Overview

Dataset statistics

Number of variables21
Number of observations100
Missing cells9
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.5 KiB
Average record size in memory179.3 B

Variable types

Text7
Categorical5
Numeric9

Alerts

lclas has constant value ""Constant
mlsfc has constant value ""Constant
file_name has constant value ""Constant
base_ymd has constant value ""Constant
adstrd_cd has 2 (2.0%) missing valuesMissing
adstrd_nm has 2 (2.0%) missing valuesMissing
rdnmaddr_cd has 2 (2.0%) missing valuesMissing
zip_cd has 2 (2.0%) missing valuesMissing
id has unique valuesUnique
fclt_name has unique valuesUnique
rdnm_addr has unique valuesUnique
grid_cd has unique valuesUnique
x_cd has unique valuesUnique
y_cd has unique valuesUnique
usemem_total has 6 (6.0%) zerosZeros
sccnt has 79 (79.0%) zerosZeros
search_rate has 79 (79.0%) zerosZeros

Reproduction

Analysis started2023-12-10 09:53:12.008617
Analysis finished2023-12-10 09:53:13.090598
Duration1.08 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

id
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:53:13.395897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1900
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
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 rowKC5PSIF21N000000065
2nd rowKC5PSIF21N000000237
3rd rowKC5PSIF21N000000118
4th rowKC5PSIF21N000000036
5th rowKC5PSIF21N000000116
ValueCountFrequency (%)
kc5psif21n000000065 1
 
1.0%
kc5psif21n000000219 1
 
1.0%
kc5psif21n000000157 1
 
1.0%
kc5psif21n000000236 1
 
1.0%
kc5psif21n000000035 1
 
1.0%
kc5psif21n000000043 1
 
1.0%
kc5psif21n000000051 1
 
1.0%
kc5psif21n000000196 1
 
1.0%
kc5psif21n000000017 1
 
1.0%
kc5psif21n000000037 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:53:14.071285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 665
35.0%
1 167
 
8.8%
2 131
 
6.9%
5 120
 
6.3%
N 100
 
5.3%
C 100
 
5.3%
K 100
 
5.3%
F 100
 
5.3%
I 100
 
5.3%
S 100
 
5.3%
Other values (7) 217
 
11.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1200
63.2%
Uppercase Letter 700
36.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 665
55.4%
1 167
 
13.9%
2 131
 
10.9%
5 120
 
10.0%
9 22
 
1.8%
6 21
 
1.8%
3 20
 
1.7%
7 20
 
1.7%
8 19
 
1.6%
4 15
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
N 100
14.3%
C 100
14.3%
K 100
14.3%
F 100
14.3%
I 100
14.3%
S 100
14.3%
P 100
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1200
63.2%
Latin 700
36.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 665
55.4%
1 167
 
13.9%
2 131
 
10.9%
5 120
 
10.0%
9 22
 
1.8%
6 21
 
1.8%
3 20
 
1.7%
7 20
 
1.7%
8 19
 
1.6%
4 15
 
1.2%
Latin
ValueCountFrequency (%)
N 100
14.3%
C 100
14.3%
K 100
14.3%
F 100
14.3%
I 100
14.3%
S 100
14.3%
P 100
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 665
35.0%
1 167
 
8.8%
2 131
 
6.9%
5 120
 
6.3%
N 100
 
5.3%
C 100
 
5.3%
K 100
 
5.3%
F 100
 
5.3%
I 100
 
5.3%
S 100
 
5.3%
Other values (7) 217
 
11.4%

lclas
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
문화시설 100
100.0%

Length

2023-12-10T18:53:14.339461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:53:14.581157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화시설 100
100.0%

mlsfc
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공연장 100
100.0%

Length

2023-12-10T18:53:14.776188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:53:14.961685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공연장 100
100.0%

fclt_name
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:53:15.432378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length8.18
Min length4

Characters and Unicode

Total characters818
Distinct characters192
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

Unique100 ?
Unique (%)100.0%

Sample

1st row(재)영화의전당
2nd row화순 하니움 문화스포츠센터
3rd row5.18기념문화센터
4th rowBNK부산은행 조은극장
5th rowF1963
ValueCountFrequency (%)
구 2
 
1.7%
대학로 2
 
1.7%
하니움 1
 
0.8%
대전평송청소년문화센터 1
 
0.8%
대전컨벤션센터(dcc 1
 
0.8%
대전예술의전당 1
 
0.8%
대전시립연정국악원 1
 
0.8%
대백프라자 1
 
0.8%
대구학생문화센터 1
 
0.8%
대구콘서트하우스 1
 
0.8%
Other values (109) 109
90.1%
2023-12-10T18:53:16.340138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
문 38
 
4.6%
화 37
 
4.5%
아 35
 
4.3%
관 29
 
3.5%
트 29
 
3.5%
회 26
 
3.2%
터 26
 
3.2%
예 25
 
3.1%
센 23
 
2.8%
술 23
 
2.8%
Other values (182) 527
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 743
90.8%
Space Separator 21
 
2.6%
Uppercase Letter 15
 
1.8%
Close Punctuation 12
 
1.5%
Open Punctuation 12
 
1.5%
Decimal Number 8
 
1.0%
Other Punctuation 7
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
문 38
 
5.1%
화 37
 
5.0%
아 35
 
4.7%
관 29
 
3.9%
트 29
 
3.9%
회 26
 
3.5%
터 26
 
3.5%
예 25
 
3.4%
센 23
 
3.1%
술 23
 
3.1%
Other values (160) 452
60.8%
Uppercase Letter
ValueCountFrequency (%)
C 4
26.7%
K 2
13.3%
N 2
13.3%
J 2
13.3%
D 1
 
6.7%
M 1
 
6.7%
T 1
 
6.7%
F 1
 
6.7%
B 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 2
25.0%
3 2
25.0%
6 1
12.5%
9 1
12.5%
8 1
12.5%
5 1
12.5%
Close Punctuation
ValueCountFrequency (%)
) 10
83.3%
] 2
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 10
83.3%
[ 2
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 6
85.7%
, 1
 
14.3%
Space Separator
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 743
90.8%
Common 60
 
7.3%
Latin 15
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
문 38
 
5.1%
화 37
 
5.0%
아 35
 
4.7%
관 29
 
3.9%
트 29
 
3.9%
회 26
 
3.5%
터 26
 
3.5%
예 25
 
3.4%
센 23
 
3.1%
술 23
 
3.1%
Other values (160) 452
60.8%
Common
ValueCountFrequency (%)
21
35.0%
) 10
16.7%
( 10
16.7%
. 6
 
10.0%
1 2
 
3.3%
3 2
 
3.3%
[ 2
 
3.3%
] 2
 
3.3%
, 1
 
1.7%
6 1
 
1.7%
Other values (3) 3
 
5.0%
Latin
ValueCountFrequency (%)
C 4
26.7%
K 2
13.3%
N 2
13.3%
J 2
13.3%
D 1
 
6.7%
M 1
 
6.7%
T 1
 
6.7%
F 1
 
6.7%
B 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 743
90.8%
ASCII 75
 
9.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
문 38
 
5.1%
화 37
 
5.0%
아 35
 
4.7%
관 29
 
3.9%
트 29
 
3.9%
회 26
 
3.5%
터 26
 
3.5%
예 25
 
3.4%
센 23
 
3.1%
술 23
 
3.1%
Other values (160) 452
60.8%
ASCII
ValueCountFrequency (%)
21
28.0%
) 10
13.3%
( 10
13.3%
. 6
 
8.0%
C 4
 
5.3%
K 2
 
2.7%
N 2
 
2.7%
1 2
 
2.7%
3 2
 
2.7%
J 2
 
2.7%
Other values (12) 14
18.7%

ctprvn_nm
Categorical

Distinct13
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
33 
경기도
11 
부산광역시
7 
전라남도
7 
경상북도
6 
Other values (8)
36 

Length

Max length5
Median length5
Mean length4.41
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시
2nd row전라남도
3rd row광주광역시
4th row부산광역시
5th row부산광역시

Common Values

ValueCountFrequency (%)
서울특별시 33
33.0%
경기도 11
 
11.0%
부산광역시 7
 
7.0%
전라남도 7
 
7.0%
경상북도 6
 
6.0%
경상남도 6
 
6.0%
충청남도 6
 
6.0%
대구광역시 6
 
6.0%
광주광역시 4
 
4.0%
강원도 4
 
4.0%
Other values (3) 10
 
10.0%

Length

2023-12-10T18:53:16.614976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 33
33.0%
경기도 11
 
11.0%
부산광역시 7
 
7.0%
전라남도 7
 
7.0%
경상북도 6
 
6.0%
경상남도 6
 
6.0%
충청남도 6
 
6.0%
대구광역시 6
 
6.0%
광주광역시 4
 
4.0%
강원도 4
 
4.0%
Other values (3) 10
 
10.0%

sgnr_nm
Text

Distinct65
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:53:17.053431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.05
Min length2

Characters and Unicode

Total characters305
Distinct characters71
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)52.0%

Sample

1st row해운대구
2nd row화순군
3rd row서구
4th row중구
5th row수영구
ValueCountFrequency (%)
종로구 13
 
12.4%
중구 8
 
7.6%
서구 6
 
5.7%
서초구 3
 
2.9%
수원시 2
 
1.9%
고양시 2
 
1.9%
공주시 2
 
1.9%
광진구 2
 
1.9%
밀양시 2
 
1.9%
북구 2
 
1.9%
Other values (58) 63
60.0%
2023-12-10T18:53:17.869414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 65
21.3%
시 37
 
12.1%
로 14
 
4.6%
종 13
 
4.3%
서 12
 
3.9%
군 9
 
3.0%
주 9
 
3.0%
양 8
 
2.6%
중 8
 
2.6%
산 8
 
2.6%
Other values (61) 122
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 300
98.4%
Space Separator 5
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 65
21.7%
시 37
 
12.3%
로 14
 
4.7%
종 13
 
4.3%
서 12
 
4.0%
군 9
 
3.0%
주 9
 
3.0%
양 8
 
2.7%
중 8
 
2.7%
산 8
 
2.7%
Other values (60) 117
39.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 300
98.4%
Common 5
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 65
21.7%
시 37
 
12.3%
로 14
 
4.7%
종 13
 
4.3%
서 12
 
4.0%
군 9
 
3.0%
주 9
 
3.0%
양 8
 
2.7%
중 8
 
2.7%
산 8
 
2.7%
Other values (60) 117
39.0%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 300
98.4%
ASCII 5
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 65
21.7%
시 37
 
12.3%
로 14
 
4.7%
종 13
 
4.3%
서 12
 
4.0%
군 9
 
3.0%
주 9
 
3.0%
양 8
 
2.7%
중 8
 
2.7%
산 8
 
2.7%
Other values (60) 117
39.0%
ASCII
ValueCountFrequency (%)
5
100.0%

legaldong_cd
Real number (ℝ)

Distinct88
Distinct (%)88.9%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean2.9673672 × 109
Minimum1.111012 × 109
Maximum4.888025 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:18.198692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111012 × 109
5-th percentile1.1110168 × 109
Q11.1440116 × 109
median2.9140118 × 109
Q34.4250105 × 109
95-th percentile4.8178104 × 109
Maximum4.888025 × 109
Range3.777013 × 109
Interquartile range (IQR)3.2809988 × 109

Descriptive statistics

Standard deviation1.4775752 × 109
Coefficient of variation (CV)0.49794147
Kurtosis-1.6318799
Mean2.9673672 × 109
Median Absolute Deviation (MAD)1.7400015 × 109
Skewness-0.14584397
Sum2.9376936 × 1011
Variance2.1832284 × 1018
MonotonicityNot monotonic
2023-12-10T18:53:18.490291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1111016800 5
 
5.0%
1111016900 3
 
3.0%
1165010800 3
 
3.0%
3017012800 3
 
3.0%
4415010700 2
 
2.0%
1130510200 1
 
1.0%
4825010800 1
 
1.0%
2711015700 1
 
1.0%
2729011100 1
 
1.0%
2711014900 1
 
1.0%
Other values (78) 78
78.0%
ValueCountFrequency (%)
1111012000 1
 
1.0%
1111016000 1
 
1.0%
1111016500 1
 
1.0%
1111016800 5
5.0%
1111016900 3
3.0%
1111017000 1
 
1.0%
1111017200 1
 
1.0%
1114012700 1
 
1.0%
1114013600 1
 
1.0%
1114013800 1
 
1.0%
ValueCountFrequency (%)
4888025000 1
1.0%
4831010200 1
1.0%
4827031000 1
1.0%
4827010300 1
1.0%
4825010800 1
1.0%
4817010400 1
1.0%
4728010100 1
1.0%
4719012000 1
1.0%
4719011000 1
1.0%
4715011000 1
1.0%

legalemd_nm
Text

Distinct84
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:53:18.986939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.06
Min length2

Characters and Unicode

Total characters306
Distinct characters101
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)75.0%

Sample

1st row우동
2nd row화순읍
3rd row쌍촌동
4th row남포동2가
5th row망미동
ValueCountFrequency (%)
동숭동 5
 
5.0%
서초동 3
 
3.0%
교동 3
 
3.0%
만년동 3
 
3.0%
혜화동 3
 
3.0%
내동 2
 
2.0%
연지동 2
 
2.0%
웅진동 2
 
2.0%
송정동 2
 
2.0%
중계동 1
 
1.0%
Other values (74) 74
74.0%
2023-12-10T18:53:19.859635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 90
29.4%
읍 11
 
3.6%
가 10
 
3.3%
산 9
 
2.9%
서 7
 
2.3%
2 6
 
2.0%
숭 5
 
1.6%
성 5
 
1.6%
화 5
 
1.6%
교 4
 
1.3%
Other values (91) 154
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 297
97.1%
Decimal Number 9
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 90
30.3%
읍 11
 
3.7%
가 10
 
3.4%
산 9
 
3.0%
서 7
 
2.4%
숭 5
 
1.7%
성 5
 
1.7%
화 5
 
1.7%
교 4
 
1.3%
초 4
 
1.3%
Other values (88) 147
49.5%
Decimal Number
ValueCountFrequency (%)
2 6
66.7%
1 2
 
22.2%
4 1
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 297
97.1%
Common 9
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 90
30.3%
읍 11
 
3.7%
가 10
 
3.4%
산 9
 
3.0%
서 7
 
2.4%
숭 5
 
1.7%
성 5
 
1.7%
화 5
 
1.7%
교 4
 
1.3%
초 4
 
1.3%
Other values (88) 147
49.5%
Common
ValueCountFrequency (%)
2 6
66.7%
1 2
 
22.2%
4 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 297
97.1%
ASCII 9
 
2.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 90
30.3%
읍 11
 
3.7%
가 10
 
3.4%
산 9
 
3.0%
서 7
 
2.4%
숭 5
 
1.7%
성 5
 
1.7%
화 5
 
1.7%
교 4
 
1.3%
초 4
 
1.3%
Other values (88) 147
49.5%
ASCII
ValueCountFrequency (%)
2 6
66.7%
1 2
 
22.2%
4 1
 
11.1%

adstrd_cd
Real number (ℝ)

MISSING 

Distinct85
Distinct (%)86.7%
Missing2
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean2.9554337 × 109
Minimum1.111053 × 109
Maximum4.888025 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:20.351472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111053 × 109
5-th percentile1.111064 × 109
Q11.1440632 × 109
median2.9125703 × 109
Q34.426051 × 109
95-th percentile4.8182519 × 109
Maximum4.888025 × 109
Range3.776972 × 109
Interquartile range (IQR)3.2819878 × 109

Descriptive statistics

Standard deviation1.4803284 × 109
Coefficient of variation (CV)0.50088364
Kurtosis-1.636892
Mean2.9554337 × 109
Median Absolute Deviation (MAD)1.7430178 × 109
Skewness-0.12702991
Sum2.896325 × 1011
Variance2.1913721 × 1018
MonotonicityNot monotonic
2023-12-10T18:53:20.708214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1111064000 6
 
6.0%
1111065000 5
 
5.0%
3017065000 3
 
3.0%
1165053000 2
 
2.0%
4415054000 2
 
2.0%
4827031000 1
 
1.0%
1135061900 1
 
1.0%
4827055000 1
 
1.0%
2729051500 1
 
1.0%
4159058500 1
 
1.0%
Other values (75) 75
75.0%
(Missing) 2
 
2.0%
ValueCountFrequency (%)
1111053000 1
 
1.0%
1111063000 1
 
1.0%
1111064000 6
6.0%
1111065000 5
5.0%
1114052000 1
 
1.0%
1114055000 1
 
1.0%
1114057000 1
 
1.0%
1114058000 1
 
1.0%
1114060500 1
 
1.0%
1117055500 1
 
1.0%
ValueCountFrequency (%)
4888025000 1
1.0%
4831051000 1
1.0%
4827055000 1
1.0%
4827031000 1
1.0%
4825054000 1
1.0%
4817051500 1
1.0%
4728058000 1
1.0%
4719067000 1
1.0%
4719051000 1
1.0%
4715057500 1
1.0%

adstrd_nm
Text

MISSING 

Distinct84
Distinct (%)85.7%
Missing2
Missing (%)2.0%
Memory size932.0 B
2023-12-10T18:53:21.363023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.3061224
Min length2

Characters and Unicode

Total characters324
Distinct characters110
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

Unique78 ?
Unique (%)79.6%

Sample

1st row우2동
2nd row화순읍
3rd row상무1동
4th row남포동
5th row망미2동
ValueCountFrequency (%)
이화동 6
 
6.1%
혜화동 5
 
5.1%
만년동 3
 
3.1%
웅진동 2
 
2.0%
송정동 2
 
2.0%
서초3동 2
 
2.0%
대봉1동 1
 
1.0%
능동 1
 
1.0%
칠성동 1
 
1.0%
상중이동 1
 
1.0%
Other values (74) 74
75.5%
2023-12-10T18:53:22.352207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 90
27.8%
화 12
 
3.7%
읍 10
 
3.1%
2 10
 
3.1%
1 9
 
2.8%
이 7
 
2.2%
산 7
 
2.2%
성 7
 
2.2%
서 7
 
2.2%
3 6
 
1.9%
Other values (100) 159
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 294
90.7%
Decimal Number 29
 
9.0%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 90
30.6%
화 12
 
4.1%
읍 10
 
3.4%
이 7
 
2.4%
산 7
 
2.4%
성 7
 
2.4%
서 7
 
2.4%
혜 5
 
1.7%
진 4
 
1.4%
교 4
 
1.4%
Other values (93) 141
48.0%
Decimal Number
ValueCountFrequency (%)
2 10
34.5%
1 9
31.0%
3 6
20.7%
5 2
 
6.9%
6 1
 
3.4%
4 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 294
90.7%
Common 30
 
9.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 90
30.6%
화 12
 
4.1%
읍 10
 
3.4%
이 7
 
2.4%
산 7
 
2.4%
성 7
 
2.4%
서 7
 
2.4%
혜 5
 
1.7%
진 4
 
1.4%
교 4
 
1.4%
Other values (93) 141
48.0%
Common
ValueCountFrequency (%)
2 10
33.3%
1 9
30.0%
3 6
20.0%
5 2
 
6.7%
6 1
 
3.3%
. 1
 
3.3%
4 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 294
90.7%
ASCII 30
 
9.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 90
30.6%
화 12
 
4.1%
읍 10
 
3.4%
이 7
 
2.4%
산 7
 
2.4%
성 7
 
2.4%
서 7
 
2.4%
혜 5
 
1.7%
진 4
 
1.4%
교 4
 
1.4%
Other values (93) 141
48.0%
ASCII
ValueCountFrequency (%)
2 10
33.3%
1 9
30.0%
3 6
20.0%
5 2
 
6.7%
6 1
 
3.3%
. 1
 
3.3%
4 1
 
3.3%

rdnmaddr_cd
Real number (ℝ)

MISSING 

Distinct95
Distinct (%)96.9%
Missing2
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean2.9554115 × 1011
Minimum1.1110301 × 1011
Maximum4.8880335 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:22.826916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110301 × 1011
5-th percentile1.111041 × 1011
Q11.1440329 × 1011
median2.9125316 × 1011
Q34.4260426 × 1011
95-th percentile4.8182318 × 1011
Maximum4.8880335 × 1011
Range3.7770034 × 1011
Interquartile range (IQR)3.2820097 × 1011

Descriptive statistics

Standard deviation1.480334 × 1011
Coefficient of variation (CV)0.5008893
Kurtosis-1.636893
Mean2.9554115 × 1011
Median Absolute Deviation (MAD)1.7429958 × 1011
Skewness-0.12702373
Sum2.8963033 × 1013
Variance2.1913888 × 1022
MonotonicityNot monotonic
2023-12-10T18:53:23.206441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
301702166001 3
 
3.0%
111104100043 2
 
2.0%
482502335001 1
 
1.0%
272903147002 1
 
1.0%
111104100075 1
 
1.0%
302003167043 1
 
1.0%
471504718695 1
 
1.0%
271103141013 1
 
1.0%
272903147027 1
 
1.0%
271103141011 1
 
1.0%
Other values (85) 85
85.0%
(Missing) 2
 
2.0%
ValueCountFrequency (%)
111103005004 1
1.0%
111103100002 1
1.0%
111103100022 1
1.0%
111104100033 1
1.0%
111104100034 1
1.0%
111104100035 1
1.0%
111104100036 1
1.0%
111104100043 2
2.0%
111104100075 1
1.0%
111104100245 1
1.0%
ValueCountFrequency (%)
488803346035 1
1.0%
483103337039 1
1.0%
482703336075 1
1.0%
482703336020 1
1.0%
482502335001 1
1.0%
481703332003 1
1.0%
472803304021 1
1.0%
471903308087 1
1.0%
471902308004 1
1.0%
471504718695 1
1.0%

rdnm_addr
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:53:24.030181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length33
Mean length23.84
Min length11

Characters and Unicode

Total characters2384
Distinct characters209
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

Unique100 ?
Unique (%)100.0%

Sample

1st row부산광역시 해운대구 수영강변대로 120 (우동)
2nd row전라남도 화순군 학포로 2698 - 0 이용대체육관
3rd row광주광역시 서구 내방로 152 (쌍촌동)
4th row부산광역시 중구 구덕로34번길 4 (남포동2가)
5th row부산광역시 수영구 구락로123번길 20 (망미동)
ValueCountFrequency (%)
서울특별시 33
 
6.3%
종로구 13
 
2.5%
경기도 11
 
2.1%
중구 8
 
1.5%
부산광역시 7
 
1.3%
전라남도 7
 
1.3%
대구광역시 6
 
1.2%
경상북도 6
 
1.2%
서구 6
 
1.2%
충청남도 6
 
1.2%
Other values (351) 418
80.2%
2023-12-10T18:53:25.444689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
421
 
17.7%
동 102
 
4.3%
로 101
 
4.2%
시 97
 
4.1%
) 81
 
3.4%
( 81
 
3.4%
구 75
 
3.1%
1 60
 
2.5%
서 57
 
2.4%
도 49
 
2.1%
Other values (199) 1260
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1487
62.4%
Space Separator 421
 
17.7%
Decimal Number 303
 
12.7%
Close Punctuation 81
 
3.4%
Open Punctuation 81
 
3.4%
Dash Punctuation 6
 
0.3%
Uppercase Letter 3
 
0.1%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 102
 
6.9%
로 101
 
6.8%
시 97
 
6.5%
구 75
 
5.0%
서 57
 
3.8%
도 49
 
3.3%
광 38
 
2.6%
대 38
 
2.6%
산 35
 
2.4%
울 34
 
2.3%
Other values (182) 861
57.9%
Decimal Number
ValueCountFrequency (%)
1 60
19.8%
2 47
15.5%
3 41
13.5%
0 30
9.9%
5 25
8.3%
4 23
 
7.6%
8 22
 
7.3%
7 20
 
6.6%
6 19
 
6.3%
9 16
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
C 2
66.7%
J 1
33.3%
Space Separator
ValueCountFrequency (%)
421
100.0%
Close Punctuation
ValueCountFrequency (%)
) 81
100.0%
Open Punctuation
ValueCountFrequency (%)
( 81
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1487
62.4%
Common 894
37.5%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 102
 
6.9%
로 101
 
6.8%
시 97
 
6.5%
구 75
 
5.0%
서 57
 
3.8%
도 49
 
3.3%
광 38
 
2.6%
대 38
 
2.6%
산 35
 
2.4%
울 34
 
2.3%
Other values (182) 861
57.9%
Common
ValueCountFrequency (%)
421
47.1%
) 81
 
9.1%
( 81
 
9.1%
1 60
 
6.7%
2 47
 
5.3%
3 41
 
4.6%
0 30
 
3.4%
5 25
 
2.8%
4 23
 
2.6%
8 22
 
2.5%
Other values (5) 63
 
7.0%
Latin
ValueCountFrequency (%)
C 2
66.7%
J 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1487
62.4%
ASCII 897
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
421
46.9%
) 81
 
9.0%
( 81
 
9.0%
1 60
 
6.7%
2 47
 
5.2%
3 41
 
4.6%
0 30
 
3.3%
5 25
 
2.8%
4 23
 
2.6%
8 22
 
2.5%
Other values (7) 66
 
7.4%
Hangul
ValueCountFrequency (%)
동 102
 
6.9%
로 101
 
6.8%
시 97
 
6.5%
구 75
 
5.0%
서 57
 
3.8%
도 49
 
3.3%
광 38
 
2.6%
대 38
 
2.6%
산 35
 
2.4%
울 34
 
2.3%
Other values (182) 861
57.9%

zip_cd
Real number (ℝ)

MISSING 

Distinct90
Distinct (%)91.8%
Missing2
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean27819.184
Minimum1228
Maximum62362
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:25.746660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1228
5-th percentile3078.55
Q15009.5
median29134.5
Q347980
95-th percentile59278.45
Maximum62362
Range61134
Interquartile range (IQR)42970.5

Descriptive statistics

Standard deviation21091.222
Coefficient of variation (CV)0.75815386
Kurtosis-1.5403055
Mean27819.184
Median Absolute Deviation (MAD)21368
Skewness0.14099568
Sum2726280
Variance4.4483962 × 108
MonotonicityNot monotonic
2023-12-10T18:53:26.036895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3086 5
 
5.0%
35204 3
 
3.0%
32535 2
 
2.0%
3084 2
 
2.0%
42635 1
 
1.0%
41902 1
 
1.0%
41585 1
 
1.0%
41759 1
 
1.0%
42672 1
 
1.0%
31774 1
 
1.0%
Other values (80) 80
80.0%
(Missing) 2
 
2.0%
ValueCountFrequency (%)
1228 1
 
1.0%
1427 1
 
1.0%
1736 1
 
1.0%
3068 1
 
1.0%
3076 1
 
1.0%
3079 1
 
1.0%
3084 2
 
2.0%
3086 5
5.0%
3100 1
 
1.0%
3129 1
 
1.0%
ValueCountFrequency (%)
62362 1
1.0%
61965 1
1.0%
61485 1
1.0%
61104 1
1.0%
59536 1
1.0%
59233 1
1.0%
58672 1
1.0%
58526 1
1.0%
58149 1
1.0%
57734 1
1.0%

grid_cd
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:53:26.622388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters800
Distinct characters15
Distinct categories2 ?
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 row마라481874
2nd row다라515729
3rd row다라414849
4th row마라396792
5th row마라471879
ValueCountFrequency (%)
마라481874 1
 
1.0%
다마532024 1
 
1.0%
다바902187 1
 
1.0%
다바902197 1
 
1.0%
다바895188 1
 
1.0%
다바900187 1
 
1.0%
라마998626 1
 
1.0%
라마929623 1
 
1.0%
라마987649 1
 
1.0%
라마985657 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:53:27.561821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 102
12.8%
다 70
8.8%
6 70
8.8%
4 67
8.4%
2 62
 
7.8%
3 56
 
7.0%
1 55
 
6.9%
8 53
 
6.6%
사 50
 
6.2%
9 49
 
6.1%
Other values (5) 166
20.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 600
75.0%
Other Letter 200
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 102
17.0%
6 70
11.7%
4 67
11.2%
2 62
10.3%
3 56
9.3%
1 55
9.2%
8 53
8.8%
9 49
8.2%
7 47
7.8%
0 39
 
6.5%
Other Letter
ValueCountFrequency (%)
다 70
35.0%
사 50
25.0%
마 36
18.0%
라 35
17.5%
바 9
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common 600
75.0%
Hangul 200
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 102
17.0%
6 70
11.7%
4 67
11.2%
2 62
10.3%
3 56
9.3%
1 55
9.2%
8 53
8.8%
9 49
8.2%
7 47
7.8%
0 39
 
6.5%
Hangul
ValueCountFrequency (%)
다 70
35.0%
사 50
25.0%
마 36
18.0%
라 35
17.5%
바 9
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 600
75.0%
Hangul 200
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 102
17.0%
6 70
11.7%
4 67
11.2%
2 62
10.3%
3 56
9.3%
1 55
9.2%
8 53
8.8%
9 49
8.2%
7 47
7.8%
0 39
 
6.5%
Hangul
ValueCountFrequency (%)
다 70
35.0%
사 50
25.0%
마 36
18.0%
라 35
17.5%
바 9
 
4.5%

x_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.591124
Minimum34.615524
Maximum37.868024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:27.827162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.615524
5-th percentile34.989815
Q135.770407
median37.045205
Q337.563933
95-th percentile37.650433
Maximum37.868024
Range3.2524998
Interquartile range (IQR)1.7935265

Descriptive statistics

Standard deviation1.0407656
Coefficient of variation (CV)0.028443116
Kurtosis-1.4743083
Mean36.591124
Median Absolute Deviation (MAD)0.6126214
Skewness-0.37782895
Sum3659.1124
Variance1.083193
MonotonicityNot monotonic
2023-12-10T18:53:28.145921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.1710365 1
 
1.0%
35.8447674 1
 
1.0%
37.5832862 1
 
1.0%
36.3658578 1
 
1.0%
36.3749837 1
 
1.0%
36.3666138 1
 
1.0%
36.3663413 1
 
1.0%
35.855717 1
 
1.0%
35.8530247 1
 
1.0%
35.876059 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
34.6155245 1
1.0%
34.6381753 1
1.0%
34.8119114 1
1.0%
34.8671784 1
1.0%
34.9799443 1
1.0%
34.9903347 1
1.0%
35.0501241 1
1.0%
35.0982834 1
1.0%
35.1380982 1
1.0%
35.1437877 1
1.0%
ValueCountFrequency (%)
37.8680243 1
1.0%
37.8567514 1
1.0%
37.7716446 1
1.0%
37.6614856 1
1.0%
37.6541673 1
1.0%
37.6502369 1
1.0%
37.6490565 1
1.0%
37.6202545 1
1.0%
37.5955701 1
1.0%
37.5871832 1
1.0%

y_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.48522
Minimum126.43671
Maximum129.28887
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:28.523371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.43671
5-th percentile126.72372
Q1126.97224
median127.0415
Q3128.08941
95-th percentile129.09551
Maximum129.28887
Range2.8521545
Interquartile range (IQR)1.1171761

Descriptive statistics

Standard deviation0.81077999
Coefficient of variation (CV)0.0063597962
Kurtosis-0.47099023
Mean127.48522
Median Absolute Deviation (MAD)0.19525355
Skewness1.027991
Sum12748.522
Variance0.6573642
MonotonicityNot monotonic
2023-12-10T18:53:28.835103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.1270845 1
 
1.0%
128.5581018 1
 
1.0%
127.0032934 1
 
1.0%
127.3918502 1
 
1.0%
127.3916917 1
 
1.0%
127.3837588 1
 
1.0%
127.3893828 1
 
1.0%
128.6063616 1
 
1.0%
128.5295209 1
 
1.0%
128.5936972 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.4367126 1
1.0%
126.4720301 1
1.0%
126.6374833 1
1.0%
126.6798899 1
1.0%
126.7070369 1
1.0%
126.7245963 1
1.0%
126.7704992 1
1.0%
126.7744583 1
1.0%
126.7910155 1
1.0%
126.821969 1
1.0%
ValueCountFrequency (%)
129.2888671 1
1.0%
129.2059962 1
1.0%
129.1270845 1
1.0%
129.1155671 1
1.0%
129.1152394 1
1.0%
129.0944742 1
1.0%
129.090546 1
1.0%
129.0650787 1
1.0%
129.0541302 1
1.0%
129.032287 1
1.0%

usemem_total
Real number (ℝ)

ZEROS 

Distinct95
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12398.69
Minimum0
Maximum137252
Zeros6
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:29.106863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1646
median4051
Q313040
95-th percentile51802.65
Maximum137252
Range137252
Interquartile range (IQR)12394

Descriptive statistics

Standard deviation21214.258
Coefficient of variation (CV)1.711008
Kurtosis12.558519
Mean12398.69
Median Absolute Deviation (MAD)3759.5
Skewness3.1033046
Sum1239869
Variance4.5004476 × 108
MonotonicityNot monotonic
2023-12-10T18:53:29.539025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6
 
6.0%
17753 1
 
1.0%
8254 1
 
1.0%
137252 1
 
1.0%
3591 1
 
1.0%
526 1
 
1.0%
51436 1
 
1.0%
5000 1
 
1.0%
4215 1
 
1.0%
1337 1
 
1.0%
Other values (85) 85
85.0%
ValueCountFrequency (%)
0 6
6.0%
6 1
 
1.0%
10 1
 
1.0%
24 1
 
1.0%
50 1
 
1.0%
111 1
 
1.0%
126 1
 
1.0%
153 1
 
1.0%
156 1
 
1.0%
213 1
 
1.0%
ValueCountFrequency (%)
137252 1
1.0%
75560 1
1.0%
74664 1
1.0%
63296 1
1.0%
58769 1
1.0%
51436 1
1.0%
51061 1
1.0%
45229 1
1.0%
44273 1
1.0%
43930 1
1.0%

sccnt
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9748.49
Minimum0
Maximum146750
Zeros79
Zeros (%)79.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:29.957674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile76756.7
Maximum146750
Range146750
Interquartile range (IQR)0

Descriptive statistics

Standard deviation26659.104
Coefficient of variation (CV)2.7346906
Kurtosis10.076877
Mean9748.49
Median Absolute Deviation (MAD)0
Skewness3.1754828
Sum974849
Variance7.107078 × 108
MonotonicityNot monotonic
2023-12-10T18:53:30.263304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 79
79.0%
10358 1
 
1.0%
2801 1
 
1.0%
10739 1
 
1.0%
27448 1
 
1.0%
99660 1
 
1.0%
146750 1
 
1.0%
85966 1
 
1.0%
71647 1
 
1.0%
29644 1
 
1.0%
Other values (12) 12
 
12.0%
ValueCountFrequency (%)
0 79
79.0%
2801 1
 
1.0%
3267 1
 
1.0%
3928 1
 
1.0%
9132 1
 
1.0%
10358 1
 
1.0%
10415 1
 
1.0%
10739 1
 
1.0%
22887 1
 
1.0%
23820 1
 
1.0%
ValueCountFrequency (%)
146750 1
1.0%
103626 1
1.0%
99660 1
1.0%
87901 1
1.0%
85966 1
1.0%
76272 1
1.0%
72623 1
1.0%
71647 1
1.0%
49355 1
1.0%
29644 1
1.0%

search_rate
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0035792809
Minimum0
Maximum0.053881111
Zeros79
Zeros (%)79.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:30.701515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.028182189
Maximum0.053881111
Range0.053881111
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0097882256
Coefficient of variation (CV)2.7346906
Kurtosis10.076877
Mean0.0035792809
Median Absolute Deviation (MAD)0
Skewness3.1754827
Sum0.35792809
Variance9.5809361 × 10-5
MonotonicityNot monotonic
2023-12-10T18:53:31.031722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.0 79
79.0%
0.0038030701 1
 
1.0%
0.0010284224 1
 
1.0%
0.0039429591 1
 
1.0%
0.0100778789 1
 
1.0%
0.036591424 1
 
1.0%
0.0538811105 1
 
1.0%
0.0315634995 1
 
1.0%
0.0263060983 1
 
1.0%
0.0108841679 1
 
1.0%
Other values (12) 12
 
12.0%
ValueCountFrequency (%)
0.0 79
79.0%
0.0010284224 1
 
1.0%
0.0011995202 1
 
1.0%
0.0014422147 1
 
1.0%
0.0033529288 1
 
1.0%
0.0038030701 1
 
1.0%
0.0038239984 1
 
1.0%
0.0039429591 1
 
1.0%
0.0084032503 1
 
1.0%
0.008745813 1
 
1.0%
ValueCountFrequency (%)
0.0538811105 1
1.0%
0.0380475909 1
1.0%
0.036591424 1
1.0%
0.0322739591 1
1.0%
0.0315634995 1
1.0%
0.0280042253 1
1.0%
0.026664449 1
1.0%
0.0263060983 1
1.0%
0.0181213098 1
1.0%
0.0108841679 1
1.0%

file_name
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC_605_PLAY_STT_INVT_FRCSTA_2021
100 

Length

Max length32
Median length32
Mean length32
Min length32

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_605_PLAY_STT_INVT_FRCSTA_2021
2nd rowKC_605_PLAY_STT_INVT_FRCSTA_2021
3rd rowKC_605_PLAY_STT_INVT_FRCSTA_2021
4th rowKC_605_PLAY_STT_INVT_FRCSTA_2021
5th rowKC_605_PLAY_STT_INVT_FRCSTA_2021

Common Values

ValueCountFrequency (%)
KC_605_PLAY_STT_INVT_FRCSTA_2021 100
100.0%

Length

2023-12-10T18:53:31.285225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:53:31.453183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_605_play_stt_invt_frcsta_2021 100
100.0%

base_ymd
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20200101
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20200101
2nd row20200101
3rd row20200101
4th row20200101
5th row20200101

Common Values

ValueCountFrequency (%)
20200101 100
100.0%

Length

2023-12-10T18:53:31.626296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:53:31.803092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20200101 100
100.0%

Sample

idlclasmlsfcfclt_namectprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrzip_cdgrid_cdx_cdy_cdusemem_totalsccntsearch_ratefile_namebase_ymd
0KC5PSIF21N000000065문화시설공연장(재)영화의전당부산광역시해운대구2635010500우동2635052000우2동263502133002부산광역시 해운대구 수영강변대로 120 (우동)48058마라48187435.171036129.1270841775300.0KC_605_PLAY_STT_INVT_FRCSTA_202120200101
1KC5PSIF21N000000237문화시설공연장화순 하니움 문화스포츠센터전라남도화순군4679025000화순읍4679025000화순읍467903291038전라남도 화순군 학포로 2698 - 0 이용대체육관58149다라51572935.050124126.96861311100.0KC_605_PLAY_STT_INVT_FRCSTA_202120200101
2KC5PSIF21N000000118문화시설공연장5.18기념문화센터광주광역시서구2914011800쌍촌동2914075100상무1동291403160004광주광역시 서구 내방로 152 (쌍촌동)61965다라41484935.158305126.857556322700.0KC_605_PLAY_STT_INVT_FRCSTA_202120200101
3KC5PSIF21N000000036문화시설공연장BNK부산은행 조은극장부산광역시중구2611013700남포동2가2611058000남포동261104175026부산광역시 중구 구덕로34번길 4 (남포동2가)48954마라39679235.098283129.032287813700.0KC_605_PLAY_STT_INVT_FRCSTA_202120200101
4KC5PSIF21N000000116문화시설공연장F1963부산광역시수영구2650010100망미동2650075000망미2동265004214104부산광역시 수영구 구락로123번길 20 (망미동)48212마라47187935.176235129.11556746400.0KC_605_PLAY_STT_INVT_FRCSTA_202120200101
5KC5PSIF21N000000168문화시설공연장JCC 아트센터서울특별시종로구1111016900혜화동1111065000혜화동111104100418서울특별시 종로구 창경궁로35길 29 (혜화동) JCC 아트센터3076다사56054337.587183127.001886116500.0KC_605_PLAY_STT_INVT_FRCSTA_202120200101
6KC5PSIF21N000000028문화시설공연장JTN 아트홀(구. 대학로예술마당)서울특별시종로구1111016500이화동1111064000이화동111104100245서울특별시 종로구 이화장길 26 (이화동)3100다사56153137.576644127.0039321510700.0KC_605_PLAY_STT_INVT_FRCSTA_202120200101
7KC5PSIF21N000000223문화시설공연장후용공연예술센터강원도원주시4213025000문막읍4213025000문막읍421304457303강원도 원주시 문막읍 비야동길 1126495라사26719437.273983127.8022491000.0KC_605_PLAY_STT_INVT_FRCSTA_202120200101
8KC5PSIF21N000000119문화시설공연장가온아트홀 [부산]부산광역시동구2617010400범일동2617066000범일2동261703127052부산광역시 동구 자성로 133번길 1048742마라42583635.138098129.06507915300.0KC_605_PLAY_STT_INVT_FRCSTA_202120200101
9KC5PSIF21N000000073문화시설공연장가정청소년문화의집인천광역시서구2826010800가정동2826054400가정3동282603154071인천광역시 서구 서달로 190 (가정동)22799다사27546537.515699126.67989633900.0KC_605_PLAY_STT_INVT_FRCSTA_202120200101
idlclasmlsfcfclt_namectprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrzip_cdgrid_cdx_cdy_cdusemem_totalsccntsearch_ratefile_namebase_ymd
90KC5PSIF21N000000135문화시설공연장목포시민문화체육센터전라남도목포시4611016400옥암동4611079000옥암동461103281025전라남도 목포시 부주로 312 (옥암동)58672다라02746834.811911126.436713767500.0KC_605_PLAY_STT_INVT_FRCSTA_202120200101
91KC5PSIF21N000000179문화시설공연장무안승달문화예술회관전라남도무안군4684025000무안읍4684025000무안읍468403296035전라남도 무안군 창포로 858526다라06166634.990335126.4720315600.0KC_605_PLAY_STT_INVT_FRCSTA_202120200101
92KC5PSIF21N000000130문화시설공연장문경문화예술회관경상북도문경시4728010100점촌동4728058000점촌2동472803304021경상북도 문경시 신흥로 85 (점촌동)36948라바62443836.590038128.197779459900.0KC_605_PLAY_STT_INVT_FRCSTA_202120200101
93KC5PSIF21N000000178문화시설공연장문산행복센터경기도파주시4148025000문산읍4148025000문산읍414803000008경기도 파주시 문산읍 통일로 168010813다사37684337.856751126.791016437274480.010078KC_605_PLAY_STT_INVT_FRCSTA_202120200101
94KC5PSIF21N000000210문화시설공연장문화비축기지서울특별시마포구1144012500성산동1144073000성산2동114403005056서울특별시 마포구 증산로 87 (성산동)3914다사46552537.570347126.895031000.0KC_605_PLAY_STT_INVT_FRCSTA_202120200101
95KC5PSIF21N000000109문화시설공연장미마지아트센터서울특별시종로구1111017000명륜1가1111065000혜화동111103100022서울특별시 종로구 혜화로 17 (명륜1가)3068다사55854337.58711126.999785784500.0KC_605_PLAY_STT_INVT_FRCSTA_202120200101
96KC5PSIF21N000000022문화시설공연장민송아트홀 (구. 브로드웨이아트홀)서울특별시종로구1111016900혜화동1111065000혜화동111103100002서울특별시 종로구 대학로 144 (혜화동) 중원빌딩 6층3084다사56053937.583982127.0020653491800.0KC_605_PLAY_STT_INVT_FRCSTA_202120200101
97KC5PSIF21N000000083문화시설공연장밀양아리나(구, 밀양연극촌)경상남도밀양시4827031000부북면4827031000부북면482703336075경상남도 밀양시 부북면 창밀로 3097-1650401마마09227035.533476128.70461612600.0KC_605_PLAY_STT_INVT_FRCSTA_202120200101
98KC5PSIF21N000000097문화시설공연장밀양아리랑아트센터경상남도밀양시4827010300교동4827055000교동482703336020경상남도 밀양시 밀양대공원로 112 (교동)50420마마14123835.504426128.758515277107390.003943KC_605_PLAY_STT_INVT_FRCSTA_202120200101
99KC5PSIF21N000000151문화시설공연장반석아트홀경기도화성시4159012700반송동4159058500동탄1동415903210025경기도 화성시 노작로 134 (반송동)18459다사62211437.200688127.075122380328010.001028KC_605_PLAY_STT_INVT_FRCSTA_202120200101