도 43
43.0%

signgu_cd
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33212.9
Minimum31030
Maximum36480
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:57:29.937701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31030
5-th percentile31030
Q131030
median31120
Q336030
95-th percentile36030
Maximum36480
Range5450
Interquartile range (IQR)5000

Descriptive statistics

Standard deviation2478.3878
Coefficient of variation (CV)0.074621242
Kurtosis-1.9523264
Mean33212.9
Median Absolute Deviation (MAD)90
Skewness0.28867229
Sum3321290
Variance6142406.3
MonotonicityNot monotonic
2023-12-10T18:57:30.201435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
36030 41
41.0%
31030 28
28.0%
31120 13
 
13.0%
31104 10
 
10.0%
31110 6
 
6.0%
36480 2
 
2.0%
ValueCountFrequency (%)
31030 28
28.0%
31104 10
 
10.0%
31110 6
 
6.0%
31120 13
 
13.0%
36030 41
41.0%
36480 2
 
2.0%
ValueCountFrequency (%)
36480 2
 
2.0%
36030 41
41.0%
31120 13
 
13.0%
31110 6
 
6.0%
31104 10
 
10.0%
31030 28
28.0%

signgu_nm
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
순천시
41 
의정부시
28 
구리시
13 
고양시 일산서구
10 
과천시
6 

Length

Max length8
Median length3
Mean length3.78
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row의정부시
2nd row고양시 일산서구
3rd row의정부시
4th row과천시
5th row순천시

Common Values

ValueCountFrequency (%)
순천시 41
41.0%
의정부시 28
28.0%
구리시 13
 
13.0%
고양시 일산서구 10
 
10.0%
과천시 6
 
6.0%
신안군 2
 
2.0%

Length

2023-12-10T18:57:30.494948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:30.801612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
순천시 41
37.3%
의정부시 28
25.5%
구리시 13
 
11.8%
고양시 10
 
9.1%
일산서구 10
 
9.1%
과천시 6
 
5.5%
신안군 2
 
1.8%

pop_cnt
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean239989
Minimum21343
Maximum364214
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:57:31.107195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21343
5-th percentile45142
Q1217744
median217744
Q3364214
95-th percentile364214
Maximum364214
Range342871
Interquartile range (IQR)146470

Descriptive statistics

Standard deviation92993.04
Coefficient of variation (CV)0.38748876
Kurtosis-0.16702259
Mean239989
Median Absolute Deviation (MAD)28225
Skewness-0.23501106
Sum23998900
Variance8.6477055 × 109
MonotonicityNot monotonic
2023-12-10T18:57:31.325237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
217744 41
41.0%
364214 28
28.0%
161552 13
 
13.0%
245969 10
 
10.0%
45142 6
 
6.0%
21343 2
 
2.0%
ValueCountFrequency (%)
21343 2
 
2.0%
45142 6
 
6.0%
161552 13
 
13.0%
217744 41
41.0%
245969 10
 
10.0%
364214 28
28.0%
ValueCountFrequency (%)
364214 28
28.0%
245969 10
 
10.0%
217744 41
41.0%
161552 13
 
13.0%
45142 6
 
6.0%
21343 2
 
2.0%

mrck_cnt
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean159.26
Minimum14
Maximum201
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:57:31.560233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile20
Q1104
median200
Q3201
95-th percentile201
Maximum201
Range187
Interquartile range (IQR)97

Descriptive statistics

Standard deviation64.314979
Coefficient of variation (CV)0.40383636
Kurtosis-0.41883811
Mean159.26
Median Absolute Deviation (MAD)1
Skewness-1.1025908
Sum15926
Variance4136.4166
MonotonicityNot monotonic
2023-12-10T18:57:31.801414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
200 41
41.0%
201 28
28.0%
70 13
 
13.0%
104 10
 
10.0%
20 6
 
6.0%
14 2
 
2.0%
ValueCountFrequency (%)
14 2
 
2.0%
20 6
 
6.0%
70 13
 
13.0%
104 10
 
10.0%
200 41
41.0%
201 28
28.0%
ValueCountFrequency (%)
201 28
28.0%
200 41
41.0%
104 10
 
10.0%
70 13
 
13.0%
20 6
 
6.0%
14 2
 
2.0%

FILE_NAME
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC_615_CLT_NURI_SHOP_MAP_2019
100 

Length

Max length29
Median length29
Mean length29
Min length29

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_615_CLT_NURI_SHOP_MAP_2019
2nd rowKC_615_CLT_NURI_SHOP_MAP_2019
3rd rowKC_615_CLT_NURI_SHOP_MAP_2019
4th rowKC_615_CLT_NURI_SHOP_MAP_2019
5th rowKC_615_CLT_NURI_SHOP_MAP_2019

Common Values

ValueCountFrequency (%)
KC_615_CLT_NURI_SHOP_MAP_2019 100
100.0%

Length

2023-12-10T18:57:32.136608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:32.337613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_615_clt_nuri_shop_map_2019 100
100.0%

base_ymd
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20200220
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20200220
2nd row20200220
3rd row20200220
4th row20200220
5th row20200220

Common Values

ValueCountFrequency (%)
20200220 100
100.0%

Length

2023-12-10T18:57:32.559753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:32.822276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20200220 100
100.0%

Interactions

2023-12-10T18:57:20.934775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:16.547617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:17.855609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:18.534444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:19.643376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:21.193335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:16.721927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:17.996869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:18.761680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:19.893904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:21.493509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:16.919249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:18.126732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:18.969073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:20.101159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:21.804474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:17.095471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:18.256096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:19.174168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:20.471039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:22.130584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:17.437814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:18.376438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:19.405540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:20.685177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:57:32.973119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
mrhst_nmaddrxyctprvn_cdctprvn_nmsigngu_cdsigngu_nmpop_cntmrck_cnt
mrhst_nm1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
addr1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
x1.0001.0001.0000.9461.0001.0001.0001.0001.0000.668
y1.0001.0000.9461.0001.0001.0001.0000.9951.0000.961
ctprvn_cd1.0001.0001.0001.0001.0000.9990.9991.0001.0000.689
ctprvn_nm1.0001.0001.0001.0000.9991.0000.9991.0001.0000.689
signgu_cd1.0001.0001.0001.0000.9990.9991.0001.0001.0000.997
signgu_nm1.0001.0001.0000.9951.0001.0001.0001.0001.0001.000
pop_cnt1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
mrck_cnt1.0001.0000.6680.9610.6890.6890.9971.0001.0001.000
2023-12-10T18:57:33.246994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ctprvn_nmsigngu_nmctprvn_cd
ctprvn_nm1.0000.9790.979
signgu_nm0.9791.0000.979
ctprvn_cd0.9790.9791.000
2023-12-10T18:57:33.417920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
xysigngu_cdpop_cntmrck_cntctprvn_cdctprvn_nmsigngu_nm
x1.000-0.689-0.9330.6390.4040.9950.9950.984
y-0.6891.0000.704-0.2850.0890.9790.9790.888
signgu_cd-0.9330.7041.000-0.681-0.4390.9790.9790.979
pop_cnt0.639-0.285-0.6811.0000.8610.9530.9530.995
mrck_cnt0.4040.089-0.4390.8611.0000.4820.4820.990
ctprvn_cd0.9950.9790.9790.9530.4821.0000.9790.979
ctprvn_nm0.9950.9790.9790.9530.4820.9791.0000.979
signgu_nm0.9840.8880.9790.9950.9900.9790.9791.000

Missing values

2023-12-10T18:57:22.468049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:57:22.874106image/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

mrhst_nmaddrxyctprvn_cdctprvn_nmsigngu_cdsigngu_nmpop_cntmrck_cntFILE_NAMEbase_ymd
0센트럴땡큐사진관경기 의정부시 시민로 80,191호37.737918127.04403731경기도31030의정부시364214201KC_615_CLT_NURI_SHOP_MAP_201920200220
1행복한책방경기 고양시 일산서구 일산로 741번길 13, 1층(대화동)37.676942126.75149631경기도31104고양시 일산서구245969104KC_615_CLT_NURI_SHOP_MAP_201920200220
2베이비 스튜디오 자스민경기 의정부시 청사로47번길 18 209호37.752522127.06864531경기도31030의정부시364214201KC_615_CLT_NURI_SHOP_MAP_201920200220
3기린나라(주 우강그린)경기 과천시 대공원광장로 80 (서울대공원 기린나라)37.433982127.01896731경기도31110과천시4514220KC_615_CLT_NURI_SHOP_MAP_201920200220
4우주서점문구전남 순천시 우석로 191-4 (인제동)34.946052127.4876536전라남도36030순천시217744200KC_615_CLT_NURI_SHOP_MAP_201920200220
5시온악기경기 고양시 일산서구 중앙로 1470(주엽동, 동부썬프라자비동 201호)37.672319126.75741131경기도31104고양시 일산서구245969104KC_615_CLT_NURI_SHOP_MAP_201920200220
6리차드뮤직경기 의정부시 호국로 1295-1, 2층37.743825127.04806931경기도31030의정부시364214201KC_615_CLT_NURI_SHOP_MAP_201920200220
7문포토경기 고양시 일산서구 킨텍스로 300 문촌마을 1406-70637.67053126.75350831경기도31104고양시 일산서구245969104KC_615_CLT_NURI_SHOP_MAP_201920200220
8순천문화예술회관전남 순천시 삼산로 1634.970543127.48524136전라남도36030순천시217744200KC_615_CLT_NURI_SHOP_MAP_201920200220
9의정부예술의전당경기 의정부시 의정로137.733271127.03437531경기도31030의정부시364214201KC_615_CLT_NURI_SHOP_MAP_201920200220
mrhst_nmaddrxyctprvn_cdctprvn_nmsigngu_cdsigngu_nmpop_cntmrck_cntFILE_NAMEbase_ymd
90대륙화방경기 의정부시 의정부1동 181~213 210-8 희상빌딩1층37.740926127.04946831경기도31030의정부시364214201KC_615_CLT_NURI_SHOP_MAP_201920200220
91호텔붐(Hotel Boom)경기 의정부시 의정부동 신흥로239번길 46 붐모텔37.737692127.04062531경기도31030의정부시364214201KC_615_CLT_NURI_SHOP_MAP_201920200220
92천재서점전남 순천시 덕연로 70 (연향동)34.94843127.51357136전라남도36030순천시217744200KC_615_CLT_NURI_SHOP_MAP_201920200220
93둥이책방경기 고양시 일산서구 일산로 556 후곡타운 상가 106호 (일산동)37.678606126.7665831경기도31104고양시 일산서구245969104KC_615_CLT_NURI_SHOP_MAP_201920200220
94카톨릭서원전남 순천시 중앙로 113-234.955907127.48388836전라남도36030순천시217744200KC_615_CLT_NURI_SHOP_MAP_201920200220
95꿈의궁전경기 의정부시 의정부동 호국로1332번길 7137.74086127.05237331경기도31030의정부시364214201KC_615_CLT_NURI_SHOP_MAP_201920200220
96팔마장전남 순천시 역전1길 9 (조곡동)34.946248127.50006436전라남도36030순천시217744200KC_615_CLT_NURI_SHOP_MAP_201920200220
97투앤포모텔전남 순천시 장선배기1길 10-8 (조례동)34.95356127.52279336전라남도36030순천시217744200KC_615_CLT_NURI_SHOP_MAP_201920200220
98(주)서울랜드경기 과천시 광명로 181 (막계동)37.436539127.02414331경기도31110과천시4514220KC_615_CLT_NURI_SHOP_MAP_201920200220
99홍익갤러리전남 순천시 구암길 15 (연향동)34.947035127.51408336전라남도36030순천시217744200KC_615_CLT_NURI_SHOP_MAP_201920200220