Overview

Dataset statistics

Number of variables40
Number of observations50
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.3 KiB
Average record size in memory353.6 B

Variable types

Numeric19
Text9
Categorical12

Dataset

DescriptionSample
Author아파트엔
URLhttps://bigdata-geo.kr/user/dataset/view.do?data_sn=45

Alerts

strd_year has constant value ""Constant
hsptl_cnt_300mblw has constant value ""Constant
uid has unique valuesUnique
apt_cd has unique valuesUnique
rdnmadr has unique valuesUnique
elctyvh_info_1kmblw has unique valuesUnique
cafe_info_1kmblw has unique valuesUnique
spml_info_10kmblw has unique valuesUnique
hsptl_info_10kmblw has unique valuesUnique
gas_statn_info_10kmblw has unique valuesUnique
lo has unique valuesUnique
la has unique valuesUnique
elctyvh_cnt_250mblw has 10 (20.0%) zerosZeros
cafe_cnt_250movr_500mblw has 1 (2.0%) zerosZeros
gas_statn_cnt_500movr_1kmblw has 3 (6.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:24:23.564110
Analysis finished2023-12-10 13:24:25.502429
Duration1.94 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

uid
Real number (ℝ)

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7899.12
Minimum7796
Maximum8275
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:25.667390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7796
5-th percentile7798.45
Q17808.5
median7823.5
Q37835.75
95-th percentile8272.55
Maximum8275
Range479
Interquartile range (IQR)27.25

Descriptive statistics

Standard deviation167.62807
Coefficient of variation (CV)0.021221107
Kurtosis0.78384431
Mean7899.12
Median Absolute Deviation (MAD)13.5
Skewness1.6150399
Sum394956
Variance28099.169
MonotonicityNot monotonic
2023-12-10T22:24:25.934849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8117 1
 
2.0%
7827 1
 
2.0%
7817 1
 
2.0%
7818 1
 
2.0%
7819 1
 
2.0%
7820 1
 
2.0%
7821 1
 
2.0%
7822 1
 
2.0%
7823 1
 
2.0%
7824 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
7796 1
2.0%
7797 1
2.0%
7798 1
2.0%
7799 1
2.0%
7800 1
2.0%
7801 1
2.0%
7802 1
2.0%
7803 1
2.0%
7804 1
2.0%
7805 1
2.0%
ValueCountFrequency (%)
8275 1
2.0%
8274 1
2.0%
8273 1
2.0%
8272 1
2.0%
8271 1
2.0%
8221 1
2.0%
8220 1
2.0%
8219 1
2.0%
8118 1
2.0%
8117 1
2.0%

apt_cd
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-10T22:24:26.274446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1250
Distinct characters13
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

Unique50 ?
Unique (%)100.0%

Sample

1st rowAPT1168041662900019000001
2nd rowAPT1168041662940013001201
3rd rowAPT1168041664190005000001
4th rowAPT1168041664190012000001
5th rowAPT1168041665090016000001
ValueCountFrequency (%)
apt1168041662900019000001 1
 
2.0%
apt1168030050860117000001 1
 
2.0%
apt1168030050860555000001 1
 
2.0%
apt1168021220020330000701 1
 
2.0%
apt1168021220020602000001 1
 
2.0%
apt1168021220020640000001 1
 
2.0%
apt1168030050860003000001 1
 
2.0%
apt1168030050860101000001 1
 
2.0%
apt1168030050860103000001 1
 
2.0%
apt1168030050860105000001 1
 
2.0%
Other values (40) 40
80.0%
2023-12-10T22:24:26.908719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 501
40.1%
1 219
17.5%
6 103
 
8.2%
2 76
 
6.1%
8 75
 
6.0%
A 50
 
4.0%
P 50
 
4.0%
T 50
 
4.0%
3 41
 
3.3%
5 40
 
3.2%
Other values (3) 45
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1100
88.0%
Uppercase Letter 150
 
12.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 501
45.5%
1 219
19.9%
6 103
 
9.4%
2 76
 
6.9%
8 75
 
6.8%
3 41
 
3.7%
5 40
 
3.6%
4 28
 
2.5%
9 9
 
0.8%
7 8
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
A 50
33.3%
P 50
33.3%
T 50
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1100
88.0%
Latin 150
 
12.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 501
45.5%
1 219
19.9%
6 103
 
9.4%
2 76
 
6.9%
8 75
 
6.8%
3 41
 
3.7%
5 40
 
3.6%
4 28
 
2.5%
9 9
 
0.8%
7 8
 
0.7%
Latin
ValueCountFrequency (%)
A 50
33.3%
P 50
33.3%
T 50
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1250
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 501
40.1%
1 219
17.5%
6 103
 
8.2%
2 76
 
6.1%
8 75
 
6.0%
A 50
 
4.0%
P 50
 
4.0%
T 50
 
4.0%
3 41
 
3.3%
5 40
 
3.2%
Other values (3) 45
 
3.6%

apt_nm
Text

Distinct49
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-10T22:24:27.319661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length14.5
Mean length6.78
Min length2

Characters and Unicode

Total characters339
Distinct characters124
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

Unique48 ?
Unique (%)96.0%

Sample

1st row이니그마빌2
2nd row퍼즐하우스
3rd row대치현대
4th row대치효성
5th row유로미아파트A동
ValueCountFrequency (%)
대우디오빌 2
 
3.6%
디에이치자이개포 1
 
1.8%
우성4 1
 
1.8%
풍림아이원4차(1007-2 1
 
1.8%
미켈란107 1
 
1.8%
아이파크 1
 
1.8%
개포6차우성아파트1동~8동 1
 
1.8%
쌍용 1
 
1.8%
전화국현대(220 1
 
1.8%
개포현대200동 1
 
1.8%
Other values (44) 44
80.0%
2023-12-10T22:24:28.015198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
 
3.8%
12
 
3.5%
1 11
 
3.2%
0 10
 
2.9%
9
 
2.7%
9
 
2.7%
8
 
2.4%
8
 
2.4%
8
 
2.4%
8
 
2.4%
Other values (114) 243
71.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 256
75.5%
Decimal Number 50
 
14.7%
Uppercase Letter 11
 
3.2%
Open Punctuation 7
 
2.1%
Close Punctuation 7
 
2.1%
Space Separator 5
 
1.5%
Dash Punctuation 2
 
0.6%
Math Symbol 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12
 
4.7%
9
 
3.5%
9
 
3.5%
8
 
3.1%
8
 
3.1%
8
 
3.1%
8
 
3.1%
7
 
2.7%
7
 
2.7%
6
 
2.3%
Other values (91) 174
68.0%
Uppercase Letter
ValueCountFrequency (%)
S 2
18.2%
B 1
9.1%
A 1
9.1%
N 1
9.1%
K 1
9.1%
T 1
9.1%
O 1
9.1%
W 1
9.1%
E 1
9.1%
R 1
9.1%
Decimal Number
ValueCountFrequency (%)
2 13
26.0%
1 11
22.0%
0 10
20.0%
6 6
12.0%
4 4
 
8.0%
9 2
 
4.0%
7 2
 
4.0%
8 2
 
4.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 256
75.5%
Common 72
 
21.2%
Latin 11
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12
 
4.7%
9
 
3.5%
9
 
3.5%
8
 
3.1%
8
 
3.1%
8
 
3.1%
8
 
3.1%
7
 
2.7%
7
 
2.7%
6
 
2.3%
Other values (91) 174
68.0%
Common
ValueCountFrequency (%)
2 13
18.1%
1 11
15.3%
0 10
13.9%
( 7
9.7%
) 7
9.7%
6 6
8.3%
5
 
6.9%
4 4
 
5.6%
9 2
 
2.8%
7 2
 
2.8%
Other values (3) 5
 
6.9%
Latin
ValueCountFrequency (%)
S 2
18.2%
B 1
9.1%
A 1
9.1%
N 1
9.1%
K 1
9.1%
T 1
9.1%
O 1
9.1%
W 1
9.1%
E 1
9.1%
R 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 256
75.5%
ASCII 83
 
24.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13
15.7%
1 11
13.3%
0 10
12.0%
( 7
8.4%
) 7
8.4%
6 6
 
7.2%
5
 
6.0%
4 4
 
4.8%
9 2
 
2.4%
S 2
 
2.4%
Other values (13) 16
19.3%
Hangul
ValueCountFrequency (%)
12
 
4.7%
9
 
3.5%
9
 
3.5%
8
 
3.1%
8
 
3.1%
8
 
3.1%
8
 
3.1%
7
 
2.7%
7
 
2.7%
6
 
2.3%
Other values (91) 174
68.0%

rdnmadr
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-10T22:24:28.383016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length18.3
Min length15

Characters and Unicode

Total characters915
Distinct characters42
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)100.0%

Sample

1st row서울특별시 강남구 도산대로61길 19
2nd row서울특별시 강남구 도산대로67길 13-12
3rd row서울특별시 강남구 삼성로64길 5
4th row서울특별시 강남구 삼성로64길 12
5th row서울특별시 강남구 압구정로14길 16
ValueCountFrequency (%)
서울특별시 50
25.0%
강남구 50
25.0%
언주로 20
 
10.0%
영동대로 7
 
3.5%
강남대로 4
 
2.0%
남부순환로 3
 
1.5%
삼성로64길 3
 
1.5%
압구정로18길 3
 
1.5%
도산대로 2
 
1.0%
압구정로14길 2
 
1.0%
Other values (56) 56
28.0%
2023-12-10T22:24:29.031406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
150
16.4%
57
 
6.2%
55
 
6.0%
54
 
5.9%
50
 
5.5%
50
 
5.5%
50
 
5.5%
50
 
5.5%
50
 
5.5%
50
 
5.5%
Other values (32) 299
32.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 591
64.6%
Decimal Number 169
 
18.5%
Space Separator 150
 
16.4%
Dash Punctuation 5
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
57
9.6%
55
9.3%
54
9.1%
50
8.5%
50
8.5%
50
8.5%
50
8.5%
50
8.5%
50
8.5%
20
 
3.4%
Other values (20) 105
17.8%
Decimal Number
ValueCountFrequency (%)
1 34
20.1%
2 34
20.1%
4 19
11.2%
0 17
10.1%
3 17
10.1%
6 17
10.1%
5 13
 
7.7%
7 9
 
5.3%
8 7
 
4.1%
9 2
 
1.2%
Space Separator
ValueCountFrequency (%)
150
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 591
64.6%
Common 324
35.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
57
9.6%
55
9.3%
54
9.1%
50
8.5%
50
8.5%
50
8.5%
50
8.5%
50
8.5%
50
8.5%
20
 
3.4%
Other values (20) 105
17.8%
Common
ValueCountFrequency (%)
150
46.3%
1 34
 
10.5%
2 34
 
10.5%
4 19
 
5.9%
0 17
 
5.2%
3 17
 
5.2%
6 17
 
5.2%
5 13
 
4.0%
7 9
 
2.8%
8 7
 
2.2%
Other values (2) 7
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 591
64.6%
ASCII 324
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
150
46.3%
1 34
 
10.5%
2 34
 
10.5%
4 19
 
5.9%
0 17
 
5.2%
3 17
 
5.2%
6 17
 
5.2%
5 13
 
4.0%
7 9
 
2.8%
8 7
 
2.2%
Other values (2) 7
 
2.2%
Hangul
ValueCountFrequency (%)
57
9.6%
55
9.3%
54
9.1%
50
8.5%
50
8.5%
50
8.5%
50
8.5%
50
8.5%
50
8.5%
20
 
3.4%
Other values (20) 105
17.8%

legaldong_cd
Real number (ℝ)

Distinct10
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1680107 × 109
Minimum1.1680101 × 109
Maximum1.1680118 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:29.344206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1680101 × 109
5-th percentile1.1680101 × 109
Q11.1680103 × 109
median1.1680106 × 109
Q31.1680112 × 109
95-th percentile1.1680118 × 109
Maximum1.1680118 × 109
Range1700
Interquartile range (IQR)875

Descriptive statistics

Standard deviation627.02407
Coefficient of variation (CV)5.3683074 × 10-7
Kurtosis-0.82693516
Mean1.1680107 × 109
Median Absolute Deviation (MAD)300
Skewness0.83598457
Sum5.8400537 × 1010
Variance393159.18
MonotonicityNot monotonic
2023-12-10T22:24:29.582884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1168011800 11
22.0%
1168010100 10
20.0%
1168010300 7
14.0%
1168010600 6
12.0%
1168010700 6
12.0%
1168010500 4
 
8.0%
1168010400 3
 
6.0%
1168010800 1
 
2.0%
1168011300 1
 
2.0%
1168011400 1
 
2.0%
ValueCountFrequency (%)
1168010100 10
20.0%
1168010300 7
14.0%
1168010400 3
 
6.0%
1168010500 4
 
8.0%
1168010600 6
12.0%
1168010700 6
12.0%
1168010800 1
 
2.0%
1168011300 1
 
2.0%
1168011400 1
 
2.0%
1168011800 11
22.0%
ValueCountFrequency (%)
1168011800 11
22.0%
1168011400 1
 
2.0%
1168011300 1
 
2.0%
1168010800 1
 
2.0%
1168010700 6
12.0%
1168010600 6
12.0%
1168010500 4
 
8.0%
1168010400 3
 
6.0%
1168010300 7
14.0%
1168010100 10
20.0%

strd_year
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2022
50 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 50
100.0%

Length

2023-12-10T22:24:29.856310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:24:30.078001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 50
100.0%
Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
0
43 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 43
86.0%
1 7
 
14.0%

Length

2023-12-10T22:24:30.225268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:24:30.411511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43
86.0%
1 7
 
14.0%
Distinct4
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
0
36 
1
12 
3
 
1
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)4.0%

Sample

1st row1
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 36
72.0%
1 12
 
24.0%
3 1
 
2.0%
2 1
 
2.0%

Length

2023-12-10T22:24:30.583309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:24:30.872907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 36
72.0%
1 12
 
24.0%
3 1
 
2.0%
2 1
 
2.0%
Distinct5
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
1
19 
0
11 
2
3
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 19
38.0%
0 11
22.0%
2 9
18.0%
3 8
16.0%
4 3
 
6.0%

Length

2023-12-10T22:24:31.161104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:24:31.409934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 19
38.0%
0 11
22.0%
2 9
18.0%
3 8
16.0%
4 3
 
6.0%

subway_idx
Real number (ℝ)

Distinct10
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.24
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:31.656780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q37.75
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation2.7962073
Coefficient of variation (CV)0.53362736
Kurtosis-1.0758681
Mean5.24
Median Absolute Deviation (MAD)2
Skewness0.25034469
Sum262
Variance7.8187755
MonotonicityNot monotonic
2023-12-10T22:24:31.925449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
3 10
20.0%
4 7
14.0%
8 5
10.0%
7 5
10.0%
5 5
10.0%
1 5
10.0%
10 5
10.0%
9 3
 
6.0%
6 3
 
6.0%
2 2
 
4.0%
ValueCountFrequency (%)
1 5
10.0%
2 2
 
4.0%
3 10
20.0%
4 7
14.0%
5 5
10.0%
6 3
 
6.0%
7 5
10.0%
8 5
10.0%
9 3
 
6.0%
10 5
10.0%
ValueCountFrequency (%)
10 5
10.0%
9 3
 
6.0%
8 5
10.0%
7 5
10.0%
6 3
 
6.0%
5 5
10.0%
4 7
14.0%
3 10
20.0%
2 2
 
4.0%
1 5
10.0%
Distinct46
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-10T22:24:32.299158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length467
Median length369
Mean length187.24
Min length14

Characters and Unicode

Total characters9362
Distinct characters77
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

Unique45 ?
Unique (%)90.0%

Sample

1st row{"data": [{"dist": 375, "poi_nm": "압구정로데오역", "latitude": 37.52738499999999, "longitude": 127.040555}]}
2nd row{"data": [{"dist": 438, "poi_nm": "압구정로데오역", "latitude": 37.52738499999999, "longitude": 127.040555}]}
3rd row{"data": [{"dist": 852, "poi_nm": "대치", "latitude": 37.49427949999999, "longitude": 127.06326649999998}]}
4th row{"data": [{"dist": 811, "poi_nm": "대치", "latitude": 37.49427949999999, "longitude": 127.06326649999998}]}
5th row{"data": [{"dist": 737, "poi_nm": "압구정", "latitude": 37.52668639, "longitude": 127.02836970000001}]}
ValueCountFrequency (%)
longitude 97
 
11.7%
dist 97
 
11.7%
poi_nm 97
 
11.7%
latitude 97
 
11.7%
data 50
 
6.0%
127.04670369999998 10
 
1.2%
37.486846439999994 10
 
1.2%
매봉 10
 
1.2%
37.49091400000001 7
 
0.8%
127.05534839999997 7
 
0.8%
Other values (168) 349
42.0%
2023-12-10T22:24:33.044123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 1070
 
11.4%
9 809
 
8.6%
781
 
8.3%
t 438
 
4.7%
: 438
 
4.7%
0 390
 
4.2%
i 388
 
4.1%
, 343
 
3.7%
d 341
 
3.6%
7 320
 
3.4%
Other values (67) 4044
43.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3051
32.6%
Lowercase Letter 2742
29.3%
Other Punctuation 2045
21.8%
Space Separator 781
 
8.3%
Other Letter 262
 
2.8%
Close Punctuation 192
 
2.1%
Open Punctuation 192
 
2.1%
Connector Punctuation 97
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
35
 
13.4%
16
 
6.1%
14
 
5.3%
14
 
5.3%
14
 
5.3%
13
 
5.0%
12
 
4.6%
12
 
4.6%
11
 
4.2%
10
 
3.8%
Other values (34) 111
42.4%
Lowercase Letter
ValueCountFrequency (%)
t 438
16.0%
i 388
14.2%
d 341
12.4%
l 204
7.4%
u 199
7.3%
n 199
7.3%
a 197
7.2%
o 194
7.1%
e 194
7.1%
s 97
 
3.5%
Other values (3) 291
10.6%
Decimal Number
ValueCountFrequency (%)
9 809
26.5%
0 390
12.8%
7 320
 
10.5%
4 271
 
8.9%
3 245
 
8.0%
2 225
 
7.4%
1 208
 
6.8%
6 204
 
6.7%
5 190
 
6.2%
8 189
 
6.2%
Other Punctuation
ValueCountFrequency (%)
" 1070
52.3%
: 438
21.4%
, 343
 
16.8%
. 194
 
9.5%
Close Punctuation
ValueCountFrequency (%)
} 147
76.6%
] 45
 
23.4%
Open Punctuation
ValueCountFrequency (%)
{ 147
76.6%
[ 45
 
23.4%
Space Separator
ValueCountFrequency (%)
781
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 97
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6358
67.9%
Latin 2742
29.3%
Hangul 262
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
35
 
13.4%
16
 
6.1%
14
 
5.3%
14
 
5.3%
14
 
5.3%
13
 
5.0%
12
 
4.6%
12
 
4.6%
11
 
4.2%
10
 
3.8%
Other values (34) 111
42.4%
Common
ValueCountFrequency (%)
" 1070
16.8%
9 809
12.7%
781
12.3%
: 438
 
6.9%
0 390
 
6.1%
, 343
 
5.4%
7 320
 
5.0%
4 271
 
4.3%
3 245
 
3.9%
2 225
 
3.5%
Other values (10) 1466
23.1%
Latin
ValueCountFrequency (%)
t 438
16.0%
i 388
14.2%
d 341
12.4%
l 204
7.4%
u 199
7.3%
n 199
7.3%
a 197
7.2%
o 194
7.1%
e 194
7.1%
s 97
 
3.5%
Other values (3) 291
10.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9100
97.2%
Hangul 262
 
2.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 1070
 
11.8%
9 809
 
8.9%
781
 
8.6%
t 438
 
4.8%
: 438
 
4.8%
0 390
 
4.3%
i 388
 
4.3%
, 343
 
3.8%
d 341
 
3.7%
7 320
 
3.5%
Other values (23) 3782
41.6%
Hangul
ValueCountFrequency (%)
35
 
13.4%
16
 
6.1%
14
 
5.3%
14
 
5.3%
14
 
5.3%
13
 
5.0%
12
 
4.6%
12
 
4.6%
11
 
4.2%
10
 
3.8%
Other values (34) 111
42.4%

elctyvh_cnt_250mblw
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.7
Minimum0
Maximum83
Zeros10
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:33.249389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.25
median8
Q313.5
95-th percentile76.1
Maximum83
Range83
Interquartile range (IQR)12.25

Descriptive statistics

Standard deviation22.85558
Coefficient of variation (CV)1.4557694
Kurtosis2.8906333
Mean15.7
Median Absolute Deviation (MAD)6.5
Skewness1.933762
Sum785
Variance522.37755
MonotonicityNot monotonic
2023-12-10T22:24:33.483765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 10
20.0%
8 6
12.0%
3 6
12.0%
1 3
 
6.0%
11 3
 
6.0%
12 2
 
4.0%
83 2
 
4.0%
2 2
 
4.0%
9 2
 
4.0%
5 2
 
4.0%
Other values (12) 12
24.0%
ValueCountFrequency (%)
0 10
20.0%
1 3
 
6.0%
2 2
 
4.0%
3 6
12.0%
5 2
 
4.0%
7 1
 
2.0%
8 6
12.0%
9 2
 
4.0%
11 3
 
6.0%
12 2
 
4.0%
ValueCountFrequency (%)
83 2
4.0%
77 1
2.0%
75 1
2.0%
55 1
2.0%
40 1
2.0%
37 1
2.0%
36 1
2.0%
35 1
2.0%
34 1
2.0%
31 1
2.0%
Distinct27
Distinct (%)54.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.12
Minimum1
Maximum106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:33.735112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16.25
median11
Q319
95-th percentile70.45
Maximum106
Range105
Interquartile range (IQR)12.75

Descriptive statistics

Standard deviation21.340428
Coefficient of variation (CV)1.2465203
Kurtosis8.3332673
Mean17.12
Median Absolute Deviation (MAD)6
Skewness2.8508246
Sum856
Variance455.41388
MonotonicityNot monotonic
2023-12-10T22:24:34.000508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1 4
 
8.0%
5 4
 
8.0%
14 3
 
6.0%
22 3
 
6.0%
7 3
 
6.0%
10 3
 
6.0%
8 3
 
6.0%
16 3
 
6.0%
12 2
 
4.0%
19 2
 
4.0%
Other values (17) 20
40.0%
ValueCountFrequency (%)
1 4
8.0%
2 2
4.0%
3 1
 
2.0%
4 1
 
2.0%
5 4
8.0%
6 1
 
2.0%
7 3
6.0%
8 3
6.0%
9 2
4.0%
10 3
6.0%
ValueCountFrequency (%)
106 1
 
2.0%
86 1
 
2.0%
79 1
 
2.0%
60 1
 
2.0%
32 1
 
2.0%
24 1
 
2.0%
23 1
 
2.0%
22 3
6.0%
21 1
 
2.0%
20 1
 
2.0%
Distinct36
Distinct (%)72.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.96
Minimum2
Maximum182
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:34.292552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile13
Q134.25
median57.5
Q385
95-th percentile129.35
Maximum182
Range180
Interquartile range (IQR)50.75

Descriptive statistics

Standard deviation38.754044
Coefficient of variation (CV)0.61553437
Kurtosis0.56986528
Mean62.96
Median Absolute Deviation (MAD)27.5
Skewness0.7372005
Sum3148
Variance1501.8759
MonotonicityNot monotonic
2023-12-10T22:24:34.543969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
57 3
 
6.0%
13 3
 
6.0%
85 3
 
6.0%
60 2
 
4.0%
48 2
 
4.0%
58 2
 
4.0%
36 2
 
4.0%
93 2
 
4.0%
47 2
 
4.0%
27 2
 
4.0%
Other values (26) 27
54.0%
ValueCountFrequency (%)
2 1
 
2.0%
6 1
 
2.0%
13 3
6.0%
14 1
 
2.0%
22 1
 
2.0%
23 1
 
2.0%
25 1
 
2.0%
27 2
4.0%
33 1
 
2.0%
34 1
 
2.0%
ValueCountFrequency (%)
182 1
2.0%
143 1
2.0%
137 1
2.0%
120 1
2.0%
115 1
2.0%
113 1
2.0%
102 1
2.0%
100 1
2.0%
94 1
2.0%
93 2
4.0%

elctyvh_idx
Real number (ℝ)

Distinct8
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.24
Minimum3
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:34.825880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4.45
Q17
median9
Q310
95-th percentile10
Maximum10
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.9225833
Coefficient of variation (CV)0.23332322
Kurtosis0.70345814
Mean8.24
Median Absolute Deviation (MAD)1
Skewness-1.0921598
Sum412
Variance3.6963265
MonotonicityNot monotonic
2023-12-10T22:24:35.153683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
10 19
38.0%
7 9
18.0%
8 8
16.0%
9 7
 
14.0%
5 2
 
4.0%
3 2
 
4.0%
6 2
 
4.0%
4 1
 
2.0%
ValueCountFrequency (%)
3 2
 
4.0%
4 1
 
2.0%
5 2
 
4.0%
6 2
 
4.0%
7 9
18.0%
8 8
16.0%
9 7
 
14.0%
10 19
38.0%
ValueCountFrequency (%)
10 19
38.0%
9 7
 
14.0%
8 8
16.0%
7 9
18.0%
6 2
 
4.0%
5 2
 
4.0%
4 1
 
2.0%
3 2
 
4.0%

elctyvh_info_1kmblw
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-10T22:24:35.600272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length1024
Mean length1024
Min length1024

Characters and Unicode

Total characters51200
Distinct characters206
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)100.0%

Sample

1st row{"data": [{"dist": 700, "poi_nm": "압구정 대원칸타빌아파트", "latitude": 37.52736107776, "longitude": 127.03703623220001}, {"dist": 838, "poi_nm": "청담영풍아파트", "latitude": 37.5191598, "longitude": 127.04469369999998}, {"dist": 838, "poi_nm": "청담영풍아파트", "latitude": 37.5191598, "longitude": 127.04469369999998}, {"dist": 750, "poi_nm": "청담4차이편한세상아파트", "latitude": 37.5207, "longitude": 127.04699999999998}, {"dist": 750, "poi_nm": "청담4차이편한세상아파트", "latitude": 37.5207, "longitude": 127.04699999999998}, {"dist": 750, "poi_nm": "청담4차이편한세상아파트", "latitude": 37.5207, "longitude": 127.04699999999998}, {"dist": 750, "poi_nm": "청담4차이편한세상아파트", "latitude": 37.5207, "longitude": 127.04699999999998}, {"dist": 881, "poi_nm": "삼성청담공원아파트", "latitude": 37.523003362665996, "longitude": 127.05046250089997}, {"dist": 881, "poi_nm": "삼성청담공원아파트", "latitude": 37.523003362665996, "longitude": 127.05046250089997}, {"dist": 881, "poi_nm": "삼성청담공원아파트", "latitude": 37.523003362665996, "longitude": 127.05046250089997}, {"dist": 881, "poi_nm": "삼성청담공원아파트",
2nd row{"data": [{"dist": 777, "poi_nm": "압구정 대원칸타빌아파트", "latitude": 37.52736107776, "longitude": 127.03703623220001}, {"dist": 849, "poi_nm": "청담영풍아파트", "latitude": 37.5191598, "longitude": 127.04469369999998}, {"dist": 849, "poi_nm": "청담영풍아파트", "latitude": 37.5191598, "longitude": 127.04469369999998}, {"dist": 726, "poi_nm": "청담4차이편한세상아파트", "latitude": 37.5207, "longitude": 127.04699999999998}, {"dist": 726, "poi_nm": "청담4차이편한세상아파트", "latitude": 37.5207, "longitude": 127.04699999999998}, {"dist": 726, "poi_nm": "청담4차이편한세상아파트", "latitude": 37.5207, "longitude": 127.04699999999998}, {"dist": 726, "poi_nm": "청담4차이편한세상아파트", "latitude": 37.5207, "longitude": 127.04699999999998}, {"dist": 811, "poi_nm": "삼성청담공원아파트", "latitude": 37.523003362665996, "longitude": 127.05046250089997}, {"dist": 811, "poi_nm": "삼성청담공원아파트", "latitude": 37.523003362665996, "longitude": 127.05046250089997}, {"dist": 811, "poi_nm": "삼성청담공원아파트", "latitude": 37.523003362665996, "longitude": 127.05046250089997}, {"dist": 811, "poi_nm": "삼성청담공원아파트",
3rd row{"data": [{"dist": 650, "poi_nm": "아우디_대치 전시장", "latitude": 37.50301900000001, "longitude": 127.06699000000002}, {"dist": 761, "poi_nm": "풍림아이원3차", "latitude": 37.50465799999999, "longitude": 127.06679030000001}, {"dist": 761, "poi_nm": "풍림아이원3차", "latitude": 37.50465799999999, "longitude": 127.06679030000001}, {"dist": 874, "poi_nm": "롯데하이마트 대치점", "latitude": 37.49421, "longitude": 127.06382599999999}, {"dist": 748, "poi_nm": "대치동풍림아이원3 4차아파트", "latitude": 37.50466029999999, "longitude": 127.06664539999998}, {"dist": 748, "poi_nm": "대치동풍림아이원3 4차아파트", "latitude": 37.50466029999999, "longitude": 127.06664539999998}, {"dist": 414, "poi_nm": "래미안대치하이스턴 아파트", "latitude": 37.5015124522, "longitude": 127.0654756841}, {"dist": 414, "poi_nm": "래미안대치하이스턴 아파트", "latitude": 37.5015124522, "longitude": 127.0654756841}, {"dist": 333, "poi_nm": "대치2문화센터 공영주차장", "latitude": 37.50233305982701, "longitude": 127.06421428139998}, {"dist": 669, "poi_nm": "서울시 강남구 컬쳐랜드타워(직원전용)", "latitude": 37.5038048, "longitude": 127.0665919999
4th row{"data": [{"dist": 755, "poi_nm": "아우디_대치 전시장", "latitude": 37.50301900000001, "longitude": 127.06699000000002}, {"dist": 889, "poi_nm": "풍림아이원3차", "latitude": 37.50465799999999, "longitude": 127.06679030000001}, {"dist": 889, "poi_nm": "풍림아이원3차", "latitude": 37.50465799999999, "longitude": 127.06679030000001}, {"dist": 841, "poi_nm": "롯데하이마트 대치점", "latitude": 37.49421, "longitude": 127.06382599999999}, {"dist": 878, "poi_nm": "대치동풍림아이원3 4차아파트", "latitude": 37.50466029999999, "longitude": 127.06664539999998}, {"dist": 878, "poi_nm": "대치동풍림아이원3 4차아파트", "latitude": 37.50466029999999, "longitude": 127.06664539999998}, {"dist": 503, "poi_nm": "래미안대치하이스턴 아파트", "latitude": 37.5015124522, "longitude": 127.0654756841}, {"dist": 503, "poi_nm": "래미안대치하이스턴 아파트", "latitude": 37.5015124522, "longitude": 127.0654756841}, {"dist": 454, "poi_nm": "대치2문화센터 공영주차장", "latitude": 37.50233305982701, "longitude": 127.06421428139998}, {"dist": 788, "poi_nm": "서울시 강남구 컬쳐랜드타워(직원전용)", "latitude": 37.5038048, "longitude": 127.0665919999
5th row{"data": [{"dist": 866, "poi_nm": "서울서초 롯데캐슬갤럭시1차", "latitude": 37.52038934211899, "longitude": 127.0159771234}, {"dist": 866, "poi_nm": "서울서초 롯데캐슬갤럭시1차", "latitude": 37.52038934211899, "longitude": 127.0159771234}, {"dist": 866, "poi_nm": "서울서초 롯데캐슬갤럭시1차", "latitude": 37.52038934211899, "longitude": 127.0159771234}, {"dist": 866, "poi_nm": "서울서초 롯데캐슬갤럭시1차", "latitude": 37.52038934211899, "longitude": 127.0159771234}, {"dist": 576, "poi_nm": "압구정 428 공영주차장1", "latitude": 37.526628658353, "longitude": 127.0264263189}, {"dist": 576, "poi_nm": "압구정 428 공영주차장1", "latitude": 37.526628658353, "longitude": 127.0264263189}, {"dist": 576, "poi_nm": "압구정 428 공영주차장1", "latitude": 37.526628658353, "longitude": 127.0264263189}, {"dist": 576, "poi_nm": "압구정 428 공영주차장1", "latitude": 37.526628658353, "longitude": 127.0264263189}, {"dist": 576, "poi_nm": "압구정 428 공영주차장1", "latitude": 37.526628658353, "longitude": 127.0264263189}, {"dist": 576, "poi_nm": "압구정 428 공영주차장1", "latitude": 37.526628658353, "longitude": 127.026426318
ValueCountFrequency (%)
dist 525
 
11.6%
poi_nm 523
 
11.5%
latitude 509
 
11.2%
longitude 499
 
11.0%
data 50
 
1.1%
b4f)(구 40
 
0.9%
압구정 33
 
0.7%
105동 32
 
0.7%
개포래미안포레스트1(a블럭 32
 
0.7%
개포래미안포레스트(구 30
 
0.7%
Other values (539) 2266
49.9%
2023-12-10T22:24:36.253490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 5252
 
10.3%
4496
 
8.8%
9 3459
 
6.8%
0 2159
 
4.2%
: 2104
 
4.1%
t 2095
 
4.1%
i 2063
 
4.0%
, 2018
 
3.9%
7 1766
 
3.4%
d 1586
 
3.1%
Other values (196) 24202
47.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15953
31.2%
Lowercase Letter 13515
26.4%
Other Punctuation 10377
20.3%
Other Letter 4633
 
9.0%
Space Separator 4496
 
8.8%
Open Punctuation 815
 
1.6%
Close Punctuation 670
 
1.3%
Connector Punctuation 544
 
1.1%
Uppercase Letter 197
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
229
 
4.9%
207
 
4.5%
191
 
4.1%
172
 
3.7%
148
 
3.2%
147
 
3.2%
145
 
3.1%
117
 
2.5%
113
 
2.4%
113
 
2.4%
Other values (148) 3051
65.9%
Lowercase Letter
ValueCountFrequency (%)
t 2095
15.5%
i 2063
15.3%
d 1586
11.7%
o 1025
7.6%
n 1025
7.6%
l 1012
7.5%
u 1010
7.5%
e 1008
7.5%
a 610
 
4.5%
s 527
 
3.9%
Other values (6) 1554
11.5%
Decimal Number
ValueCountFrequency (%)
9 3459
21.7%
0 2159
13.5%
7 1766
11.1%
1 1572
9.9%
3 1496
9.4%
2 1407
8.8%
5 1103
 
6.9%
4 1096
 
6.9%
8 965
 
6.0%
6 930
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
B 55
27.9%
F 52
26.4%
A 50
25.4%
S 14
 
7.1%
H 12
 
6.1%
E 4
 
2.0%
K 3
 
1.5%
W 3
 
1.5%
T 2
 
1.0%
C 2
 
1.0%
Other Punctuation
ValueCountFrequency (%)
" 5252
50.6%
: 2104
20.3%
, 2018
 
19.4%
. 1001
 
9.6%
/ 2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
{ 578
70.9%
( 187
 
22.9%
[ 50
 
6.1%
Close Punctuation
ValueCountFrequency (%)
} 484
72.2%
) 186
 
27.8%
Space Separator
ValueCountFrequency (%)
4496
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 544
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32855
64.2%
Latin 13712
26.8%
Hangul 4633
 
9.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
229
 
4.9%
207
 
4.5%
191
 
4.1%
172
 
3.7%
148
 
3.2%
147
 
3.2%
145
 
3.1%
117
 
2.5%
113
 
2.4%
113
 
2.4%
Other values (148) 3051
65.9%
Latin
ValueCountFrequency (%)
t 2095
15.3%
i 2063
15.0%
d 1586
11.6%
o 1025
7.5%
n 1025
7.5%
l 1012
7.4%
u 1010
7.4%
e 1008
7.4%
a 610
 
4.4%
s 527
 
3.8%
Other values (16) 1751
12.8%
Common
ValueCountFrequency (%)
" 5252
16.0%
4496
13.7%
9 3459
10.5%
0 2159
 
6.6%
: 2104
 
6.4%
, 2018
 
6.1%
7 1766
 
5.4%
1 1572
 
4.8%
3 1496
 
4.6%
2 1407
 
4.3%
Other values (12) 7126
21.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46567
91.0%
Hangul 4633
 
9.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 5252
 
11.3%
4496
 
9.7%
9 3459
 
7.4%
0 2159
 
4.6%
: 2104
 
4.5%
t 2095
 
4.5%
i 2063
 
4.4%
, 2018
 
4.3%
7 1766
 
3.8%
d 1586
 
3.4%
Other values (38) 19569
42.0%
Hangul
ValueCountFrequency (%)
229
 
4.9%
207
 
4.5%
191
 
4.1%
172
 
3.7%
148
 
3.2%
147
 
3.2%
145
 
3.1%
117
 
2.5%
113
 
2.4%
113
 
2.4%
Other values (148) 3051
65.9%

cafe_cnt_250mblw
Real number (ℝ)

Distinct25
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.78
Minimum1
Maximum46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:36.459385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median10.5
Q324
95-th percentile38.75
Maximum46
Range45
Interquartile range (IQR)21

Descriptive statistics

Standard deviation12.944607
Coefficient of variation (CV)0.87581917
Kurtosis-0.62815154
Mean14.78
Median Absolute Deviation (MAD)8.5
Skewness0.67134724
Sum739
Variance167.56286
MonotonicityNot monotonic
2023-12-10T22:24:36.627904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3 6
 
12.0%
1 5
 
10.0%
2 5
 
10.0%
8 3
 
6.0%
25 3
 
6.0%
4 2
 
4.0%
5 2
 
4.0%
30 2
 
4.0%
16 2
 
4.0%
19 2
 
4.0%
Other values (15) 18
36.0%
ValueCountFrequency (%)
1 5
10.0%
2 5
10.0%
3 6
12.0%
4 2
 
4.0%
5 2
 
4.0%
7 1
 
2.0%
8 3
6.0%
10 1
 
2.0%
11 1
 
2.0%
16 2
 
4.0%
ValueCountFrequency (%)
46 1
 
2.0%
42 1
 
2.0%
41 1
 
2.0%
36 1
 
2.0%
34 2
4.0%
30 2
4.0%
27 1
 
2.0%
25 3
6.0%
24 2
4.0%
23 1
 
2.0%

cafe_cnt_250movr_500mblw
Real number (ℝ)

ZEROS 

Distinct34
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.72
Minimum0
Maximum59
Zeros1
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:36.824435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.9
Q19.5
median24
Q336.5
95-th percentile54.55
Maximum59
Range59
Interquartile range (IQR)27

Descriptive statistics

Standard deviation17.06774
Coefficient of variation (CV)0.69044256
Kurtosis-1.0056737
Mean24.72
Median Absolute Deviation (MAD)13.5
Skewness0.38420066
Sum1236
Variance291.30776
MonotonicityNot monotonic
2023-12-10T22:24:37.399943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
24 3
 
6.0%
11 3
 
6.0%
34 3
 
6.0%
12 3
 
6.0%
8 3
 
6.0%
6 3
 
6.0%
40 2
 
4.0%
31 2
 
4.0%
44 2
 
4.0%
33 2
 
4.0%
Other values (24) 24
48.0%
ValueCountFrequency (%)
0 1
 
2.0%
1 1
 
2.0%
2 1
 
2.0%
4 1
 
2.0%
5 1
 
2.0%
6 3
6.0%
7 1
 
2.0%
8 3
6.0%
9 1
 
2.0%
11 3
6.0%
ValueCountFrequency (%)
59 1
2.0%
58 1
2.0%
55 1
2.0%
54 1
2.0%
51 1
2.0%
49 1
2.0%
48 1
2.0%
44 2
4.0%
40 2
4.0%
38 1
2.0%

cafe_cnt_500movr_1kmblw
Real number (ℝ)

Distinct44
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.6
Minimum4
Maximum281
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:37.672925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile47.8
Q169.25
median104
Q3151.75
95-th percentile192.55
Maximum281
Range277
Interquartile range (IQR)82.5

Descriptive statistics

Standard deviation56.518734
Coefficient of variation (CV)0.49752407
Kurtosis0.087844978
Mean113.6
Median Absolute Deviation (MAD)39
Skewness0.60254783
Sum5680
Variance3194.3673
MonotonicityNot monotonic
2023-12-10T22:24:37.871651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
53 2
 
4.0%
120 2
 
4.0%
184 2
 
4.0%
91 2
 
4.0%
62 2
 
4.0%
104 2
 
4.0%
63 1
 
2.0%
105 1
 
2.0%
72 1
 
2.0%
51 1
 
2.0%
Other values (34) 34
68.0%
ValueCountFrequency (%)
4 1
2.0%
32 1
2.0%
46 1
2.0%
50 1
2.0%
51 1
2.0%
53 2
4.0%
56 1
2.0%
62 2
4.0%
63 1
2.0%
67 1
2.0%
ValueCountFrequency (%)
281 1
2.0%
201 1
2.0%
193 1
2.0%
192 1
2.0%
190 1
2.0%
188 1
2.0%
186 1
2.0%
185 1
2.0%
184 2
4.0%
180 1
2.0%

cafe_idx
Real number (ℝ)

Distinct7
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.66
Minimum2
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:38.053595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q18
median10
Q310
95-th percentile10
Maximum10
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.8473367
Coefficient of variation (CV)0.21331833
Kurtosis2.2968122
Mean8.66
Median Absolute Deviation (MAD)0
Skewness-1.5392427
Sum433
Variance3.4126531
MonotonicityNot monotonic
2023-12-10T22:24:38.247043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
10 26
52.0%
8 7
 
14.0%
9 6
 
12.0%
7 4
 
8.0%
6 3
 
6.0%
5 3
 
6.0%
2 1
 
2.0%
ValueCountFrequency (%)
2 1
 
2.0%
5 3
 
6.0%
6 3
 
6.0%
7 4
 
8.0%
8 7
 
14.0%
9 6
 
12.0%
10 26
52.0%
ValueCountFrequency (%)
10 26
52.0%
9 6
 
12.0%
8 7
 
14.0%
7 4
 
8.0%
6 3
 
6.0%
5 3
 
6.0%
2 1
 
2.0%

cafe_info_1kmblw
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-10T22:24:38.686149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length1024
Mean length1015.66
Min length607

Characters and Unicode

Total characters50783
Distinct characters374
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)100.0%

Sample

1st row{"data": [{"dist": 678, "poi_nm": "트리아농", "latitude": 37.5203171345118, "longitude": 127.04458748758798}, {"dist": 931, "poi_nm": "칠요일의케이크", "latitude": 37.5185761769019, "longitude": 127.045165613999}, {"dist": 942, "poi_nm": "리프레쉬먼트 디저트샵", "latitude": 37.518281747244295, "longitude": 127.042192716608}, {"dist": 903, "poi_nm": "5어클락", "latitude": 37.5186665040818, "longitude": 127.044568406578}, {"dist": 850, "poi_nm": "욜로", "latitude": 37.51897305715989, "longitude": 127.04400299770401}, {"dist": 945, "poi_nm": "쁠로 청담", "latitude": 37.51844287510839, "longitude": 127.04504336681997}, {"dist": 945, "poi_nm": "마&모", "latitude": 37.51844287510839, "longitude": 127.04504336681997}, {"dist": 837, "poi_nm": "영영브런치카페", "latitude": 37.51902956358528, "longitude": 127.04223838500201}, {"dist": 757, "poi_nm": "영재오행운길북카페", "latitude": 37.519700915086, "longitude": 127.044410654744}, {"dist": 995, "poi_nm": "까모메", "latitude": 37.518388339169995, "longitude": 127.04627405088202}, {"dist": 907, "poi_nm": "이즈카페 청담점", "lat
2nd row{"data": [{"dist": 687, "poi_nm": "트리아농", "latitude": 37.5203171345118, "longitude": 127.04458748758798}, {"dist": 938, "poi_nm": "칠요일의케이크", "latitude": 37.5185761769019, "longitude": 127.045165613999}, {"dist": 980, "poi_nm": "리프레쉬먼트 디저트샵", "latitude": 37.518281747244295, "longitude": 127.042192716608}, {"dist": 916, "poi_nm": "5어클락", "latitude": 37.5186665040818, "longitude": 127.044568406578}, {"dist": 869, "poi_nm": "욜로", "latitude": 37.51897305715989, "longitude": 127.04400299770401}, {"dist": 954, "poi_nm": "쁠로 청담", "latitude": 37.51844287510839, "longitude": 127.04504336681997}, {"dist": 954, "poi_nm": "마&모", "latitude": 37.51844287510839, "longitude": 127.04504336681997}, {"dist": 875, "poi_nm": "영영브런치카페", "latitude": 37.51902956358528, "longitude": 127.04223838500201}, {"dist": 770, "poi_nm": "영재오행운길북카페", "latitude": 37.519700915086, "longitude": 127.044410654744}, {"dist": 993, "poi_nm": "까모메", "latitude": 37.518388339169995, "longitude": 127.04627405088202}, {"dist": 920, "poi_nm": "이즈카페 청담점", "lat
3rd row{"data": [{"dist": 876, "poi_nm": "126카페", "latitude": 37.49504275183408, "longitude": 127.066328328907}, {"dist": 918, "poi_nm": "아므네", "latitude": 37.49480835344529, "longitude": 127.06657124742198}, {"dist": 932, "poi_nm": "카페바라", "latitude": 37.49470741906618, "longitude": 127.066609605582}, {"dist": 804, "poi_nm": "스타벅스 스탈릿대치R점", "latitude": 37.49456362547089, "longitude": 127.06264371300797}, {"dist": 937, "poi_nm": "스타벅스 대치역점", "latitude": 37.493589085360476, "longitude": 127.06198138142197}, {"dist": 910, "poi_nm": "메가커피 대치역점", "latitude": 37.493830048131386, "longitude": 127.062940501494}, {"dist": 909, "poi_nm": "공차 대치점", "latitude": 37.49381664910497, "longitude": 127.06272224531001}, {"dist": 971, "poi_nm": "바나프레소 대치역점", "latitude": 37.493347648798476, "longitude": 127.061917857343}, {"dist": 729, "poi_nm": "커피인류 대치은마점", "latitude": 37.49517774826838, "longitude": 127.063326112416}, {"dist": 726, "poi_nm": "선유도커피집", "latitude": 37.4953287810752, "longitude": 127.06395045566902}, {"dist": 969, "poi
4th row{"data": [{"dist": 874, "poi_nm": "126카페", "latitude": 37.49504275183408, "longitude": 127.066328328907}, {"dist": 916, "poi_nm": "아므네", "latitude": 37.49480835344529, "longitude": 127.06657124742198}, {"dist": 930, "poi_nm": "카페바라", "latitude": 37.49470741906618, "longitude": 127.066609605582}, {"dist": 754, "poi_nm": "스타벅스 스탈릿대치R점", "latitude": 37.49456362547089, "longitude": 127.06264371300797}, {"dist": 875, "poi_nm": "스타벅스 대치역점", "latitude": 37.493589085360476, "longitude": 127.06198138142197}, {"dist": 861, "poi_nm": "메가커피 대치역점", "latitude": 37.493830048131386, "longitude": 127.062940501494}, {"dist": 858, "poi_nm": "공차 대치점", "latitude": 37.49381664910497, "longitude": 127.06272224531001}, {"dist": 908, "poi_nm": "바나프레소 대치역점", "latitude": 37.493347648798476, "longitude": 127.061917857343}, {"dist": 694, "poi_nm": "커피인류 대치은마점", "latitude": 37.49517774826838, "longitude": 127.063326112416}, {"dist": 701, "poi_nm": "선유도커피집", "latitude": 37.4953287810752, "longitude": 127.06395045566902}, {"dist": 907, "poi
5th row{"data": [{"dist": 831, "poi_nm": "스타벅스 을지병원사거리점", "latitude": 37.51921565914219, "longitude": 127.02858733611201}, {"dist": 914, "poi_nm": "주식회사 누리풋볼", "latitude": 37.5186641592871, "longitude": 127.02894005318699}, {"dist": 885, "poi_nm": "허니크록", "latitude": 37.51882998145972, "longitude": 127.02878627670798}, {"dist": 983, "poi_nm": "엠포리아 메이플가든", "latitude": 37.520267386573586, "longitude": 127.03113520423499}, {"dist": 885, "poi_nm": "아라비카클래식", "latitude": 37.51926234171461, "longitude": 127.02927964025402}, {"dist": 914, "poi_nm": "루씨앤정", "latitude": 37.523795651781185, "longitude": 127.031367446495}, {"dist": 609, "poi_nm": "스타벅스 압구정윤성빌딩점", "latitude": 37.5228304757948, "longitude": 127.02861586506798}, {"dist": 772, "poi_nm": "엉플레", "latitude": 37.52192375056651, "longitude": 127.029893805275}, {"dist": 791, "poi_nm": "빌리엔젤 압구정역점", "latitude": 37.523060716662904, "longitude": 127.0302834069}, {"dist": 910, "poi_nm": "탐스커버리 도산로점", "latitude": 37.5217738656036, "longitude": 127.03112678043101}, {"dist":
ValueCountFrequency (%)
dist 542
 
12.4%
poi_nm 523
 
11.9%
latitude 497
 
11.3%
longitude 496
 
11.3%
data 50
 
1.1%
스타벅스 31
 
0.7%
투썸플레이스 13
 
0.3%
양재점 10
 
0.2%
도곡점 10
 
0.2%
대치역점 10
 
0.2%
Other values (1138) 2206
50.3%
2023-12-10T22:24:39.413029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 5268
 
10.4%
4343
 
8.6%
7 2392
 
4.7%
: 2105
 
4.1%
t 2092
 
4.1%
i 2067
 
4.1%
, 2032
 
4.0%
1 1865
 
3.7%
9 1864
 
3.7%
2 1777
 
3.5%
Other values (364) 24978
49.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17618
34.7%
Lowercase Letter 13492
26.6%
Other Punctuation 10404
20.5%
Space Separator 4343
 
8.6%
Other Letter 3224
 
6.3%
Open Punctuation 642
 
1.3%
Connector Punctuation 525
 
1.0%
Close Punctuation 495
 
1.0%
Uppercase Letter 40
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
209
 
6.5%
178
 
5.5%
118
 
3.7%
117
 
3.6%
107
 
3.3%
102
 
3.2%
83
 
2.6%
72
 
2.2%
63
 
2.0%
49
 
1.5%
Other values (315) 2126
65.9%
Lowercase Letter
ValueCountFrequency (%)
t 2092
15.5%
i 2067
15.3%
d 1586
11.8%
o 1025
7.6%
n 1020
7.6%
l 1003
7.4%
e 997
7.4%
u 994
7.4%
a 608
 
4.5%
s 545
 
4.0%
Other values (6) 1555
11.5%
Uppercase Letter
ValueCountFrequency (%)
S 7
17.5%
A 7
17.5%
C 6
15.0%
R 6
15.0%
G 5
12.5%
L 4
10.0%
D 1
 
2.5%
O 1
 
2.5%
M 1
 
2.5%
N 1
 
2.5%
Decimal Number
ValueCountFrequency (%)
7 2392
13.6%
1 1865
10.6%
9 1864
10.6%
2 1777
10.1%
0 1731
9.8%
4 1724
9.8%
3 1717
9.7%
5 1640
9.3%
8 1543
8.8%
6 1365
7.7%
Other Punctuation
ValueCountFrequency (%)
" 5268
50.6%
: 2105
 
20.2%
, 2032
 
19.5%
. 993
 
9.5%
& 5
 
< 0.1%
% 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
{ 592
92.2%
[ 50
 
7.8%
Close Punctuation
ValueCountFrequency (%)
} 494
99.8%
] 1
 
0.2%
Space Separator
ValueCountFrequency (%)
4343
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 525
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34027
67.0%
Latin 13532
 
26.6%
Hangul 3224
 
6.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
209
 
6.5%
178
 
5.5%
118
 
3.7%
117
 
3.6%
107
 
3.3%
102
 
3.2%
83
 
2.6%
72
 
2.2%
63
 
2.0%
49
 
1.5%
Other values (315) 2126
65.9%
Latin
ValueCountFrequency (%)
t 2092
15.5%
i 2067
15.3%
d 1586
11.7%
o 1025
7.6%
n 1020
7.5%
l 1003
7.4%
e 997
7.4%
u 994
7.3%
a 608
 
4.5%
s 545
 
4.0%
Other values (17) 1595
11.8%
Common
ValueCountFrequency (%)
" 5268
15.5%
4343
12.8%
7 2392
 
7.0%
: 2105
 
6.2%
, 2032
 
6.0%
1 1865
 
5.5%
9 1864
 
5.5%
2 1777
 
5.2%
0 1731
 
5.1%
4 1724
 
5.1%
Other values (12) 8926
26.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47559
93.7%
Hangul 3224
 
6.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 5268
 
11.1%
4343
 
9.1%
7 2392
 
5.0%
: 2105
 
4.4%
t 2092
 
4.4%
i 2067
 
4.3%
, 2032
 
4.3%
1 1865
 
3.9%
9 1864
 
3.9%
2 1777
 
3.7%
Other values (39) 21754
45.7%
Hangul
ValueCountFrequency (%)
209
 
6.5%
178
 
5.5%
118
 
3.7%
117
 
3.6%
107
 
3.3%
102
 
3.2%
83
 
2.6%
72
 
2.2%
63
 
2.0%
49
 
1.5%
Other values (315) 2126
65.9%

spml_cnt_1kmblw
Categorical

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
0
44 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 44
88.0%
1 6
 
12.0%

Length

2023-12-10T22:24:39.653659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:24:39.807503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 44
88.0%
1 6
 
12.0%

spml_cnt_1kmovr_5kmblw
Real number (ℝ)

Distinct6
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.96
Minimum2
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:39.958040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q13.25
median4
Q34
95-th percentile6
Maximum7
Range5
Interquartile range (IQR)0.75

Descriptive statistics

Standard deviation1.0682811
Coefficient of variation (CV)0.26976795
Kurtosis0.81247929
Mean3.96
Median Absolute Deviation (MAD)0
Skewness0.29143793
Sum198
Variance1.1412245
MonotonicityNot monotonic
2023-12-10T22:24:40.148636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
4 26
52.0%
3 8
 
16.0%
5 7
 
14.0%
2 5
 
10.0%
6 3
 
6.0%
7 1
 
2.0%
ValueCountFrequency (%)
2 5
 
10.0%
3 8
 
16.0%
4 26
52.0%
5 7
 
14.0%
6 3
 
6.0%
7 1
 
2.0%
ValueCountFrequency (%)
7 1
 
2.0%
6 3
 
6.0%
5 7
 
14.0%
4 26
52.0%
3 8
 
16.0%
2 5
 
10.0%

spml_cnt_5kmovr_10kmblw
Real number (ℝ)

Distinct8
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.1
Minimum8
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:40.371596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile9
Q110
median10
Q313
95-th percentile15
Maximum15
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.8979043
Coefficient of variation (CV)0.17098237
Kurtosis-0.39652646
Mean11.1
Median Absolute Deviation (MAD)1
Skewness0.82094426
Sum555
Variance3.6020408
MonotonicityNot monotonic
2023-12-10T22:24:40.548486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
10 21
42.0%
13 8
 
16.0%
11 6
 
12.0%
9 6
 
12.0%
15 5
 
10.0%
12 2
 
4.0%
14 1
 
2.0%
8 1
 
2.0%
ValueCountFrequency (%)
8 1
 
2.0%
9 6
 
12.0%
10 21
42.0%
11 6
 
12.0%
12 2
 
4.0%
13 8
 
16.0%
14 1
 
2.0%
15 5
 
10.0%
ValueCountFrequency (%)
15 5
 
10.0%
14 1
 
2.0%
13 8
 
16.0%
12 2
 
4.0%
11 6
 
12.0%
10 21
42.0%
9 6
 
12.0%
8 1
 
2.0%

spml_idx
Categorical

Distinct3
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
7
38 
8
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7
2nd row7
3rd row7
4th row7
5th row7

Common Values

ValueCountFrequency (%)
7 38
76.0%
8 6
 
12.0%
6 6
 
12.0%

Length

2023-12-10T22:24:40.746568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:24:40.896098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7 38
76.0%
8 6
 
12.0%
6 6
 
12.0%

spml_info_10kmblw
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-10T22:24:41.186841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length1024
Mean length1024
Min length1024

Characters and Unicode

Total characters51200
Distinct characters83
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

Unique50 ?
Unique (%)100.0%

Sample

1st row{"data": [{"dist": 3653, "poi_nm": "이마트 역삼점", "latitude": 37.49930420889, "longitude": 127.04839738379499}, {"dist": 4700, "poi_nm": "한두레마트 대치점", "latitude": 37.49592343539237, "longitude": 127.06396905608298}, {"dist": 9544, "poi_nm": "롯데마트 송파점", "latitude": 37.49173383860761, "longitude": 127.117749483852}, {"dist": 8925, "poi_nm": "이마트 이수점", "latitude": 37.48455586984431, "longitude": 126.98083525574002}, {"dist": 8664, "poi_nm": "이마트 양재점", "latitude": 37.46339410878719, "longitude": 127.037012004407}, {"dist": 8875, "poi_nm": "코스트코 양재점", "latitude": 37.461931090225605, "longitude": 127.03628787682797}, {"dist": 6243, "poi_nm": "롯데마트 잠실점", "latitude": 37.5117013922435, "longitude": 127.09647144413502}, {"dist": 4506, "poi_nm": "킴스클럽 강남점", "latitude": 37.50923936481699, "longitude": 127.00743769002499}, {"dist": 9122, "poi_nm": "롯데마트 서울역점", "latitude": 37.55576718508408, "longitude": 126.97037108834101}, {"dist": 8875, "poi_nm": "홈플러스 면목점", "latitude": 37.58052702977879, "longitude": 127.08197403840602}, {"
2nd row{"data": [{"dist": 3666, "poi_nm": "이마트 역삼점", "latitude": 37.49930420889, "longitude": 127.04839738379499}, {"dist": 4682, "poi_nm": "한두레마트 대치점", "latitude": 37.49592343539237, "longitude": 127.06396905608298}, {"dist": 9484, "poi_nm": "롯데마트 송파점", "latitude": 37.49173383860761, "longitude": 127.117749483852}, {"dist": 9013, "poi_nm": "이마트 이수점", "latitude": 37.48455586984431, "longitude": 126.98083525574002}, {"dist": 8698, "poi_nm": "이마트 양재점", "latitude": 37.46339410878719, "longitude": 127.037012004407}, {"dist": 8909, "poi_nm": "코스트코 양재점", "latitude": 37.461931090225605, "longitude": 127.03628787682797}, {"dist": 6170, "poi_nm": "롯데마트 잠실점", "latitude": 37.5117013922435, "longitude": 127.09647144413502}, {"dist": 4598, "poi_nm": "킴스클럽 강남점", "latitude": 37.50923936481699, "longitude": 127.00743769002499}, {"dist": 9196, "poi_nm": "롯데마트 서울역점", "latitude": 37.55576718508408, "longitude": 126.97037108834101}, {"dist": 8845, "poi_nm": "홈플러스 면목점", "latitude": 37.58052702977879, "longitude": 127.08197403840602}, {"
3rd row{"data": [{"dist": 1300, "poi_nm": "이마트 역삼점", "latitude": 37.49930420889, "longitude": 127.04839738379499}, {"dist": 647, "poi_nm": "한두레마트 대치점", "latitude": 37.49592343539237, "longitude": 127.06396905608298}, {"dist": 6314, "poi_nm": "롯데마트 송파점", "latitude": 37.49173383860761, "longitude": 127.117749483852}, {"dist": 9561, "poi_nm": "홈플러스 서울남현점", "latitude": 37.47147887868318, "longitude": 126.98251394612197}, {"dist": 9100, "poi_nm": "이마트 이수점", "latitude": 37.48455586984431, "longitude": 126.98083525574002}, {"dist": 5789, "poi_nm": "이마트 양재점", "latitude": 37.46339410878719, "longitude": 127.037012004407}, {"dist": 6008, "poi_nm": "코스트코 양재점", "latitude": 37.461931090225605, "longitude": 127.03628787682797}, {"dist": 4148, "poi_nm": "롯데마트 잠실점", "latitude": 37.5117013922435, "longitude": 127.09647144413502}, {"dist": 6934, "poi_nm": "이마트 가든파이브점", "latitude": 37.47915335636241, "longitude": 127.11836060535099}, {"dist": 7727, "poi_nm": "킴스클럽 송파점", "latitude": 37.478138548444996, "longitude": 127.12560593297098},
4th row{"data": [{"dist": 1403, "poi_nm": "이마트 역삼점", "latitude": 37.49930420889, "longitude": 127.04839738379499}, {"dist": 626, "poi_nm": "한두레마트 대치점", "latitude": 37.49592343539237, "longitude": 127.06396905608298}, {"dist": 6374, "poi_nm": "롯데마트 송파점", "latitude": 37.49173383860761, "longitude": 127.117749483852}, {"dist": 9603, "poi_nm": "홈플러스 서울남현점", "latitude": 37.47147887868318, "longitude": 126.98251394612197}, {"dist": 9179, "poi_nm": "이마트 이수점", "latitude": 37.48455586984431, "longitude": 126.98083525574002}, {"dist": 5764, "poi_nm": "이마트 양재점", "latitude": 37.46339410878719, "longitude": 127.037012004407}, {"dist": 5984, "poi_nm": "코스트코 양재점", "latitude": 37.461931090225605, "longitude": 127.03628787682797}, {"dist": 4238, "poi_nm": "롯데마트 잠실점", "latitude": 37.5117013922435, "longitude": 127.09647144413502}, {"dist": 6975, "poi_nm": "이마트 가든파이브점", "latitude": 37.47915335636241, "longitude": 127.11836060535099}, {"dist": 7770, "poi_nm": "킴스클럽 송파점", "latitude": 37.478138548444996, "longitude": 127.12560593297098},
5th row{"data": [{"dist": 4383, "poi_nm": "이마트 역삼점", "latitude": 37.49930420889, "longitude": 127.04839738379499}, {"dist": 5948, "poi_nm": "한두레마트 대치점", "latitude": 37.49592343539237, "longitude": 127.06396905608298}, {"dist": 9278, "poi_nm": "월드마트", "latitude": 37.50426853747387, "longitude": 126.94304256489698}, {"dist": 8835, "poi_nm": "수협바다마트 노량진점", "latitude": 37.51070809589241, "longitude": 126.945107507463}, {"dist": 8537, "poi_nm": "홈플러스 서울남현점", "latitude": 37.47147887868318, "longitude": 126.98251394612197}, {"dist": 7165, "poi_nm": "이마트 이수점", "latitude": 37.48455586984431, "longitude": 126.98083525574002}, {"dist": 8536, "poi_nm": "이마트 양재점", "latitude": 37.46339410878719, "longitude": 127.037012004407}, {"dist": 8724, "poi_nm": "코스트코 양재점", "latitude": 37.461931090225605, "longitude": 127.03628787682797}, {"dist": 8320, "poi_nm": "롯데마트 잠실점", "latitude": 37.5117013922435, "longitude": 127.09647144413502}, {"dist": 2608, "poi_nm": "킴스클럽 강남점", "latitude": 37.50923936481699, "longitude": 127.00743769002499}, {"
ValueCountFrequency (%)
poi_nm 500
 
11.0%
latitude 500
 
11.0%
dist 500
 
11.0%
longitude 500
 
11.0%
이마트 192
 
4.2%
양재점 100
 
2.2%
롯데마트 97
 
2.1%
송파점 74
 
1.6%
킴스클럽 51
 
1.1%
잠실점 51
 
1.1%
Other values (543) 1988
43.7%
2023-12-10T22:24:41.855202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 5110
 
10.0%
4515
 
8.8%
7 2383
 
4.7%
3 2284
 
4.5%
t 2050
 
4.0%
: 2050
 
4.0%
9 2025
 
4.0%
i 2001
 
3.9%
, 1986
 
3.9%
1 1875
 
3.7%
Other values (73) 24921
48.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18167
35.5%
Lowercase Letter 13202
25.8%
Other Punctuation 10146
19.8%
Space Separator 4515
 
8.8%
Other Letter 3561
 
7.0%
Open Punctuation 610
 
1.2%
Connector Punctuation 500
 
1.0%
Close Punctuation 499
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
493
 
13.8%
407
 
11.4%
360
 
10.1%
278
 
7.8%
143
 
4.0%
113
 
3.2%
100
 
2.8%
100
 
2.8%
100
 
2.8%
97
 
2.7%
Other values (41) 1370
38.5%
Lowercase Letter
ValueCountFrequency (%)
t 2050
15.5%
i 2001
15.2%
d 1551
11.7%
l 1000
7.6%
n 1000
7.6%
o 1000
7.6%
u 1000
7.6%
e 1000
7.6%
a 600
 
4.5%
m 500
 
3.8%
Other values (3) 1500
11.4%
Decimal Number
ValueCountFrequency (%)
7 2383
13.1%
3 2284
12.6%
9 2025
11.1%
1 1875
10.3%
4 1874
10.3%
8 1707
9.4%
2 1699
9.4%
0 1689
9.3%
6 1319
7.3%
5 1312
7.2%
Other Punctuation
ValueCountFrequency (%)
" 5110
50.4%
: 2050
20.2%
, 1986
 
19.6%
. 1000
 
9.9%
Open Punctuation
ValueCountFrequency (%)
{ 560
91.8%
[ 50
 
8.2%
Space Separator
ValueCountFrequency (%)
4515
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 500
100.0%
Close Punctuation
ValueCountFrequency (%)
} 499
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34437
67.3%
Latin 13202
 
25.8%
Hangul 3561
 
7.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
493
 
13.8%
407
 
11.4%
360
 
10.1%
278
 
7.8%
143
 
4.0%
113
 
3.2%
100
 
2.8%
100
 
2.8%
100
 
2.8%
97
 
2.7%
Other values (41) 1370
38.5%
Common
ValueCountFrequency (%)
" 5110
14.8%
4515
13.1%
7 2383
 
6.9%
3 2284
 
6.6%
: 2050
 
6.0%
9 2025
 
5.9%
, 1986
 
5.8%
1 1875
 
5.4%
4 1874
 
5.4%
8 1707
 
5.0%
Other values (9) 8628
25.1%
Latin
ValueCountFrequency (%)
t 2050
15.5%
i 2001
15.2%
d 1551
11.7%
l 1000
7.6%
n 1000
7.6%
o 1000
7.6%
u 1000
7.6%
e 1000
7.6%
a 600
 
4.5%
m 500
 
3.8%
Other values (3) 1500
11.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47639
93.0%
Hangul 3561
 
7.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 5110
 
10.7%
4515
 
9.5%
7 2383
 
5.0%
3 2284
 
4.8%
t 2050
 
4.3%
: 2050
 
4.3%
9 2025
 
4.3%
i 2001
 
4.2%
, 1986
 
4.2%
1 1875
 
3.9%
Other values (22) 21360
44.8%
Hangul
ValueCountFrequency (%)
493
 
13.8%
407
 
11.4%
360
 
10.1%
278
 
7.8%
143
 
4.0%
113
 
3.2%
100
 
2.8%
100
 
2.8%
100
 
2.8%
97
 
2.7%
Other values (41) 1370
38.5%

hsptl_cnt_300mblw
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
0
50 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 50
100.0%

Length

2023-12-10T22:24:42.078243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:24:42.321069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 50
100.0%
Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
0
36 
1
14 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 36
72.0%
1 14
 
28.0%

Length

2023-12-10T22:24:42.484937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:24:42.791498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 36
72.0%
1 14
 
28.0%
Distinct5
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
3
23 
4
12 
2
5
6
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6
2nd row6
3rd row3
4th row3
5th row4

Common Values

ValueCountFrequency (%)
3 23
46.0%
4 12
24.0%
2 9
 
18.0%
5 4
 
8.0%
6 2
 
4.0%

Length

2023-12-10T22:24:43.105782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:24:43.398086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 23
46.0%
4 12
24.0%
2 9
 
18.0%
5 4
 
8.0%
6 2
 
4.0%

hsptl_cnt_5kmovr_10kmblw
Real number (ℝ)

Distinct10
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.92
Minimum6
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:43.581727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile6
Q16.25
median7.5
Q310.75
95-th percentile15
Maximum15
Range9
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation3.1933605
Coefficient of variation (CV)0.35800005
Kurtosis-0.59297961
Mean8.92
Median Absolute Deviation (MAD)1.5
Skewness0.94523994
Sum446
Variance10.197551
MonotonicityNot monotonic
2023-12-10T22:24:43.801388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
6 13
26.0%
7 12
24.0%
8 7
14.0%
15 6
12.0%
10 4
 
8.0%
14 3
 
6.0%
11 2
 
4.0%
13 1
 
2.0%
9 1
 
2.0%
12 1
 
2.0%
ValueCountFrequency (%)
6 13
26.0%
7 12
24.0%
8 7
14.0%
9 1
 
2.0%
10 4
 
8.0%
11 2
 
4.0%
12 1
 
2.0%
13 1
 
2.0%
14 3
 
6.0%
15 6
12.0%
ValueCountFrequency (%)
15 6
12.0%
14 3
 
6.0%
13 1
 
2.0%
12 1
 
2.0%
11 2
 
4.0%
10 4
 
8.0%
9 1
 
2.0%
8 7
14.0%
7 12
24.0%
6 13
26.0%

hsptl_idx
Categorical

Distinct4
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
8
19 
7
18 
6
10 
9

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9
2nd row9
3rd row7
4th row7
5th row8

Common Values

ValueCountFrequency (%)
8 19
38.0%
7 18
36.0%
6 10
20.0%
9 3
 
6.0%

Length

2023-12-10T22:24:44.022007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:24:44.182102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8 19
38.0%
7 18
36.0%
6 10
20.0%
9 3
 
6.0%

hsptl_info_10kmblw
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-10T22:24:44.493607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length1024
Mean length1000.62
Min length925

Characters and Unicode

Total characters50031
Distinct characters102
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

Unique50 ?
Unique (%)100.0%

Sample

1st row{"data": [{"dist": 9052, "poi_nm": "서울대학교병원", "latitude": 37.57971509999999, "longitude": 126.99901679999999}, {"dist": 3832, "poi_nm": "건국대학교병원", "latitude": 37.54037640000001, "longitude": 127.07182760000002}, {"dist": 9702, "poi_nm": "경희대학교병원", "latitude": 37.59411949999999, "longitude": 127.05185200000001}, {"dist": 6968, "poi_nm": "삼성서울병원", "latitude": 37.4882978, "longitude": 127.08515079999998}, {"dist": 4511, "poi_nm": "연세대학교의과대학 강남세브란스병원", "latitude": 37.4929296, "longitude": 127.04626830000001}, {"dist": 7222, "poi_nm": "재단법인아산사회복지재단 서울아산병원", "latitude": 37.526576199999994, "longitude": 127.10793499999998}, {"dist": 9471, "poi_nm": "중앙대학교병원", "latitude": 37.50674809999999, "longitude": 126.9607839}, {"dist": 8844, "poi_nm": "학교법인 고려중앙학원 고려대학교의과대학부속병원(안암병원)", "latitude": 37.5870165, "longitude": 127.0263537}, {"dist": 5377, "poi_nm": "학교법인가톨릭학원가톨릭대학교서울성모병원", "latitude": 37.500944400000016, "longitude": 127.00511540000001}, {"dist": 4811, "poi_nm": "한양대학교병원", "latitude": 37.5596569, "longitude": 127.0
2nd row{"data": [{"dist": 9102, "poi_nm": "서울대학교병원", "latitude": 37.57971509999999, "longitude": 126.99901679999999}, {"dist": 3774, "poi_nm": "건국대학교병원", "latitude": 37.54037640000001, "longitude": 127.07182760000002}, {"dist": 9701, "poi_nm": "경희대학교병원", "latitude": 37.59411949999999, "longitude": 127.05185200000001}, {"dist": 6932, "poi_nm": "삼성서울병원", "latitude": 37.4882978, "longitude": 127.08515079999998}, {"dist": 4532, "poi_nm": "연세대학교의과대학 강남세브란스병원", "latitude": 37.4929296, "longitude": 127.04626830000001}, {"dist": 7146, "poi_nm": "재단법인아산사회복지재단 서울아산병원", "latitude": 37.526576199999994, "longitude": 127.10793499999998}, {"dist": 9565, "poi_nm": "중앙대학교병원", "latitude": 37.50674809999999, "longitude": 126.9607839}, {"dist": 8868, "poi_nm": "학교법인 고려중앙학원 고려대학교의과대학부속병원(안암병원)", "latitude": 37.5870165, "longitude": 127.0263537}, {"dist": 5465, "poi_nm": "학교법인가톨릭학원가톨릭대학교서울성모병원", "latitude": 37.500944400000016, "longitude": 127.00511540000001}, {"dist": 4817, "poi_nm": "한양대학교병원", "latitude": 37.5596569, "longitude": 127.0
3rd row{"data": [{"dist": 5585, "poi_nm": "건국대학교병원", "latitude": 37.54037640000001, "longitude": 127.07182760000002}, {"dist": 3073, "poi_nm": "삼성서울병원", "latitude": 37.4882978, "longitude": 127.08515079999998}, {"dist": 1876, "poi_nm": "연세대학교의과대학 강남세브란스병원", "latitude": 37.4929296, "longitude": 127.04626830000001}, {"dist": 6272, "poi_nm": "재단법인아산사회복지재단 서울아산병원", "latitude": 37.526576199999994, "longitude": 127.10793499999998}, {"dist": 6087, "poi_nm": "학교법인가톨릭학원가톨릭대학교서울성모병원", "latitude": 37.500944400000016, "longitude": 127.00511540000001}, {"dist": 8371, "poi_nm": "한양대학교병원", "latitude": 37.5596569, "longitude": 127.04413389999999}, {"dist": 6861, "poi_nm": "경찰병원", "latitude": 37.49638359999998, "longitude": 127.12350899999998}, {"dist": 9557, "poi_nm": "성심의료재단강동성심병원", "latitude": 37.53599709999999, "longitude": 127.135378}, {"dist": 7681, "poi_nm": "순천향대학교 부속 서울병원", "latitude": 37.53380400000001, "longitude": 127.00425790000001}, {"dist": 2859, "poi_nm": "차의과학대학교 강남차병원", "latitude": 37.5067941, "longitude": 127.0350
4th row{"data": [{"dist": 5784, "poi_nm": "건국대학교병원", "latitude": 37.54037640000001, "longitude": 127.07182760000002}, {"dist": 3103, "poi_nm": "삼성서울병원", "latitude": 37.4882978, "longitude": 127.08515079999998}, {"dist": 1907, "poi_nm": "연세대학교의과대학 강남세브란스병원", "latitude": 37.4929296, "longitude": 127.04626830000001}, {"dist": 6385, "poi_nm": "재단법인아산사회복지재단 서울아산병원", "latitude": 37.526576199999994, "longitude": 127.10793499999998}, {"dist": 6219, "poi_nm": "학교법인가톨릭학원가톨릭대학교서울성모병원", "latitude": 37.500944400000016, "longitude": 127.00511540000001}, {"dist": 8580, "poi_nm": "한양대학교병원", "latitude": 37.5596569, "longitude": 127.04413389999999}, {"dist": 6929, "poi_nm": "경찰병원", "latitude": 37.49638359999998, "longitude": 127.12350899999998}, {"dist": 9663, "poi_nm": "성심의료재단강동성심병원", "latitude": 37.53599709999999, "longitude": 127.135378}, {"dist": 7899, "poi_nm": "순천향대학교 부속 서울병원", "latitude": 37.53380400000001, "longitude": 127.00425790000001}, {"dist": 3040, "poi_nm": "차의과학대학교 강남차병원", "latitude": 37.5067941, "longitude": 127.0350
5th row{"data": [{"dist": 8338, "poi_nm": "서울대학교병원", "latitude": 37.57971509999999, "longitude": 126.99901679999999}, {"dist": 8805, "poi_nm": "강북삼성병원", "latitude": 37.5684083, "longitude": 126.96774999999997}, {"dist": 5916, "poi_nm": "건국대학교병원", "latitude": 37.54037640000001, "longitude": 127.07182760000002}, {"dist": 8469, "poi_nm": "삼성서울병원", "latitude": 37.4882978, "longitude": 127.08515079999998}, {"dist": 4974, "poi_nm": "연세대학교의과대학 강남세브란스병원", "latitude": 37.4929296, "longitude": 127.04626830000001}, {"dist": 9446, "poi_nm": "재단법인아산사회복지재단 서울아산병원", "latitude": 37.526576199999994, "longitude": 127.10793499999998}, {"dist": 7290, "poi_nm": "중앙대학교병원", "latitude": 37.50674809999999, "longitude": 126.9607839}, {"dist": 8933, "poi_nm": "학교법인 고려중앙학원 고려대학교의과대학부속병원(안암병원)", "latitude": 37.5870165, "longitude": 127.0263537}, {"dist": 3698, "poi_nm": "학교법인가톨릭학원가톨릭대학교서울성모병원", "latitude": 37.500944400000016, "longitude": 127.00511540000001}, {"dist": 5594, "poi_nm": "한양대학교병원", "latitude": 37.5596569, "longitude": 127.044133899
ValueCountFrequency (%)
poi_nm 488
 
11.7%
dist 488
 
11.7%
latitude 487
 
11.7%
longitude 487
 
11.7%
data 50
 
1.2%
삼성서울병원 50
 
1.2%
127.10793499999998 50
 
1.2%
37.526576199999994 50
 
1.2%
서울아산병원 50
 
1.2%
재단법인아산사회복지재단 50
 
1.2%
Other values (561) 1924
46.1%
2023-12-10T22:24:45.157842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 4974
 
9.9%
4126
 
8.2%
0 3246
 
6.5%
9 3225
 
6.4%
t 1999
 
4.0%
: 1999
 
4.0%
i 1950
 
3.9%
, 1904
 
3.8%
7 1764
 
3.5%
d 1512
 
3.0%
Other values (92) 23332
46.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16130
32.2%
Lowercase Letter 12871
25.7%
Other Punctuation 9851
19.7%
Other Letter 5474
 
10.9%
Space Separator 4126
 
8.2%
Open Punctuation 599
 
1.2%
Close Punctuation 492
 
1.0%
Connector Punctuation 488
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
554
 
10.1%
502
 
9.2%
487
 
8.9%
352
 
6.4%
351
 
6.4%
199
 
3.6%
199
 
3.6%
126
 
2.3%
114
 
2.1%
112
 
2.0%
Other values (57) 2478
45.3%
Lowercase Letter
ValueCountFrequency (%)
t 1999
15.5%
i 1950
15.2%
d 1512
11.7%
o 975
7.6%
n 975
7.6%
e 974
7.6%
u 974
7.6%
l 974
7.6%
a 587
 
4.6%
m 488
 
3.8%
Other values (3) 1463
11.4%
Decimal Number
ValueCountFrequency (%)
0 3246
20.1%
9 3225
20.0%
7 1764
10.9%
1 1400
8.7%
3 1245
 
7.7%
2 1129
 
7.0%
5 1121
 
6.9%
4 1036
 
6.4%
8 1021
 
6.3%
6 943
 
5.8%
Other Punctuation
ValueCountFrequency (%)
" 4974
50.5%
: 1999
20.3%
, 1904
 
19.3%
. 974
 
9.9%
Open Punctuation
ValueCountFrequency (%)
{ 540
90.2%
[ 50
 
8.3%
( 9
 
1.5%
Close Punctuation
ValueCountFrequency (%)
} 470
95.5%
] 13
 
2.6%
) 9
 
1.8%
Space Separator
ValueCountFrequency (%)
4126
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 488
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 31686
63.3%
Latin 12871
25.7%
Hangul 5474
 
10.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
554
 
10.1%
502
 
9.2%
487
 
8.9%
352
 
6.4%
351
 
6.4%
199
 
3.6%
199
 
3.6%
126
 
2.3%
114
 
2.1%
112
 
2.0%
Other values (57) 2478
45.3%
Common
ValueCountFrequency (%)
" 4974
15.7%
4126
13.0%
0 3246
10.2%
9 3225
10.2%
: 1999
 
6.3%
, 1904
 
6.0%
7 1764
 
5.6%
1 1400
 
4.4%
3 1245
 
3.9%
2 1129
 
3.6%
Other values (12) 6674
21.1%
Latin
ValueCountFrequency (%)
t 1999
15.5%
i 1950
15.2%
d 1512
11.7%
o 975
7.6%
n 975
7.6%
e 974
7.6%
u 974
7.6%
l 974
7.6%
a 587
 
4.6%
m 488
 
3.8%
Other values (3) 1463
11.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44557
89.1%
Hangul 5474
 
10.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 4974
 
11.2%
4126
 
9.3%
0 3246
 
7.3%
9 3225
 
7.2%
t 1999
 
4.5%
: 1999
 
4.5%
i 1950
 
4.4%
, 1904
 
4.3%
7 1764
 
4.0%
d 1512
 
3.4%
Other values (25) 17858
40.1%
Hangul
ValueCountFrequency (%)
554
 
10.1%
502
 
9.2%
487
 
8.9%
352
 
6.4%
351
 
6.4%
199
 
3.6%
199
 
3.6%
126
 
2.3%
114
 
2.1%
112
 
2.0%
Other values (57) 2478
45.3%
Distinct5
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
0
18 
1
17 
2
10 
3
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st row2
2nd row2
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 18
36.0%
1 17
34.0%
2 10
20.0%
3 4
 
8.0%
4 1
 
2.0%

Length

2023-12-10T22:24:45.374369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:24:45.533205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 18
36.0%
1 17
34.0%
2 10
20.0%
3 4
 
8.0%
4 1
 
2.0%

gas_statn_cnt_500movr_1kmblw
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.36
Minimum0
Maximum7
Zeros3
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:45.680821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.45
Q12
median4
Q34
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.8043032
Coefficient of variation (CV)0.53699501
Kurtosis-0.60865063
Mean3.36
Median Absolute Deviation (MAD)1
Skewness-0.045653144
Sum168
Variance3.2555102
MonotonicityNot monotonic
2023-12-10T22:24:45.859530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
4 15
30.0%
2 8
16.0%
1 6
 
12.0%
3 6
 
12.0%
5 6
 
12.0%
6 4
 
8.0%
0 3
 
6.0%
7 2
 
4.0%
ValueCountFrequency (%)
0 3
 
6.0%
1 6
 
12.0%
2 8
16.0%
3 6
 
12.0%
4 15
30.0%
5 6
 
12.0%
6 4
 
8.0%
7 2
 
4.0%
ValueCountFrequency (%)
7 2
 
4.0%
6 4
 
8.0%
5 6
 
12.0%
4 15
30.0%
3 6
 
12.0%
2 8
16.0%
1 6
 
12.0%
0 3
 
6.0%
Distinct22
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.46
Minimum40
Maximum76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:46.041416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile54.9
Q163
median67
Q370
95-th percentile74
Maximum76
Range36
Interquartile range (IQR)7

Descriptive statistics

Standard deviation7.2399402
Coefficient of variation (CV)0.11060098
Kurtosis2.066331
Mean65.46
Median Absolute Deviation (MAD)4
Skewness-1.2387985
Sum3273
Variance52.416735
MonotonicityNot monotonic
2023-12-10T22:24:46.255937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
70 6
12.0%
67 6
12.0%
56 5
 
10.0%
63 5
 
10.0%
73 3
 
6.0%
71 3
 
6.0%
68 2
 
4.0%
64 2
 
4.0%
74 2
 
4.0%
66 2
 
4.0%
Other values (12) 14
28.0%
ValueCountFrequency (%)
40 1
 
2.0%
48 1
 
2.0%
54 1
 
2.0%
56 5
10.0%
58 1
 
2.0%
59 1
 
2.0%
61 1
 
2.0%
62 1
 
2.0%
63 5
10.0%
64 2
 
4.0%
ValueCountFrequency (%)
76 1
 
2.0%
75 1
 
2.0%
74 2
 
4.0%
73 3
6.0%
72 2
 
4.0%
71 3
6.0%
70 6
12.0%
69 2
 
4.0%
68 2
 
4.0%
67 6
12.0%
Distinct38
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean136.82
Minimum91
Maximum185
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:46.454714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum91
5-th percentile92.45
Q1113.25
median130
Q3163
95-th percentile179
Maximum185
Range94
Interquartile range (IQR)49.75

Descriptive statistics

Standard deviation29.207694
Coefficient of variation (CV)0.21347533
Kurtosis-1.3357558
Mean136.82
Median Absolute Deviation (MAD)21.5
Skewness0.15302818
Sum6841
Variance853.08939
MonotonicityNot monotonic
2023-12-10T22:24:46.709814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
116 2
 
4.0%
130 2
 
4.0%
119 2
 
4.0%
112 2
 
4.0%
111 2
 
4.0%
120 2
 
4.0%
179 2
 
4.0%
92 2
 
4.0%
176 2
 
4.0%
154 2
 
4.0%
Other values (28) 30
60.0%
ValueCountFrequency (%)
91 1
2.0%
92 2
4.0%
93 1
2.0%
95 1
2.0%
104 1
2.0%
108 1
2.0%
110 1
2.0%
111 2
4.0%
112 2
4.0%
113 1
2.0%
ValueCountFrequency (%)
185 1
2.0%
184 1
2.0%
179 2
4.0%
177 1
2.0%
176 2
4.0%
175 1
2.0%
174 1
2.0%
173 1
2.0%
171 1
2.0%
170 1
2.0%

gas_statn_idx
Categorical

Distinct5
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
9
26 
8
18 
10
6
 
2
7
 
1

Length

Max length2
Median length1
Mean length1.06
Min length1

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st row9
2nd row9
3rd row9
4th row9
5th row8

Common Values

ValueCountFrequency (%)
9 26
52.0%
8 18
36.0%
10 3
 
6.0%
6 2
 
4.0%
7 1
 
2.0%

Length

2023-12-10T22:24:47.103609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:24:47.343919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9 26
52.0%
8 18
36.0%
10 3
 
6.0%
6 2
 
4.0%
7 1
 
2.0%
Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-10T22:24:47.893843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length1024
Mean length1024
Min length1024

Characters and Unicode

Total characters51200
Distinct characters131
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)100.0%

Sample

1st row{"data": [{"dist": 9159, "poi_nm": "GS칼텍스대원주유소", "latitude": 37.583863916283, "longitude": 127.08012610941306}, {"dist": 9608, "poi_nm": "현대오일뱅크대창주유소", "latitude": 37.58721644633095, "longitude": 127.08023002421784}, {"dist": 9796, "poi_nm": "S-OIL동천주유소", "latitude": 37.58883136724417, "longitude": 127.08026550111099}, {"dist": 7169, "poi_nm": "SK에너지삼영주유소", "latitude": 37.57230188625075, "longitude": 127.06886338840624}, {"dist": 5663, "poi_nm": "SK네트웍스군자동주유소", "latitude": 37.56056472689493, "longitude": 127.06835208969184}, {"dist": 5801, "poi_nm": "SK네트웍스스피드주유소", "latitude": 37.5611856440228, "longitude": 127.06943438752158}, {"dist": 5970, "poi_nm": "현대오일뱅크LPG중곡충전소", "latitude": 37.560246771406455, "longitude": 127.07388577003711}, {"dist": 7346, "poi_nm": "S-OIL대원주유소", "latitude": 37.56455799635434, "longitude": 127.087009148718}, {"dist": 6306, "poi_nm": "평안알뜰주유소", "latitude": 37.553793709202104, "longitude": 127.08716486178032}, {"dist": 3475, "poi_nm": "SK에너지청담대교주유소", "latitude": 37.538677456135325, "l
2nd row{"data": [{"dist": 9133, "poi_nm": "GS칼텍스대원주유소", "latitude": 37.583863916283, "longitude": 127.08012610941306}, {"dist": 9583, "poi_nm": "현대오일뱅크대창주유소", "latitude": 37.58721644633095, "longitude": 127.08023002421784}, {"dist": 9771, "poi_nm": "S-OIL동천주유소", "latitude": 37.58883136724417, "longitude": 127.08026550111099}, {"dist": 7146, "poi_nm": "SK에너지삼영주유소", "latitude": 37.57230188625075, "longitude": 127.06886338840624}, {"dist": 5632, "poi_nm": "SK네트웍스군자동주유소", "latitude": 37.56056472689493, "longitude": 127.06835208969184}, {"dist": 5770, "poi_nm": "SK네트웍스스피드주유소", "latitude": 37.5611856440228, "longitude": 127.06943438752158}, {"dist": 5933, "poi_nm": "현대오일뱅크LPG중곡충전소", "latitude": 37.560246771406455, "longitude": 127.07388577003711}, {"dist": 7302, "poi_nm": "S-OIL대원주유소", "latitude": 37.56455799635434, "longitude": 127.087009148718}, {"dist": 6253, "poi_nm": "평안알뜰주유소", "latitude": 37.553793709202104, "longitude": 127.08716486178032}, {"dist": 3416, "poi_nm": "SK에너지청담대교주유소", "latitude": 37.538677456135325, "l
3rd row{"data": [{"dist": 9960, "poi_nm": "SK에너지삼영주유소", "latitude": 37.57230188625075, "longitude": 127.06886338840624}, {"dist": 8311, "poi_nm": "SK네트웍스군자동주유소", "latitude": 37.56056472689493, "longitude": 127.06835208969184}, {"dist": 8412, "poi_nm": "SK네트웍스스피드주유소", "latitude": 37.5611856440228, "longitude": 127.06943438752158}, {"dist": 8358, "poi_nm": "현대오일뱅크LPG중곡충전소", "latitude": 37.560246771406455, "longitude": 127.07388577003711}, {"dist": 9293, "poi_nm": "S-OIL대원주유소", "latitude": 37.56455799635434, "longitude": 127.087009148718}, {"dist": 7873, "poi_nm": "평안알뜰주유소", "latitude": 37.553793709202104, "longitude": 127.08716486178032}, {"dist": 5278, "poi_nm": "SK에너지청담대교주유소", "latitude": 37.538677456135325, "longitude": 127.06971475143747}, {"dist": 6469, "poi_nm": "SK네트웍스대명셀프주유소", "latitude": 37.545104165003366, "longitude": 127.08049371117657}, {"dist": 7494, "poi_nm": "아차산주유소", "latitude": 37.54951032120209, "longitude": 127.09101604777521}, {"dist": 4984, "poi_nm": "SK네트웍스장호셀프주유소", "latitude": 37.53134609146488
4th row{"data": [{"dist": 8516, "poi_nm": "SK네트웍스군자동주유소", "latitude": 37.56056472689493, "longitude": 127.06835208969184}, {"dist": 8616, "poi_nm": "SK네트웍스스피드주유소", "latitude": 37.5611856440228, "longitude": 127.06943438752158}, {"dist": 8560, "poi_nm": "현대오일뱅크LPG중곡충전소", "latitude": 37.560246771406455, "longitude": 127.07388577003711}, {"dist": 9485, "poi_nm": "S-OIL대원주유소", "latitude": 37.56455799635434, "longitude": 127.087009148718}, {"dist": 8060, "poi_nm": "평안알뜰주유소", "latitude": 37.553793709202104, "longitude": 127.08716486178032}, {"dist": 5480, "poi_nm": "SK에너지청담대교주유소", "latitude": 37.538677456135325, "longitude": 127.06971475143747}, {"dist": 6660, "poi_nm": "SK네트웍스대명셀프주유소", "latitude": 37.545104165003366, "longitude": 127.08049371117657}, {"dist": 7673, "poi_nm": "아차산주유소", "latitude": 37.54951032120209, "longitude": 127.09101604777521}, {"dist": 5150, "poi_nm": "SK네트웍스장호셀프주유소", "latitude": 37.53134609146488, "longitude": 127.08580527106436}, {"dist": 8039, "poi_nm": "SK네트웍스한미주유소", "latitude": 37.5291567237555
5th row{"data": [{"dist": 8518, "poi_nm": "SK에너지삼영주유소", "latitude": 37.57230188625075, "longitude": 127.06886338840624}, {"dist": 7215, "poi_nm": "SK네트웍스군자동주유소", "latitude": 37.56056472689493, "longitude": 127.06835208969184}, {"dist": 7366, "poi_nm": "SK네트웍스스피드주유소", "latitude": 37.5611856440228, "longitude": 127.06943438752158}, {"dist": 7643, "poi_nm": "현대오일뱅크LPG중곡충전소", "latitude": 37.560246771406455, "longitude": 127.07388577003711}, {"dist": 9140, "poi_nm": "S-OIL대원주유소", "latitude": 37.56455799635434, "longitude": 127.087009148718}, {"dist": 8282, "poi_nm": "평안알뜰주유소", "latitude": 37.553793709202104, "longitude": 127.08716486178032}, {"dist": 5577, "poi_nm": "SK에너지청담대교주유소", "latitude": 37.538677456135325, "longitude": 127.06971475143747}, {"dist": 7038, "poi_nm": "SK네트웍스대명셀프주유소", "latitude": 37.545104165003366, "longitude": 127.08049371117657}, {"dist": 8372, "poi_nm": "아차산주유소", "latitude": 37.54951032120209, "longitude": 127.09101604777521}, {"dist": 7038, "poi_nm": "SK네트웍스장호셀프주유소", "latitude": 37.53134609146488
ValueCountFrequency (%)
dist 500
 
12.6%
poi_nm 500
 
12.6%
latitude 500
 
12.6%
longitude 452
 
11.4%
data 50
 
1.3%
sk에너지청담대교주유소 46
 
1.2%
37.538677456135325 46
 
1.2%
127.06971475143747 42
 
1.1%
37.53134609146488 41
 
1.0%
sk네트웍스장호셀프주유소 41
 
1.0%
Other values (607) 1744
44.0%
2023-12-10T22:24:48.698587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 5012
 
9.8%
3913
 
7.6%
7 2641
 
5.2%
1 2035
 
4.0%
t 2005
 
3.9%
: 2000
 
3.9%
i 1956
 
3.8%
3 1920
 
3.8%
, 1913
 
3.7%
5 1849
 
3.6%
Other values (121) 25956
50.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17641
34.5%
Lowercase Letter 12798
25.0%
Other Punctuation 9875
19.3%
Other Letter 4461
 
8.7%
Space Separator 3913
 
7.6%
Uppercase Letter 933
 
1.8%
Open Punctuation 601
 
1.2%
Connector Punctuation 500
 
1.0%
Close Punctuation 451
 
0.9%
Dash Punctuation 27
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
499
 
11.2%
454
 
10.2%
453
 
10.2%
258
 
5.8%
194
 
4.3%
194
 
4.3%
194
 
4.3%
164
 
3.7%
130
 
2.9%
130
 
2.9%
Other values (79) 1791
40.1%
Lowercase Letter
ValueCountFrequency (%)
t 2005
15.7%
i 1956
15.3%
d 1503
11.7%
l 960
7.5%
o 957
7.5%
n 956
7.5%
u 953
7.4%
e 952
7.4%
a 600
 
4.7%
s 500
 
3.9%
Other values (3) 1456
11.4%
Decimal Number
ValueCountFrequency (%)
7 2641
15.0%
1 2035
11.5%
3 1920
10.9%
5 1849
10.5%
0 1709
9.7%
4 1639
9.3%
6 1624
9.2%
2 1582
9.0%
8 1364
7.7%
9 1278
7.2%
Uppercase Letter
ValueCountFrequency (%)
S 384
41.2%
K 331
35.5%
L 64
 
6.9%
G 63
 
6.8%
P 37
 
4.0%
O 27
 
2.9%
I 27
 
2.9%
Other Punctuation
ValueCountFrequency (%)
" 5012
50.8%
: 2000
 
20.3%
, 1913
 
19.4%
. 950
 
9.6%
Open Punctuation
ValueCountFrequency (%)
{ 550
91.5%
[ 50
 
8.3%
( 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
} 450
99.8%
) 1
 
0.2%
Space Separator
ValueCountFrequency (%)
3913
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 500
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33008
64.5%
Latin 13731
26.8%
Hangul 4461
 
8.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
499
 
11.2%
454
 
10.2%
453
 
10.2%
258
 
5.8%
194
 
4.3%
194
 
4.3%
194
 
4.3%
164
 
3.7%
130
 
2.9%
130
 
2.9%
Other values (79) 1791
40.1%
Common
ValueCountFrequency (%)
" 5012
15.2%
3913
11.9%
7 2641
 
8.0%
1 2035
 
6.2%
: 2000
 
6.1%
3 1920
 
5.8%
, 1913
 
5.8%
5 1849
 
5.6%
0 1709
 
5.2%
4 1639
 
5.0%
Other values (12) 8377
25.4%
Latin
ValueCountFrequency (%)
t 2005
14.6%
i 1956
14.2%
d 1503
10.9%
l 960
7.0%
o 957
7.0%
n 956
7.0%
u 953
 
6.9%
e 952
 
6.9%
a 600
 
4.4%
s 500
 
3.6%
Other values (10) 2389
17.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46739
91.3%
Hangul 4461
 
8.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 5012
 
10.7%
3913
 
8.4%
7 2641
 
5.7%
1 2035
 
4.4%
t 2005
 
4.3%
: 2000
 
4.3%
i 1956
 
4.2%
3 1920
 
4.1%
, 1913
 
4.1%
5 1849
 
4.0%
Other values (32) 21495
46.0%
Hangul
ValueCountFrequency (%)
499
 
11.2%
454
 
10.2%
453
 
10.2%
258
 
5.8%
194
 
4.3%
194
 
4.3%
194
 
4.3%
164
 
3.7%
130
 
2.9%
130
 
2.9%
Other values (79) 1791
40.1%

lo
Real number (ℝ)

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.04821
Minimum127.02302
Maximum127.11274
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:48.949662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.02302
5-th percentile127.02375
Q1127.03918
median127.04784
Q3127.05672
95-th percentile127.06904
Maximum127.11274
Range0.089720753
Interquartile range (IQR)0.017534048

Descriptive statistics

Standard deviation0.015936963
Coefficient of variation (CV)0.00012544028
Kurtosis4.2628966
Mean127.04821
Median Absolute Deviation (MAD)0.009048081
Skewness1.1632126
Sum6352.4103
Variance0.00025398678
MonotonicityNot monotonic
2023-12-10T22:24:49.352710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.042935771183 1
 
2.0%
127.051003157318 1
 
2.0%
127.060483984218 1
 
2.0%
127.059365680062 1
 
2.0%
127.057218089165 1
 
2.0%
127.053273437437 1
 
2.0%
127.052894424892 1
 
2.0%
127.05267317141 1
 
2.0%
127.051364654689 1
 
2.0%
127.054170896598 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
127.023019210601 1
2.0%
127.02306594964 1
2.0%
127.023664755177 1
2.0%
127.023847245973 1
2.0%
127.02405909363 1
2.0%
127.029408985511 1
2.0%
127.03095293507 1
2.0%
127.031387524964 1
2.0%
127.032874451293 1
2.0%
127.033552843524 1
2.0%
ValueCountFrequency (%)
127.112739963673 1
2.0%
127.075100500297 1
2.0%
127.07087436852 1
2.0%
127.066787012877 1
2.0%
127.065532964008 1
2.0%
127.063383503349 1
2.0%
127.061203644383 1
2.0%
127.060970175676 1
2.0%
127.060483984218 1
2.0%
127.059418422668 1
2.0%

la
Real number (ℝ)

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.49966
Minimum37.473165
Maximum37.525252
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:24:49.708258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.473165
5-th percentile37.478359
Q137.486484
median37.498753
Q337.51432
95-th percentile37.523752
Maximum37.525252
Range0.052087298
Interquartile range (IQR)0.027835989

Descriptive statistics

Standard deviation0.015772292
Coefficient of variation (CV)0.00042059827
Kurtosis-1.1559296
Mean37.49966
Median Absolute Deviation (MAD)0.01300386
Skewness0.28214349
Sum1874.983
Variance0.00024876519
MonotonicityNot monotonic
2023-12-10T22:24:50.269947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5252249820547 1
 
2.0%
37.4870848920094 1
 
2.0%
37.514721392611904 1
 
2.0%
37.518348072455105 1
 
2.0%
37.476155698557506 1
 
2.0%
37.4810519004336 1
 
2.0%
37.481333664273905 1
 
2.0%
37.481682128555 1
 
2.0%
37.4824657036676 1
 
2.0%
37.4846486329701 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
37.4731645931654 1
2.0%
37.4746082742704 1
2.0%
37.476155698557506 1
2.0%
37.4810519004336 1
2.0%
37.481333664273905 1
2.0%
37.481682128555 1
2.0%
37.4824657036676 1
2.0%
37.4846486329701 1
2.0%
37.4852013763256 1
2.0%
37.48527638223089 1
2.0%
ValueCountFrequency (%)
37.5252518912234 1
2.0%
37.5252249820547 1
2.0%
37.523802974611 1
2.0%
37.52369044873689 1
2.0%
37.52368419807831 1
2.0%
37.5235548472912 1
2.0%
37.52336206792089 1
2.0%
37.523021366117 1
2.0%
37.521092184631506 1
2.0%
37.5196629002269 1
2.0%

Sample

uidapt_cdapt_nmrdnmadrlegaldong_cdstrd_yearsubway_cnt_250mblwsubway_cnt_250movr_500mblwsubway_cnt_500movr_1kmblwsubway_idxsubway_info_1kmblwelctyvh_cnt_250mblwelctyvh_cnt_250movr_500mblwelctyvh_cnt_500movr_1kmblwelctyvh_idxelctyvh_info_1kmblwcafe_cnt_250mblwcafe_cnt_250movr_500mblwcafe_cnt_500movr_1kmblwcafe_idxcafe_info_1kmblwspml_cnt_1kmblwspml_cnt_1kmovr_5kmblwspml_cnt_5kmovr_10kmblwspml_idxspml_info_10kmblwhsptl_cnt_300mblwhsptl_cnt_300movr_1kmblwhsptl_cnt_1kmovr_5kmblwhsptl_cnt_5kmovr_10kmblwhsptl_idxhsptl_info_10kmblwgas_statn_cnt_500mblwgas_statn_cnt_500movr_1kmblwgas_statn_cnt_1kmovr_5kmblwgas_statn_cnt_5kmovr_10kmblwgas_statn_idxgas_statn_info_10kmblwlola
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