Overview

Dataset statistics

Number of variables39
Number of observations100
Missing cells25
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.6 KiB
Average record size in memory323.3 B

Variable types

Text9
Categorical19
Numeric8
Boolean3

Alerts

lclas has constant value ""Constant
mlsfc has constant value ""Constant
data_orgn has constant value ""Constant
FILE_NAME has constant value ""Constant
base_ymd has constant value ""Constant
infbru_intr has 4 (4.0%) missing valuesMissing
en_gud_psbl_yn has 5 (5.0%) missing valuesMissing
jp_gud_psbl_yn has 7 (7.0%) missing valuesMissing
cn_gud_psbl_yn has 7 (7.0%) missing valuesMissing
id has unique valuesUnique
lst_updt_dt has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:05:50.205258
Analysis finished2023-12-10 10:05:51.997300
Duration1.79 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
2023-12-10T19:05:52.254341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters1600
Distinct characters14
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 rowKC489PC19N000001
2nd rowKC489PC19N000002
3rd rowKC489PC19N000003
4th rowKC489PC19N000004
5th rowKC489PC19N000005
ValueCountFrequency (%)
kc489pc19n000001 1
 
1.0%
kc489pc19n000063 1
 
1.0%
kc489pc19n000074 1
 
1.0%
kc489pc19n000073 1
 
1.0%
kc489pc19n000072 1
 
1.0%
kc489pc19n000071 1
 
1.0%
kc489pc19n000070 1
 
1.0%
kc489pc19n000069 1
 
1.0%
kc489pc19n000068 1
 
1.0%
kc489pc19n000067 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:05:52.882271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 419
26.2%
9 220
13.8%
C 200
12.5%
1 123
 
7.7%
4 120
 
7.5%
8 119
 
7.4%
K 100
 
6.2%
P 100
 
6.2%
N 100
 
6.2%
3 20
 
1.2%
Other values (4) 79
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1100
68.8%
Uppercase Letter 500
31.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 419
38.1%
9 220
20.0%
1 123
 
11.2%
4 120
 
10.9%
8 119
 
10.8%
3 20
 
1.8%
5 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
2 19
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
C 200
40.0%
K 100
20.0%
P 100
20.0%
N 100
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1100
68.8%
Latin 500
31.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 419
38.1%
9 220
20.0%
1 123
 
11.2%
4 120
 
10.9%
8 119
 
10.8%
3 20
 
1.8%
5 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
2 19
 
1.7%
Latin
ValueCountFrequency (%)
C 200
40.0%
K 100
20.0%
P 100
20.0%
N 100
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 419
26.2%
9 220
13.8%
C 200
12.5%
1 123
 
7.7%
4 120
 
7.5%
8 119
 
7.4%
K 100
 
6.2%
P 100
 
6.2%
N 100
 
6.2%
3 20
 
1.2%
Other values (4) 79
 
4.9%

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

2023-12-10T19:05:53.179056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:05:53.356801image/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
관광안내소
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광안내소 100
100.0%

Length

2023-12-10T19:05:53.540984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:05:53.713187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광안내소 100
100.0%

fclt_name
Text

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:05:54.284748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17.5
Mean length9.65
Min length5

Characters and Unicode

Total characters965
Distinct characters158
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)93.0%

Sample

1st row성안길관광안내소
2nd row수암골관광안내소
3rd row신촌플레이버스
4th row강원도 화천군 관광안내소(터미널)
5th row영동군 관광안내소
ValueCountFrequency (%)
관광안내소 24
 
16.7%
종합관광안내소 4
 
2.8%
대구관광정보센터 3
 
2.1%
터미널관광안내소 2
 
1.4%
김대중센터 2
 
1.4%
광주송정역 2
 
1.4%
용인시 2
 
1.4%
안내센터 2
 
1.4%
안산역관광안내소 1
 
0.7%
시간여행마을안내소 1
 
0.7%
Other values (101) 101
70.1%
2023-12-10T19:05:54.943687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
안 90
 
9.3%
광 88
 
9.1%
내 86
 
8.9%
관 85
 
8.8%
소 81
 
8.4%
44
 
4.6%
역 19
 
2.0%
터 18
 
1.9%
산 13
 
1.3%
사 13
 
1.3%
Other values (148) 428
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 897
93.0%
Space Separator 44
 
4.6%
Close Punctuation 11
 
1.1%
Open Punctuation 11
 
1.1%
Decimal Number 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 90
 
10.0%
광 88
 
9.8%
내 86
 
9.6%
관 85
 
9.5%
소 81
 
9.0%
역 19
 
2.1%
터 18
 
2.0%
산 13
 
1.4%
사 13
 
1.4%
대 12
 
1.3%
Other values (143) 392
43.7%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 897
93.0%
Common 68
 
7.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 90
 
10.0%
광 88
 
9.8%
내 86
 
9.6%
관 85
 
9.5%
소 81
 
9.0%
역 19
 
2.1%
터 18
 
2.0%
산 13
 
1.4%
사 13
 
1.4%
대 12
 
1.3%
Other values (143) 392
43.7%
Common
ValueCountFrequency (%)
44
64.7%
) 11
 
16.2%
( 11
 
16.2%
1 1
 
1.5%
2 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 897
93.0%
ASCII 68
 
7.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
안 90
 
10.0%
광 88
 
9.8%
내 86
 
9.6%
관 85
 
9.5%
소 81
 
9.0%
역 19
 
2.1%
터 18
 
2.0%
산 13
 
1.4%
사 13
 
1.4%
대 12
 
1.3%
Other values (143) 392
43.7%
ASCII
ValueCountFrequency (%)
44
64.7%
) 11
 
16.2%
( 11
 
16.2%
1 1
 
1.5%
2 1
 
1.5%

ctprvn_nm
Categorical

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경상남도
19 
경기도
11 
강원도
10 
광주광역시
9 
전라북도
9 
Other values (9)
42 

Length

Max length5
Median length4
Mean length4.05
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row충청북도
2nd row충청북도
3rd row서울특별시
4th row강원도
5th row충청북도

Common Values

ValueCountFrequency (%)
경상남도 19
19.0%
경기도 11
11.0%
강원도 10
10.0%
광주광역시 9
9.0%
전라북도 9
9.0%
충청북도 7
 
7.0%
전라남도 7
 
7.0%
대구광역시 7
 
7.0%
경상북도 6
 
6.0%
대전광역시 5
 
5.0%
Other values (4) 10
10.0%

Length

2023-12-10T19:05:55.173107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경상남도 19
19.0%
경기도 11
11.0%
강원도 10
10.0%
광주광역시 9
9.0%
전라북도 9
9.0%
충청북도 7
 
7.0%
전라남도 7
 
7.0%
대구광역시 7
 
7.0%
경상북도 6
 
6.0%
대전광역시 5
 
5.0%
Other values (4) 10
10.0%

sgnr_nm
Categorical

Distinct44
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
군산시
 
6
남해군
 
6
강릉시
 
6
의령군
 
6
장성군
 
5
Other values (39)
71 

Length

Max length7
Median length3
Mean length3.19
Min length2

Unique

Unique24 ?
Unique (%)24.0%

Sample

1st row청주시 청원구
2nd row청주시 청원구
3rd row서대문구
4th row화천군
5th row영동군

Common Values

ValueCountFrequency (%)
군산시 6
 
6.0%
남해군 6
 
6.0%
강릉시 6
 
6.0%
의령군 6
 
6.0%
장성군 5
 
5.0%
동구 5
 
5.0%
경주시 5
 
5.0%
북구 4
 
4.0%
함양군 4
 
4.0%
달서구 4
 
4.0%
Other values (34) 49
49.0%

Length

2023-12-10T19:05:55.409798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
군산시 6
 
5.6%
강릉시 6
 
5.6%
의령군 6
 
5.6%
남해군 6
 
5.6%
장성군 5
 
4.6%
동구 5
 
4.6%
경주시 5
 
4.6%
함양군 4
 
3.7%
달서구 4
 
3.7%
북구 4
 
3.7%
Other values (38) 57
52.8%

legaldong_cd
Real number (ℝ)

Distinct92
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0769862 × 109
Minimum1.1410116 × 109
Maximum4.887036 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:05:55.647707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1410116 × 109
5-th percentile2.7230111 × 109
Q13.133282 × 109
median4.3730283 × 109
Q34.6942826 × 109
95-th percentile4.884039 × 109
Maximum4.887036 × 109
Range3.7460244 × 109
Interquartile range (IQR)1.5610006 × 109

Descriptive statistics

Standard deviation8.2126193 × 108
Coefficient of variation (CV)0.20143849
Kurtosis0.31580808
Mean4.0769862 × 109
Median Absolute Deviation (MAD)3.3998233 × 108
Skewness-1.0897161
Sum4.0769862 × 1011
Variance6.7447116 × 1017
MonotonicityNot monotonic
2023-12-10T19:05:55.940118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2729010200 4
 
4.0%
4311410100 2
 
2.0%
4872025022 2
 
2.0%
2914012000 2
 
2.0%
2617010100 2
 
2.0%
2920010100 2
 
2.0%
2917010100 1
 
1.0%
2914011500 1
 
1.0%
4127310800 1
 
1.0%
4127311100 1
 
1.0%
Other values (82) 82
82.0%
ValueCountFrequency (%)
1141011600 1
 
1.0%
2617010100 2
2.0%
2638010800 1
 
1.0%
2723010200 1
 
1.0%
2723011100 1
 
1.0%
2723012300 1
 
1.0%
2729010200 4
4.0%
2911011300 1
 
1.0%
2914011500 1
 
1.0%
2914012000 2
2.0%
ValueCountFrequency (%)
4887036032 1
1.0%
4887035021 1
1.0%
4887034028 1
1.0%
4887025024 1
1.0%
4884039024 1
1.0%
4884039022 1
1.0%
4884037028 1
1.0%
4884035023 1
1.0%
4884033025 1
1.0%
4884025023 1
1.0%

legalemd_nm
Text

Distinct83
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:05:56.421282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.03
Min length2

Characters and Unicode

Total characters303
Distinct characters95
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

Unique69 ?
Unique (%)69.0%

Sample

1st row우암동
2nd row우암동
3rd row창천동
4th row화천읍
5th row영동읍
ValueCountFrequency (%)
두류동 4
 
4.0%
의령읍 3
 
3.0%
치평동 2
 
2.0%
우암동 2
 
2.0%
창선면 2
 
2.0%
초량동 2
 
2.0%
송정동 2
 
2.0%
옥도면 2
 
2.0%
교동 2
 
2.0%
단양읍 2
 
2.0%
Other values (73) 77
77.0%
2023-12-10T19:05:57.303360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 55
 
18.2%
면 28
 
9.2%
읍 21
 
6.9%
천 7
 
2.3%
정 7
 
2.3%
류 6
 
2.0%
곡 6
 
2.0%
산 5
 
1.7%
양 5
 
1.7%
의 5
 
1.7%
Other values (85) 158
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 301
99.3%
Decimal Number 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 55
 
18.3%
면 28
 
9.3%
읍 21
 
7.0%
천 7
 
2.3%
정 7
 
2.3%
류 6
 
2.0%
곡 6
 
2.0%
산 5
 
1.7%
양 5
 
1.7%
의 5
 
1.7%
Other values (83) 156
51.8%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 301
99.3%
Common 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 55
 
18.3%
면 28
 
9.3%
읍 21
 
7.0%
천 7
 
2.3%
정 7
 
2.3%
류 6
 
2.0%
곡 6
 
2.0%
산 5
 
1.7%
양 5
 
1.7%
의 5
 
1.7%
Other values (83) 156
51.8%
Common
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 301
99.3%
ASCII 2
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 55
 
18.3%
면 28
 
9.3%
읍 21
 
7.0%
천 7
 
2.3%
정 7
 
2.3%
류 6
 
2.0%
곡 6
 
2.0%
산 5
 
1.7%
양 5
 
1.7%
의 5
 
1.7%
Other values (83) 156
51.8%
ASCII
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%

adstrd_cd
Real number (ℝ)

Distinct83
Distinct (%)83.8%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean4.0887869 × 109
Minimum1.1410585 × 109
Maximum4.887036 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:05:57.594312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1410585 × 109
5-th percentile2.7230611 × 109
Q13.6430455 × 109
median4.374025 × 109
Q34.7005328 × 109
95-th percentile4.884039 × 109
Maximum4.887036 × 109
Range3.7459775 × 109
Interquartile range (IQR)1.0574873 × 109

Descriptive statistics

Standard deviation8.1689406 × 108
Coefficient of variation (CV)0.19978886
Kurtosis0.44754039
Mean4.0887869 × 109
Median Absolute Deviation (MAD)3.390006 × 108
Skewness-1.13264
Sum4.047899 × 1011
Variance6.6731591 × 1017
MonotonicityNot monotonic
2023-12-10T19:05:57.951456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4872025000 3
 
3.0%
2729055000 3
 
3.0%
4311451000 2
 
2.0%
2617053000 2
 
2.0%
4513039000 2
 
2.0%
4513053000 2
 
2.0%
4884039000 2
 
2.0%
2914074500 2
 
2.0%
4380025000 2
 
2.0%
2920052500 2
 
2.0%
Other values (73) 77
77.0%
ValueCountFrequency (%)
1141058500 1
 
1.0%
2617053000 2
2.0%
2638063000 1
 
1.0%
2723052600 1
 
1.0%
2723062000 1
 
1.0%
2723074500 1
 
1.0%
2729053500 1
 
1.0%
2729055000 3
3.0%
2914073000 1
 
1.0%
2914074500 2
2.0%
ValueCountFrequency (%)
4887036000 1
1.0%
4887035000 1
1.0%
4887034000 1
1.0%
4887025000 1
1.0%
4884039000 2
2.0%
4884037000 1
1.0%
4884035000 1
1.0%
4884033000 1
1.0%
4884025000 1
1.0%
4872042000 1
1.0%

adstrd_nm
Text

Distinct78
Distinct (%)78.8%
Missing1
Missing (%)1.0%
Memory size932.0 B
2023-12-10T19:05:58.481159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.2323232
Min length2

Characters and Unicode

Total characters320
Distinct characters96
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

Unique62 ?
Unique (%)62.6%

Sample

1st row우암동
2nd row우암동
3rd row신촌동
4th row화천읍
5th row영동읍
ValueCountFrequency (%)
중앙동 5
 
5.1%
두류3동 3
 
3.0%
의령읍 3
 
3.0%
북하면 2
 
2.0%
창선면 2
 
2.0%
초량제3동 2
 
2.0%
월명동 2
 
2.0%
우암동 2
 
2.0%
송정2동 2
 
2.0%
옥도면 2
 
2.0%
Other values (68) 74
74.7%
2023-12-10T19:05:59.306425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 55
 
17.2%
면 28
 
8.8%
읍 21
 
6.6%
2 8
 
2.5%
중 7
 
2.2%
류 6
 
1.9%
천 6
 
1.9%
암 5
 
1.6%
양 5
 
1.6%
산 5
 
1.6%
Other values (86) 174
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 302
94.4%
Decimal Number 17
 
5.3%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 55
 
18.2%
면 28
 
9.3%
읍 21
 
7.0%
중 7
 
2.3%
류 6
 
2.0%
천 6
 
2.0%
암 5
 
1.7%
양 5
 
1.7%
산 5
 
1.7%
앙 5
 
1.7%
Other values (82) 159
52.6%
Decimal Number
ValueCountFrequency (%)
2 8
47.1%
3 5
29.4%
1 4
23.5%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 302
94.4%
Common 18
 
5.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 55
 
18.2%
면 28
 
9.3%
읍 21
 
7.0%
중 7
 
2.3%
류 6
 
2.0%
천 6
 
2.0%
암 5
 
1.7%
양 5
 
1.7%
산 5
 
1.7%
앙 5
 
1.7%
Other values (82) 159
52.6%
Common
ValueCountFrequency (%)
2 8
44.4%
3 5
27.8%
1 4
22.2%
. 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 302
94.4%
ASCII 18
 
5.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 55
 
18.2%
면 28
 
9.3%
읍 21
 
7.0%
중 7
 
2.3%
류 6
 
2.0%
천 6
 
2.0%
암 5
 
1.7%
양 5
 
1.7%
산 5
 
1.7%
앙 5
 
1.7%
Other values (82) 159
52.6%
ASCII
ValueCountFrequency (%)
2 8
44.4%
3 5
27.8%
1 4
22.2%
. 1
 
5.6%

rdnmaddr_cd
Real number (ℝ)

Distinct91
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0769994 × 1011
Minimum1.1410414 × 1011
Maximum4.8870484 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:05:59.755726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1410414 × 1011
5-th percentile2.7230314 × 1011
Q13.1332817 × 1011
median4.3730324 × 1011
Q34.694291 × 1011
95-th percentile4.8840342 × 1011
Maximum4.8870484 × 1011
Range3.746007 × 1011
Interquartile range (IQR)1.5610093 × 1011

Descriptive statistics

Standard deviation8.2125754 × 1010
Coefficient of variation (CV)0.20143676
Kurtosis0.31581085
Mean4.0769994 × 1011
Median Absolute Deviation (MAD)3.3999563 × 1010
Skewness-1.0897232
Sum4.0769994 × 1013
Variance6.7446394 × 1021
MonotonicityNot monotonic
2023-12-10T19:06:00.132541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
292002009004 3
 
3.0%
272903147002 3
 
3.0%
431143236034 2
 
2.0%
421503220050 2
 
2.0%
291403160016 2
 
2.0%
487203339041 2
 
2.0%
488402343003 2
 
2.0%
412733191019 1
 
1.0%
291103159006 1
 
1.0%
291702009011 1
 
1.0%
Other values (81) 81
81.0%
ValueCountFrequency (%)
114104136241 1
 
1.0%
261702000010 1
 
1.0%
261702006001 1
 
1.0%
263803134002 1
 
1.0%
272303141011 1
 
1.0%
272303145012 1
 
1.0%
272303351535 1
 
1.0%
272903007009 1
 
1.0%
272903147002 3
3.0%
291103159006 1
 
1.0%
ValueCountFrequency (%)
488704838452 1
1.0%
488704838072 1
1.0%
488703346017 1
1.0%
488703346010 1
1.0%
488404829204 1
1.0%
488403343046 1
1.0%
488403343011 1
1.0%
488402343003 2
2.0%
488402343002 1
1.0%
487204817403 1
1.0%

rdnm_addr
Text

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:06:00.773287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length22.49
Min length17

Characters and Unicode

Total characters2249
Distinct characters189
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

Unique93 ?
Unique (%)93.0%

Sample

1st row충청북도 청주시 청원구 수암로 82 (우암동)
2nd row충청북도 청주시 청원구 수암로 78-1 (우암동)
3rd row서울특별시 서대문구 연세로5길 26-9 (창천동)
4th row강원도 화천군 화천읍 상승로 38-5
5th row충청북도 영동군 영동읍 계산로 87
ValueCountFrequency (%)
경상남도 19
 
3.7%
경기도 11
 
2.2%
강원도 10
 
2.0%
전라북도 9
 
1.8%
광주광역시 9
 
1.8%
대구광역시 7
 
1.4%
전라남도 7
 
1.4%
충청북도 7
 
1.4%
군산시 6
 
1.2%
의령군 6
 
1.2%
Other values (311) 420
82.2%
2023-12-10T19:06:01.810946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
411
 
18.3%
로 86
 
3.8%
도 79
 
3.5%
동 70
 
3.1%
시 64
 
2.8%
1 62
 
2.8%
( 51
 
2.3%
) 51
 
2.3%
남 50
 
2.2%
구 45
 
2.0%
Other values (179) 1280
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1412
62.8%
Space Separator 411
 
18.3%
Decimal Number 306
 
13.6%
Open Punctuation 51
 
2.3%
Close Punctuation 51
 
2.3%
Dash Punctuation 16
 
0.7%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 86
 
6.1%
도 79
 
5.6%
동 70
 
5.0%
시 64
 
4.5%
남 50
 
3.5%
구 45
 
3.2%
군 43
 
3.0%
경 42
 
3.0%
광 40
 
2.8%
원 32
 
2.3%
Other values (164) 861
61.0%
Decimal Number
ValueCountFrequency (%)
1 62
20.3%
2 44
14.4%
3 34
11.1%
0 31
10.1%
7 27
8.8%
4 24
 
7.8%
8 23
 
7.5%
9 22
 
7.2%
6 21
 
6.9%
5 18
 
5.9%
Space Separator
ValueCountFrequency (%)
411
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1412
62.8%
Common 837
37.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 86
 
6.1%
도 79
 
5.6%
동 70
 
5.0%
시 64
 
4.5%
남 50
 
3.5%
구 45
 
3.2%
군 43
 
3.0%
경 42
 
3.0%
광 40
 
2.8%
원 32
 
2.3%
Other values (164) 861
61.0%
Common
ValueCountFrequency (%)
411
49.1%
1 62
 
7.4%
( 51
 
6.1%
) 51
 
6.1%
2 44
 
5.3%
3 34
 
4.1%
0 31
 
3.7%
7 27
 
3.2%
4 24
 
2.9%
8 23
 
2.7%
Other values (5) 79
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1412
62.8%
ASCII 837
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
411
49.1%
1 62
 
7.4%
( 51
 
6.1%
) 51
 
6.1%
2 44
 
5.3%
3 34
 
4.1%
0 31
 
3.7%
7 27
 
3.2%
4 24
 
2.9%
8 23
 
2.7%
Other values (5) 79
 
9.4%
Hangul
ValueCountFrequency (%)
로 86
 
6.1%
도 79
 
5.6%
동 70
 
5.0%
시 64
 
4.5%
남 50
 
3.5%
구 45
 
3.2%
군 43
 
3.0%
경 42
 
3.0%
광 40
 
2.8%
원 32
 
2.3%
Other values (164) 861
61.0%

zip_cd
Real number (ℝ)

Distinct92
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40861.71
Minimum3789
Maximum62429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:06:02.130095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3789
5-th percentile12640.75
Q128135.5
median42672
Q352837.5
95-th percentile61938.05
Maximum62429
Range58640
Interquartile range (IQR)24702

Descriptive statistics

Standard deviation15433.747
Coefficient of variation (CV)0.37770683
Kurtosis-0.88834196
Mean40861.71
Median Absolute Deviation (MAD)11450.5
Skewness-0.45882978
Sum4086171
Variance2.3820055 × 108
MonotonicityNot monotonic
2023-12-10T19:06:02.404246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42672 3
 
3.0%
28506 2
 
2.0%
57223 2
 
2.0%
62429 2
 
2.0%
61958 2
 
2.0%
52152 2
 
2.0%
54000 2
 
2.0%
11027 1
 
1.0%
31470 1
 
1.0%
61640 1
 
1.0%
Other values (82) 82
82.0%
ValueCountFrequency (%)
3789 1
1.0%
10093 1
1.0%
11027 1
1.0%
11673 1
1.0%
12636 1
1.0%
12641 1
1.0%
12650 1
1.0%
15391 1
1.0%
15638 1
1.0%
17023 1
1.0%
ValueCountFrequency (%)
62429 2
2.0%
62425 1
1.0%
61958 2
2.0%
61937 1
1.0%
61640 1
1.0%
61485 1
1.0%
61226 1
1.0%
57337 1
1.0%
57231 1
1.0%
57223 2
2.0%

grid_cd
Text

Distinct95
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:06:02.840610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters800
Distinct characters16
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

Unique91 ?
Unique (%)91.0%

Sample

1st row다바994501
2nd row다바994501
3rd row다사500509
4th row라아179116
5th row라마257972
ValueCountFrequency (%)
라마955621 3
 
3.0%
다라399837 2
 
2.0%
다바994501 2
 
2.0%
다라353826 2
 
2.0%
마마004684 1
 
1.0%
다라471836 1
 
1.0%
다라461858 1
 
1.0%
다라435852 1
 
1.0%
다사374254 1
 
1.0%
다사182216 1
 
1.0%
Other values (85) 85
85.0%
2023-12-10T19:06:03.476280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 74
9.2%
6 72
 
9.0%
3 66
 
8.2%
마 62
 
7.8%
2 62
 
7.8%
7 61
 
7.6%
5 59
 
7.4%
라 56
 
7.0%
9 54
 
6.8%
4 53
 
6.6%
Other values (6) 181
22.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 74
12.3%
6 72
12.0%
3 66
11.0%
2 62
10.3%
7 61
10.2%
5 59
9.8%
9 54
9.0%
4 53
8.8%
8 50
8.3%
0 49
8.2%
Other Letter
ValueCountFrequency (%)
마 62
31.0%
라 56
28.0%
다 44
22.0%
사 19
 
9.5%
바 17
 
8.5%
아 2
 
1.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 74
12.3%
6 72
12.0%
3 66
11.0%
2 62
10.3%
7 61
10.2%
5 59
9.8%
9 54
9.0%
4 53
8.8%
8 50
8.3%
0 49
8.2%
Hangul
ValueCountFrequency (%)
마 62
31.0%
라 56
28.0%
다 44
22.0%
사 19
 
9.5%
바 17
 
8.5%
아 2
 
1.0%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 74
12.3%
6 72
12.0%
3 66
11.0%
2 62
10.3%
7 61
10.2%
5 59
9.8%
9 54
9.0%
4 53
8.8%
8 50
8.3%
0 49
8.2%
Hangul
ValueCountFrequency (%)
마 62
31.0%
라 56
28.0%
다 44
22.0%
사 19
 
9.5%
바 17
 
8.5%
아 2
 
1.0%

x_cd
Real number (ℝ)

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.119697
Minimum34.728069
Maximum38.104511
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:06:03.750457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.728069
5-th percentile34.917181
Q135.353368
median35.852445
Q336.861049
95-th percentile37.754881
Maximum38.104511
Range3.3764416
Interquartile range (IQR)1.5076809

Descriptive statistics

Standard deviation0.92951598
Coefficient of variation (CV)0.025734323
Kurtosis-0.91067549
Mean36.119697
Median Absolute Deviation (MAD)0.68101885
Skewness0.55753578
Sum3611.9697
Variance0.86399995
MonotonicityNot monotonic
2023-12-10T19:06:04.025824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.85086541 3
 
3.0%
35.137384 2
 
2.0%
36.649649 1
 
1.0%
37.30014172 1
 
1.0%
35.142203 1
 
1.0%
35.146719 1
 
1.0%
35.146745 1
 
1.0%
35.166574 1
 
1.0%
35.1605749204 1
 
1.0%
37.3257908151 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
34.7280694 1
1.0%
34.8008595643 1
1.0%
34.8319585778 1
1.0%
34.8720398734 1
1.0%
34.9133657 1
1.0%
34.9173820412 1
1.0%
35.0561896437 1
1.0%
35.09748815 1
1.0%
35.11760617 1
1.0%
35.1211974 1
1.0%
ValueCountFrequency (%)
38.104511 1
1.0%
38.0141103 1
1.0%
37.8905877489 1
1.0%
37.804849 1
1.0%
37.76385959 1
1.0%
37.754408 1
1.0%
37.754341 1
1.0%
37.7390499 1
1.0%
37.6889027 1
1.0%
37.6872535885 1
1.0%

y_cd
Real number (ℝ)

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.7594
Minimum126.39511
Maximum129.32721
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:06:04.292528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.39511
5-th percentile126.57703
Q1126.91904
median127.71308
Q3128.55767
95-th percentile129.13867
Maximum129.32721
Range2.9321026
Interquartile range (IQR)1.6386251

Descriptive statistics

Standard deviation0.85662204
Coefficient of variation (CV)0.0067049628
Kurtosis-1.2431754
Mean127.7594
Median Absolute Deviation (MAD)0.801008
Skewness0.20492771
Sum12775.94
Variance0.73380131
MonotonicityNot monotonic
2023-12-10T19:06:04.551555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.5576698 3
 
3.0%
126.790869 2
 
2.0%
127.493941 1
 
1.0%
127.6545493 1
 
1.0%
126.915417 1
 
1.0%
126.920254 1
 
1.0%
126.840932 1
 
1.0%
126.908722 1
 
1.0%
126.8798720197 1
 
1.0%
126.793703 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
126.3951092837 1
1.0%
126.409499 1
1.0%
126.4644756 1
1.0%
126.519948721 1
1.0%
126.5597038 1
1.0%
126.577945113 1
1.0%
126.7117 1
1.0%
126.71745 1
1.0%
126.7257619 1
1.0%
126.726715 1
1.0%
ValueCountFrequency (%)
129.3272119 1
1.0%
129.2174888 1
1.0%
129.203053 1
1.0%
129.196792 1
1.0%
129.1393974 1
1.0%
129.1386342 1
1.0%
129.1104527 1
1.0%
129.050951372 1
1.0%
129.0487401 1
1.0%
129.0450624 1
1.0%

infbru_lc_nm
Text

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:06:04.903045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length19
Mean length10.75
Min length3

Characters and Unicode

Total characters1075
Distinct characters218
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)97.0%

Sample

1st row성안길 KDB산업은행 앞
2nd row수암골 마실 앞
3rd row서울특별시 서대문구 연세로 5길 11
4th row화천시외버스터미널
5th row영동역
ValueCountFrequency (%)
내 11
 
4.5%
앞 9
 
3.6%
광장 7
 
2.8%
옆 6
 
2.4%
경남 6
 
2.4%
의령군 6
 
2.4%
주차장 4
 
1.6%
입구 4
 
1.6%
1층 3
 
1.2%
근처 3
 
1.2%
Other values (166) 188
76.1%
2023-12-10T19:06:05.481298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
148
 
13.8%
내 31
 
2.9%
역 27
 
2.5%
광 27
 
2.5%
장 22
 
2.0%
관 18
 
1.7%
주 17
 
1.6%
시 15
 
1.4%
산 15
 
1.4%
1 15
 
1.4%
Other values (208) 740
68.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 849
79.0%
Space Separator 148
 
13.8%
Decimal Number 46
 
4.3%
Close Punctuation 9
 
0.8%
Dash Punctuation 9
 
0.8%
Open Punctuation 8
 
0.7%
Uppercase Letter 6
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
내 31
 
3.7%
역 27
 
3.2%
광 27
 
3.2%
장 22
 
2.6%
관 18
 
2.1%
주 17
 
2.0%
시 15
 
1.8%
산 15
 
1.8%
군 14
 
1.6%
터 13
 
1.5%
Other values (189) 650
76.6%
Decimal Number
ValueCountFrequency (%)
1 15
32.6%
2 11
23.9%
3 5
 
10.9%
5 4
 
8.7%
4 4
 
8.7%
0 2
 
4.3%
7 2
 
4.3%
6 2
 
4.3%
8 1
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
C 1
16.7%
I 1
16.7%
K 1
16.7%
D 1
16.7%
B 1
16.7%
F 1
16.7%
Space Separator
ValueCountFrequency (%)
148
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 848
78.9%
Common 220
 
20.5%
Latin 6
 
0.6%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
내 31
 
3.7%
역 27
 
3.2%
광 27
 
3.2%
장 22
 
2.6%
관 18
 
2.1%
주 17
 
2.0%
시 15
 
1.8%
산 15
 
1.8%
군 14
 
1.7%
터 13
 
1.5%
Other values (188) 649
76.5%
Common
ValueCountFrequency (%)
148
67.3%
1 15
 
6.8%
2 11
 
5.0%
) 9
 
4.1%
- 9
 
4.1%
( 8
 
3.6%
3 5
 
2.3%
5 4
 
1.8%
4 4
 
1.8%
0 2
 
0.9%
Other values (3) 5
 
2.3%
Latin
ValueCountFrequency (%)
C 1
16.7%
I 1
16.7%
K 1
16.7%
D 1
16.7%
B 1
16.7%
F 1
16.7%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 848
78.9%
ASCII 226
 
21.0%
CJK 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
148
65.5%
1 15
 
6.6%
2 11
 
4.9%
) 9
 
4.0%
- 9
 
4.0%
( 8
 
3.5%
3 5
 
2.2%
5 4
 
1.8%
4 4
 
1.8%
0 2
 
0.9%
Other values (9) 11
 
4.9%
Hangul
ValueCountFrequency (%)
내 31
 
3.7%
역 27
 
3.2%
광 27
 
3.2%
장 22
 
2.6%
관 18
 
2.1%
주 17
 
2.0%
시 15
 
1.8%
산 15
 
1.8%
군 14
 
1.7%
터 13
 
1.5%
Other values (188) 649
76.5%
CJK
ValueCountFrequency (%)
內 1
100.0%

infbru_intr
Text

MISSING 

Distinct66
Distinct (%)68.8%
Missing4
Missing (%)4.0%
Memory size932.0 B
2023-12-10T19:06:05.982612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length51.5
Mean length24.395833
Min length5

Characters and Unicode

Total characters2342
Distinct characters215
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)57.3%

Sample

1st row성안길 일원 외국인 관광객 쇼핑 통역 지원
2nd row수암골 관광안내 및 통역 지원
3rd row서대문구 관광안내책자 및 지도 제공
4th row관광안내소
5th row영동군 관광지 소개, 교통편 등 정보 제공 및 관광지 안내 등
ValueCountFrequency (%)
제공 28
 
4.8%
및 27
 
4.6%
등 20
 
3.4%
관광안내 19
 
3.3%
대한 15
 
2.6%
안내 14
 
2.4%
관광안내소 13
 
2.2%
관광지 11
 
1.9%
정보 11
 
1.9%
위치한 10
 
1.7%
Other values (199) 413
71.1%
2023-12-10T19:06:06.739849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
485
 
20.7%
관 133
 
5.7%
광 118
 
5.0%
내 76
 
3.2%
안 67
 
2.9%
지 40
 
1.7%
대 39
 
1.7%
보 36
 
1.5%
제 36
 
1.5%
시 36
 
1.5%
Other values (205) 1276
54.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1797
76.7%
Space Separator 485
 
20.7%
Other Punctuation 47
 
2.0%
Open Punctuation 4
 
0.2%
Close Punctuation 4
 
0.2%
Decimal Number 4
 
0.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 133
 
7.4%
광 118
 
6.6%
내 76
 
4.2%
안 67
 
3.7%
지 40
 
2.2%
대 39
 
2.2%
보 36
 
2.0%
제 36
 
2.0%
시 36
 
2.0%
공 34
 
1.9%
Other values (196) 1182
65.8%
Other Punctuation
ValueCountFrequency (%)
, 28
59.6%
. 18
38.3%
/ 1
 
2.1%
Decimal Number
ValueCountFrequency (%)
1 3
75.0%
5 1
 
25.0%
Space Separator
ValueCountFrequency (%)
485
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1796
76.7%
Common 545
 
23.3%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 133
 
7.4%
광 118
 
6.6%
내 76
 
4.2%
안 67
 
3.7%
지 40
 
2.2%
대 39
 
2.2%
보 36
 
2.0%
제 36
 
2.0%
시 36
 
2.0%
공 34
 
1.9%
Other values (195) 1181
65.8%
Common
ValueCountFrequency (%)
485
89.0%
, 28
 
5.1%
. 18
 
3.3%
( 4
 
0.7%
) 4
 
0.7%
1 3
 
0.6%
5 1
 
0.2%
- 1
 
0.2%
/ 1
 
0.2%
Latin
ValueCountFrequency (%)
º 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1796
76.7%
ASCII 545
 
23.3%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
485
89.0%
, 28
 
5.1%
. 18
 
3.3%
( 4
 
0.7%
) 4
 
0.7%
1 3
 
0.6%
5 1
 
0.2%
- 1
 
0.2%
/ 1
 
0.2%
Hangul
ValueCountFrequency (%)
관 133
 
7.4%
광 118
 
6.6%
내 76
 
4.2%
안 67
 
3.7%
지 40
 
2.2%
대 39
 
2.2%
보 36
 
2.0%
제 36
 
2.0%
시 36
 
2.0%
공 34
 
1.9%
Other values (195) 1181
65.8%
None
ValueCountFrequency (%)
º 1
100.0%

adisvc_inf
Categorical

Distinct29
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
37 
관광정보 안내
8 
×
6 
문화관광해설
6 
없음
6 
Other values (24)
37 

Length

Max length36
Median length25.5
Mean length7.08
Min length1

Unique

Unique19 ?
Unique (%)19.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 37
37.0%
관광정보 안내 8
 
8.0%
× 6
 
6.0%
문화관광해설 6
 
6.0%
없음 6
 
6.0%
휠체어대여,핸드폰충전,인터넷사용 5
 
5.0%
핸드폰충전 4
 
4.0%
휴대폰충전 3
 
3.0%
외국어 안내+숙박안내+쇼핑안내+특산품판매 3
 
3.0%
핸드폰 충전 3
 
3.0%
Other values (19) 19
19.0%

Length

2023-12-10T19:06:07.361957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 37
25.7%
안내 8
 
5.6%
관광정보 8
 
5.6%
문화관광해설 7
 
4.9%
× 6
 
4.2%
없음 6
 
4.2%
휠체어대여,핸드폰충전,인터넷사용 5
 
3.5%
충전 5
 
3.5%
핸드폰 4
 
2.8%
휴대폰충전 4
 
2.8%
Other values (41) 54
37.5%

rstde
Categorical

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
연중무휴
57 
설명절당일, 추석명절당일
 
5
설날, 추석, 연휴
 
4
명절연휴
 
3
매주 월요일
 
3
Other values (21)
28 

Length

Max length28
Median length4
Mean length6.41
Min length2

Unique

Unique15 ?
Unique (%)15.0%

Sample

1st row명절
2nd row없음
3rd row매주월요일, 설날, 추석
4th row설, 추석
5th row연중무휴

Common Values

ValueCountFrequency (%)
연중무휴 57
57.0%
설명절당일, 추석명절당일 5
 
5.0%
설날, 추석, 연휴 4
 
4.0%
명절연휴 3
 
3.0%
매주 월요일 3
 
3.0%
1월1일,추석당일,설날당일 3
 
3.0%
정기휴무 일,월/임시휴무 신정, 구정, 추석 2
 
2.0%
없음 2
 
2.0%
설날,추석 2
 
2.0%
월~금요일 2
 
2.0%
Other values (16) 17
 
17.0%

Length

2023-12-10T19:06:07.605441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연중무휴 57
37.3%
추석 12
 
7.8%
설날 7
 
4.6%
월요일 7
 
4.6%
매주 6
 
3.9%
추석명절당일 5
 
3.3%
설명절당일 5
 
3.3%
연휴 4
 
2.6%
명절연휴 3
 
2.0%
1월1일,추석당일,설날당일 3
 
2.0%
Other values (29) 44
28.8%

smr_opn_tm
Categorical

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
09:00
62 
10:00
36 
11:00
 
1
08:00
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row10:00
2nd row10:00
3rd row11:00
4th row09:00
5th row09:00

Common Values

ValueCountFrequency (%)
09:00 62
62.0%
10:00 36
36.0%
11:00 1
 
1.0%
08:00 1
 
1.0%

Length

2023-12-10T19:06:07.851181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:06:08.033278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09:00 62
62.0%
10:00 36
36.0%
11:00 1
 
1.0%
08:00 1
 
1.0%

smr_cls_tm
Categorical

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
18:00
55 
17:00
38 
20:00
 
4
21:00
 
1
14:00
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row20:00
2nd row18:00
3rd row21:00
4th row17:00
5th row18:00

Common Values

ValueCountFrequency (%)
18:00 55
55.0%
17:00 38
38.0%
20:00 4
 
4.0%
21:00 1
 
1.0%
14:00 1
 
1.0%
19:30 1
 
1.0%

Length

2023-12-10T19:06:08.232681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:06:08.454686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
18:00 55
55.0%
17:00 38
38.0%
20:00 4
 
4.0%
21:00 1
 
1.0%
14:00 1
 
1.0%
19:30 1
 
1.0%

wntr_opn_tm
Categorical

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
09:00
62 
10:00
36 
11:00
 
1
08:00
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row10:00
2nd row10:00
3rd row11:00
4th row09:00
5th row09:00

Common Values

ValueCountFrequency (%)
09:00 62
62.0%
10:00 36
36.0%
11:00 1
 
1.0%
08:00 1
 
1.0%

Length

2023-12-10T19:06:08.732946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:06:08.924083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09:00 62
62.0%
10:00 36
36.0%
11:00 1
 
1.0%
08:00 1
 
1.0%

wntr_cls_tm
Categorical

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
18:00
52 
17:00
38 
20:00
 
4
16:00
 
3
21:00
 
1
Other values (2)
 
2

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row20:00
2nd row18:00
3rd row21:00
4th row17:00
5th row18:00

Common Values

ValueCountFrequency (%)
18:00 52
52.0%
17:00 38
38.0%
20:00 4
 
4.0%
16:00 3
 
3.0%
21:00 1
 
1.0%
17:30 1
 
1.0%
19:30 1
 
1.0%

Length

2023-12-10T19:06:09.123566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:06:09.321058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
18:00 52
52.0%
17:00 38
38.0%
20:00 4
 
4.0%
16:00 3
 
3.0%
21:00 1
 
1.0%
17:30 1
 
1.0%
19:30 1
 
1.0%

avg_wrk_nmpr
Categorical

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2
46 
1
36 
<NA>
9 
3
7 
7
 
1

Length

Max length4
Median length1
Mean length1.28
Min length1

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 46
46.0%
1 36
36.0%
<NA> 9
 
9.0%
3 7
 
7.0%
7 1
 
1.0%
10 1
 
1.0%

Length

2023-12-10T19:06:09.586800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:06:09.908769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 46
46.0%
1 36
36.0%
na 9
 
9.0%
3 7
 
7.0%
7 1
 
1.0%
10 1
 
1.0%

en_gud_psbl_yn
Boolean

MISSING 

Distinct2
Distinct (%)2.1%
Missing5
Missing (%)5.0%
Memory size332.0 B
False
49 
True
46 
(Missing)
5 
ValueCountFrequency (%)
False 49
49.0%
True 46
46.0%
(Missing) 5
 
5.0%
2023-12-10T19:06:10.199136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

jp_gud_psbl_yn
Boolean

MISSING 

Distinct2
Distinct (%)2.2%
Missing7
Missing (%)7.0%
Memory size332.0 B
False
51 
True
42 
(Missing)
7 
ValueCountFrequency (%)
False 51
51.0%
True 42
42.0%
(Missing) 7
 
7.0%
2023-12-10T19:06:10.395101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

cn_gud_psbl_yn
Boolean

MISSING 

Distinct2
Distinct (%)2.2%
Missing7
Missing (%)7.0%
Memory size332.0 B
False
54 
True
39 
(Missing)
7 
ValueCountFrequency (%)
False 54
54.0%
True 39
39.0%
(Missing) 7
 
7.0%
2023-12-10T19:06:10.584187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

gud_psbl_fggg
Categorical

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
63 
N
10 
러시아어
8 
없음
7 
영어
 
3
Other values (6)
9 

Length

Max length10
Median length4
Mean length3.65
Min length1

Unique

Unique4 ?
Unique (%)4.0%

Sample

1st row일본어, 중국어
2nd row일본어, 중국어
3rd row<NA>
4th row없음
5th rowN

Common Values

ValueCountFrequency (%)
<NA> 63
63.0%
N 10
 
10.0%
러시아어 8
 
8.0%
없음 7
 
7.0%
영어 3
 
3.0%
해당없음 3
 
3.0%
일본어, 중국어 2
 
2.0%
영어, 일본어 1
 
1.0%
영어+일본어+중국어 1
 
1.0%
일본어 1
 
1.0%

Length

2023-12-10T19:06:10.843352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 63
61.2%
n 10
 
9.7%
러시아어 8
 
7.8%
없음 7
 
6.8%
영어 4
 
3.9%
일본어 4
 
3.9%
해당없음 3
 
2.9%
중국어 3
 
2.9%
영어+일본어+중국어 1
 
1.0%

telno
Text

Distinct91
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:06:11.305898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.91
Min length9

Characters and Unicode

Total characters1191
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)86.0%

Sample

1st row043-254-1230
2nd row043-253-1330
3rd row070-4909-9131
4th row033-440-2575
5th row043-745-7741
ValueCountFrequency (%)
055-570-2513 6
 
6.0%
062-611-3616 2
 
2.0%
055-392-3234 2
 
2.0%
1899-8687 2
 
2.0%
000-0000-0000 2
 
2.0%
062-941-6301 1
 
1.0%
053-627-8906 1
 
1.0%
062-944-9044 1
 
1.0%
062-601-4260 1
 
1.0%
051-204-1444 1
 
1.0%
Other values (81) 81
81.0%
2023-12-10T19:06:12.218633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 195
16.4%
- 195
16.4%
3 141
11.8%
5 121
10.2%
4 100
8.4%
1 91
7.6%
6 89
7.5%
2 87
7.3%
7 62
 
5.2%
8 61
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 996
83.6%
Dash Punctuation 195
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 195
19.6%
3 141
14.2%
5 121
12.1%
4 100
10.0%
1 91
9.1%
6 89
8.9%
2 87
8.7%
7 62
 
6.2%
8 61
 
6.1%
9 49
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 195
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1191
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 195
16.4%
- 195
16.4%
3 141
11.8%
5 121
10.2%
4 100
8.4%
1 91
7.6%
6 89
7.5%
2 87
7.3%
7 62
 
5.2%
8 61
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1191
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 195
16.4%
- 195
16.4%
3 141
11.8%
5 121
10.2%
4 100
8.4%
1 91
7.6%
6 89
7.5%
2 87
7.3%
7 62
 
5.2%
8 61
 
5.1%

adm_agnc_nm
Categorical

Distinct43
Distinct (%)43.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
광주시관광협회
8 
경상남도 남해군
 
6
전라북도 군산시청
 
6
의령군청(관광진흥담당)
 
6
강릉시
 
6
Other values (38)
68 

Length

Max length13
Median length12
Mean length7.8
Min length3

Unique

Unique24 ?
Unique (%)24.0%

Sample

1st row관광과
2nd row관광과
3rd row서울특별시 서대문구청
4th row강원도 화천군청
5th row충청북도 영동군청

Common Values

ValueCountFrequency (%)
광주시관광협회 8
 
8.0%
경상남도 남해군 6
 
6.0%
전라북도 군산시청 6
 
6.0%
의령군청(관광진흥담당) 6
 
6.0%
강릉시 6
 
6.0%
대전광역시관광협회 5
 
5.0%
경상북도 경주시청 5
 
5.0%
양산시 4
 
4.0%
대구광역시관광협회 4
 
4.0%
경상남도 함양군청 4
 
4.0%
Other values (33) 46
46.0%

Length

2023-12-10T19:06:12.506343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경상남도 10
 
6.5%
광주시관광협회 8
 
5.2%
전라북도 8
 
5.2%
남해군 6
 
3.9%
군산시청 6
 
3.9%
의령군청(관광진흥담당 6
 
3.9%
강릉시 6
 
3.9%
경상북도 6
 
3.9%
대전광역시관광협회 5
 
3.3%
경주시청 5
 
3.3%
Other values (47) 87
56.9%

hmpg
Categorical

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
35 
www.gn.go.kr/tour
6 
×
6 
http://tour.gunsan.go.kr
6 
http://tour.namhae.go.kr/00003006/00003009/00003030.web
6 
Other values (21)
41 

Length

Max length55
Median length38
Mean length18.54
Min length1

Unique

Unique13 ?
Unique (%)13.0%

Sample

1st row<NA>
2nd row<NA>
3rd rowplay.sdm.go.kr
4th rowtour.ihc.go.kr
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 35
35.0%
www.gn.go.kr/tour 6
 
6.0%
× 6
 
6.0%
http://tour.gunsan.go.kr 6
 
6.0%
http://tour.namhae.go.kr/00003006/00003009/00003030.web 6
 
6.0%
http://tour.jangseong.go.kr/ 5
 
5.0%
http://www.gogbta.or.kr/dowomi 5
 
5.0%
http://www.daegutravel.or.kr 4
 
4.0%
http://www.hygn.go.kr/01235/01288/01465.web 4
 
4.0%
cheonan.go.kr 3
 
3.0%
Other values (16) 20
20.0%

Length

2023-12-10T19:06:12.813264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 35
35.0%
× 6
 
6.0%
http://tour.gunsan.go.kr 6
 
6.0%
http://tour.namhae.go.kr/00003006/00003009/00003030.web 6
 
6.0%
www.gn.go.kr/tour 6
 
6.0%
http://tour.jangseong.go.kr 5
 
5.0%
http://www.gogbta.or.kr/dowomi 5
 
5.0%
http://www.daegutravel.or.kr 4
 
4.0%
http://www.hygn.go.kr/01235/01288/01465.web 4
 
4.0%
http://tour.yangsan.go.kr 3
 
3.0%
Other values (16) 20
20.0%

data_stdde
Categorical

Distinct36
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2019-06-26
12 
2019-07-05
 
6
2019-07-09
 
6
2019-09-06
 
6
2019-06-24
 
6
Other values (31)
64 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique15 ?
Unique (%)15.0%

Sample

1st row2018-08-13
2nd row2018-08-13
3rd row2018-08-20
4th row2018-08-10
5th row2018-02-23

Common Values

ValueCountFrequency (%)
2019-06-26 12
 
12.0%
2019-07-05 6
 
6.0%
2019-07-09 6
 
6.0%
2019-09-06 6
 
6.0%
2019-06-24 6
 
6.0%
2018-05-14 5
 
5.0%
2018-02-19 5
 
5.0%
2019-09-21 5
 
5.0%
2019-09-16 4
 
4.0%
2019-05-01 4
 
4.0%
Other values (26) 41
41.0%

Length

2023-12-10T19:06:13.029521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2019-06-26 12
 
12.0%
2019-09-06 6
 
6.0%
2019-06-24 6
 
6.0%
2019-07-05 6
 
6.0%
2019-07-09 6
 
6.0%
2018-05-14 5
 
5.0%
2018-02-19 5
 
5.0%
2019-09-21 5
 
5.0%
2019-05-01 4
 
4.0%
2019-09-16 4
 
4.0%
Other values (26) 41
41.0%

prvd_agnc_cd
Real number (ℝ)

Distinct39
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4854800
Minimum3120000
Maximum6300000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:06:13.247483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3120000
5-th percentile3450000
Q14200000
median4905000
Q35430000
95-th percentile6290500
Maximum6300000
Range3180000
Interquartile range (IQR)1230000

Descriptive statistics

Standard deviation870915.55
Coefficient of variation (CV)0.17939267
Kurtosis-0.76209621
Mean4854800
Median Absolute Deviation (MAD)555000
Skewness-0.032028211
Sum4.8548 × 108
Variance7.584939 × 1011
MonotonicityNot monotonic
2023-12-10T19:06:13.510395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
6290000 8
 
8.0%
4200000 6
 
6.0%
5390000 6
 
6.0%
4670000 6
 
6.0%
5430000 6
 
6.0%
4980000 5
 
5.0%
6300000 5
 
5.0%
5050000 5
 
5.0%
5380000 4
 
4.0%
5460000 4
 
4.0%
Other values (29) 45
45.0%
ValueCountFrequency (%)
3120000 1
 
1.0%
3270000 2
2.0%
3340000 1
 
1.0%
3450000 3
3.0%
3470000 4
4.0%
3550000 1
 
1.0%
3600000 1
 
1.0%
3820000 1
 
1.0%
3930000 2
2.0%
4050000 2
2.0%
ValueCountFrequency (%)
6300000 5
5.0%
6290000 8
8.0%
5710000 2
 
2.0%
5700000 3
 
3.0%
5460000 4
4.0%
5430000 6
6.0%
5390000 6
6.0%
5380000 4
4.0%
5080000 1
 
1.0%
5050000 5
5.0%

prvd_agnc_nm
Categorical

Distinct39
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
광주광역시
8 
강원도 강릉시
 
6
전라북도 군산시
 
6
경상남도 의령군
 
6
경상남도 남해군
 
6
Other values (34)
68 

Length

Max length10
Median length8
Mean length7.5
Min length5

Unique

Unique19 ?
Unique (%)19.0%

Sample

1st row충청북도 청주시
2nd row충청북도 청주시
3rd row서울특별시 서대문구
4th row강원도 화천군
5th row충청북도 영동군

Common Values

ValueCountFrequency (%)
광주광역시 8
 
8.0%
강원도 강릉시 6
 
6.0%
전라북도 군산시 6
 
6.0%
경상남도 의령군 6
 
6.0%
경상남도 남해군 6
 
6.0%
전라남도 장성군 5
 
5.0%
대전광역시 5
 
5.0%
경상북도 경주시 5
 
5.0%
경상남도 양산시 4
 
4.0%
경상남도 함양군 4
 
4.0%
Other values (29) 45
45.0%

Length

2023-12-10T19:06:13.755142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경상남도 20
 
10.7%
경기도 10
 
5.3%
강원도 10
 
5.3%
광주광역시 9
 
4.8%
전라북도 9
 
4.8%
충청북도 7
 
3.7%
대구광역시 7
 
3.7%
전라남도 7
 
3.7%
남해군 6
 
3.2%
경상북도 6
 
3.2%
Other values (41) 96
51.3%

lst_updt_dt
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20191167
Minimum20191117
Maximum20191217
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:06:13.981683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20191117
5-th percentile20191122
Q120191142
median20191166
Q320191191
95-th percentile20191212
Maximum20191217
Range100
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.28084
Coefficient of variation (CV)1.4501807 × 10-6
Kurtosis-1.1889345
Mean20191167
Median Absolute Deviation (MAD)25
Skewness0.020179482
Sum2.0191167 × 109
Variance857.36758
MonotonicityStrictly increasing
2023-12-10T19:06:14.304513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20191117 1
 
1.0%
20191181 1
 
1.0%
20191191 1
 
1.0%
20191190 1
 
1.0%
20191189 1
 
1.0%
20191188 1
 
1.0%
20191187 1
 
1.0%
20191186 1
 
1.0%
20191185 1
 
1.0%
20191184 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
20191117 1
1.0%
20191118 1
1.0%
20191119 1
1.0%
20191120 1
1.0%
20191121 1
1.0%
20191122 1
1.0%
20191123 1
1.0%
20191124 1
1.0%
20191125 1
1.0%
20191126 1
1.0%
ValueCountFrequency (%)
20191217 1
1.0%
20191216 1
1.0%
20191215 1
1.0%
20191214 1
1.0%
20191213 1
1.0%
20191212 1
1.0%
20191211 1
1.0%
20191210 1
1.0%
20191209 1
1.0%
20191208 1
1.0%

data_orgn
Categorical

CONSTANT 

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

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공데이터포탈 100
100.0%

Length

2023-12-10T19:06:14.576423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:06:14.761212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공데이터포탈 100
100.0%

FILE_NAME
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC_489_WNTY_TRSMIC_2019
100 

Length

Max length23
Median length23
Mean length23
Min length23

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_489_WNTY_TRSMIC_2019
2nd rowKC_489_WNTY_TRSMIC_2019
3rd rowKC_489_WNTY_TRSMIC_2019
4th rowKC_489_WNTY_TRSMIC_2019
5th rowKC_489_WNTY_TRSMIC_2019

Common Values

ValueCountFrequency (%)
KC_489_WNTY_TRSMIC_2019 100
100.0%

Length

2023-12-10T19:06:14.965832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:06:15.142210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_489_wnty_trsmic_2019 100
100.0%

base_ymd
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20191125
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20191125
2nd row20191125
3rd row20191125
4th row20191125
5th row20191125

Common Values

ValueCountFrequency (%)
20191125 100
100.0%

Length

2023-12-10T19:06:15.368151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:06:15.707303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20191125 100
100.0%

Sample

idlclasmlsfcfclt_namectprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrzip_cdgrid_cdx_cdy_cdinfbru_lc_nminfbru_intradisvc_infrstdesmr_opn_tmsmr_cls_tmwntr_opn_tmwntr_cls_tmavg_wrk_nmpren_gud_psbl_ynjp_gud_psbl_yncn_gud_psbl_yngud_psbl_fgggtelnoadm_agnc_nmhmpgdata_stddeprvd_agnc_cdprvd_agnc_nmlst_updt_dtdata_orgnFILE_NAMEbase_ymd
0KC489PC19N000001문화시설관광안내소성안길관광안내소충청북도청주시 청원구4311410100우암동4311451000우암동431143236034충청북도 청주시 청원구 수암로 82 (우암동)28506다바99450136.649649127.493941성안길 KDB산업은행 앞성안길 일원 외국인 관광객 쇼핑 통역 지원<NA>명절10:0020:0010:0020:002<NA>YY일본어, 중국어043-254-1230관광과<NA>2018-08-135710000충청북도 청주시20191117공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
1KC489PC19N000002문화시설관광안내소수암골관광안내소충청북도청주시 청원구4311410100우암동4311451000우암동431143236034충청북도 청주시 청원구 수암로 78-1 (우암동)28506다바99450136.649442127.494113수암골 마실 앞수암골 관광안내 및 통역 지원<NA>없음10:0018:0010:0018:002<NA>YY일본어, 중국어043-253-1330관광과<NA>2018-08-135710000충청북도 청주시20191118공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
2KC489PC19N000003문화시설관광안내소신촌플레이버스서울특별시서대문구1141011600창천동1141058500신촌동114104136241서울특별시 서대문구 연세로5길 26-9 (창천동)3789다사50050937.556622126.935005서울특별시 서대문구 연세로 5길 11서대문구 관광안내책자 및 지도 제공<NA>매주월요일, 설날, 추석11:0021:0011:0021:002YNN<NA>070-4909-9131서울특별시 서대문구청play.sdm.go.kr2018-08-203120000서울특별시 서대문구20191119공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
3KC489PC19N000004문화시설관광안내소강원도 화천군 관광안내소(터미널)강원도화천군4279025022화천읍4279025000화천읍427903231011강원도 화천군 화천읍 상승로 38-524130라아17911638.104511127.704262화천시외버스터미널관광안내소<NA>설, 추석09:0017:0009:0017:002NNN없음033-440-2575강원도 화천군청tour.ihc.go.kr2018-08-104310000강원도 화천군20191120공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
4KC489PC19N000005문화시설관광안내소영동군 관광안내소충청북도영동군4374025021영동읍4374025000영동읍437403243002충청북도 영동군 영동읍 계산로 8729144라마25797236.172128127.786562영동역영동군 관광지 소개, 교통편 등 정보 제공 및 관광지 안내 등핸드폰 충전연중무휴09:0018:0009:0018:002NNNN043-745-7741충청북도 영동군청<NA>2018-02-234440000충청북도 영동군20191121공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
5KC489PC19N000006문화시설관광안내소축령산 치유의 숲 안내센터전라남도장성군4688037023서삼면4688037000서삼면468804697123전라남도 장성군 서삼면 모암길 28-3157231다마32809135.376174126.760709축령산 치유의 숲 관리사무소축령산 산행안내, 숲 해설사 신청 등<NA>연중무휴09:0018:0009:0018:007YNN<NA>061-393-1777산림청http://tour.jangseong.go.kr/2018-05-144980000전라남도 장성군20191122공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
6KC489PC19N000007문화시설관광안내소내장산국립공원 백암사무소전라남도장성군4688040025북하면4688040000북하면468803299016전라남도 장성군 북하면 백양로 115157205다마43615135.430963126.879302백양사 입구백암산 산행안내, 숲 해설사 신청 등<NA>연중무휴09:0018:0009:0018:0010YNN<NA>061-392-7288내장산국립공원 백암사무소http://tour.jangseong.go.kr/2018-05-144980000전라남도 장성군20191123공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
7KC489PC19N000008문화시설관광안내소장성호관광지전라남도장성군4688040031북하면4688040000북하면468804697218전라남도 장성군 북하면 송정공원길 1357204다마41013535.415562126.850562장성호 관광지 관리사무소장성호 관광지 전반 안내<NA>연중무휴09:0018:0009:0018:002NNN<NA>061-392-7248전라남도 장성군청http://tour.jangseong.go.kr/2018-05-144980000전라남도 장성군20191124공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
8KC489PC19N000009문화시설관광안내소홍길동테마파크 관광지전라남도장성군4688036028황룡면4688036000황룡면468803299056전라남도 장성군 황룡면 홍길동로 43157223다마29702935.319264126.726715홍길동테마파크 관리사무소홍길동 테마파크 전반 안내<NA>연중무휴09:0018:0009:0018:002NNN<NA>061-394-8580전라남도 장성군청http://tour.jangseong.go.kr/2018-05-144980000전라남도 장성군20191125공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
9KC489PC19N000010문화시설관광안내소필암서원 유물전시관전라남도장성군4688036027황룡면4688036000황룡면468803299055전라남도 장성군 황룡면 필암서원로 178-4757223다마32002135.312376126.751991필암서원 유물전시관필암서원, 필암서원 유물전시관 전반 안내<NA>연중무휴09:0018:0009:0017:002NNN<NA>061-393-8583전라남도 장성군청http://tour.jangseong.go.kr/2018-05-144980000전라남도 장성군20191126공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
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90KC489PC19N000092문화시설관광안내소부산관광안내소부산광역시동구2617010100초량동2617053000초량제3동261702006001부산광역시 동구 충장대로 201 (초량동)48759마라41181735.121197129.04874부산항 국제여객터미널 2층부산지역 관광안내 책자 배부 및 홍보없음연중무휴08:0019:3008:0019:302YYY<NA>051-465-3471부산광역시<NA>2019-09-193270000부산광역시 동구20191208공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
91KC489PC19N000093문화시설관광안내소대구관광정보센터대구광역시달서구2729010200두류동2729055000두류3동272903147002대구광역시 달서구 공원순환로 46 (두류동)42672라마95562135.850865128.55767두류공원 내(야외음악당 옆)국내,외 관광정보 제공 및 대구.경북 지역의 관광자원을 홍보외국어 안내+숙박안내+쇼핑안내+특산품판매연중무휴09:0018:0009:0018:00<NA>Y<NA><NA><NA>053-627-8900대구광역시관광협회http://www.daegutravel.or.kr2019-09-163470000대구광역시 달서구20191209공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
92KC489PC19N000094문화시설관광안내소대구관광정보센터대구광역시달서구2729010200두류동2729055000두류3동272903147002대구광역시 달서구 공원순환로 46 (두류동)42672라마95562135.850865128.55767두류공원 내(야외음악당 옆)국내,외 관광정보 제공 및 대구.경북 지역의 관광자원을 홍보외국어 안내+숙박안내+쇼핑안내+특산품판매연중무휴09:0018:0009:0018:00<NA>Y<NA><NA><NA>053-627-8986대구광역시관광협회http://www.daegutravel.or.kr2019-09-163470000대구광역시 달서구20191210공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
93KC489PC19N000095문화시설관광안내소대구관광정보센터대구광역시달서구2729010200두류동2729055000두류3동272903147002대구광역시 달서구 공원순환로 46 (두류동)42672라마95562135.850865128.55767두류공원 내(야외음악당 옆)국내,외 관광정보 제공 및 대구.경북 지역의 관광자원을 홍보외국어 안내+숙박안내+쇼핑안내+특산품판매연중무휴09:0018:0009:0018:00<NA>Y<NA><NA><NA>053-627-8906대구광역시관광협회http://www.daegutravel.or.kr2019-09-163470000대구광역시 달서구20191211공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
94KC489PC19N000096문화시설관광안내소이월드 관광안내소대구광역시달서구2729010200두류동2729053500두류1.2동272903007009대구광역시 달서구 두류공원로 200 (두류동)42666라마96062435.854025128.563417이월드 정문동우측각종 축제의 중심인 두류공원 인근에 위치하고 있어 대구를 찾는 내외국인에게 대구의 관광안내 및 관광정보를 제공통역서비스연중무휴10:0017:0010:0017:00<NA>Y<NA><NA><NA>053-621-6046대구광역시관광협회http://www.daegutravel.or.kr2019-09-163470000대구광역시 달서구20191212공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
95KC489PC19N000097문화시설관광안내소감천문화마을 안내센터부산광역시사하구2638010800감천동2638063000감천제2동263803134002부산광역시 사하구 감내2로 203 (감천동)49368마라37679035.097488129.010608감천문화마을 감정초등학교 앞감천문화마을 소개, 마을지도 판매, 홍보책자 배부 등관광해설사 근무, 물품보관연중무휴09:0018:0009:0018:003YYY<NA>051-204-1444감천문화마을 주민협의회https://www.gamcheon.or.kr/2019-09-253340000부산광역시 사하구20191213공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
96KC489PC19N000098문화시설관광안내소함평종합관광안내소전라남도함평군4686025024함평읍4686025000함평읍468603297002전라남도 함평군 함평읍 곤재로 2757143다라10673835.05619126.519949함평읍 곤재로 27<NA><NA>연중무휴10:0017:0010:0017:00<NA><NA><NA><NA><NA>061-320-2268팜평군<NA>2019-09-244960000전라남도 함평군20191214공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
97KC489PC19N000099문화시설관광안내소무주군 종합관광안내소전라북도무주군4573025022무주읍4573025000무주읍457303275053전라북도 무주군 무주읍 한풍루로 34455514라마14778636.004179127.663464무주공용시외버스터미널 앞무주군 관광 안내 및 해설핸드폰 충전명절 당일09:0018:0009:0018:002YYY<NA>1899-8687전라북도 무주군청http://www.mujutour.co.kr2019-09-304740000전라북도 무주군20191215공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
98KC489PC19N000100문화시설관광안내소만남의광장 종합관광안내소전라북도무주군4573025028무주읍4573025000무주읍457303275023전라북도 무주군 무주읍 무주로 173955512라마13675335.974432127.650957무주 IC 만남의 광장무주군 관광 안내 및 해설핸드폰 충전명절 당일09:0018:0009:0018:002YYY<NA>1899-8687전라북도 무주군청http://www.mujutour.co.kr2019-09-304740000전라북도 무주군20191216공공데이터포탈KC_489_WNTY_TRSMIC_201920191125
99KC489PC19N000101문화시설관광안내소김대중센터 관광안내소광주광역시서구2914012000치평동2914074500치평동291403160016광주광역시 서구 상무누리로 30 (치평동)61958다라39983735.146744126.840932김대중컨벤션센터광주광역시 관광정보 제공관광안내 및 관광홍보물 제공연중무휴09:0018:0009:0018:001YYY<NA>062-611-3616광주광역시http://utour.gwangju.go.kr/2019-09-053600000광주광역시 서구20191217공공데이터포탈KC_489_WNTY_TRSMIC_201920191125