Overview

Dataset statistics

Number of variables23
Number of observations50
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.9 KiB
Average record size in memory203.6 B

Variable types

Numeric13
Text6
Categorical4

Dataset

DescriptionSample
Author아파트엔
URLhttps://bigdata-geo.kr/user/dataset/view.do?data_sn=46

Alerts

strd_year has constant value ""Constant
uid has unique valuesUnique
apt_cd has unique valuesUnique
rdnmadr has unique valuesUnique
cctv_info_1kmblw has unique valuesUnique
fire_statn_info_7kmblw has unique valuesUnique
police_statn_info_5kmblw has unique valuesUnique
lo has unique valuesUnique
la has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:22:39.626419
Analysis finished2023-12-10 13:22:40.936289
Duration1.31 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%
Mean7835.02
Minimum7796
Maximum8262
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:22:41.121089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7796
5-th percentile7798.45
Q17808.5
median7823.5
Q37835.75
95-th percentile7845.55
Maximum8262
Range466
Interquartile range (IQR)27.25

Descriptive statistics

Standard deviation71.321774
Coefficient of variation (CV)0.0091029473
Kurtosis28.467299
Mean7835.02
Median Absolute Deviation (MAD)13.5
Skewness5.1350239
Sum391751
Variance5086.7955
MonotonicityNot monotonic
2023-12-10T22:22:41.523547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8262 1
 
2.0%
7841 1
 
2.0%
7825 1
 
2.0%
8053 1
 
2.0%
7826 1
 
2.0%
7827 1
 
2.0%
7828 1
 
2.0%
7829 1
 
2.0%
7830 1
 
2.0%
7831 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 (%)
8262 1
2.0%
8053 1
2.0%
7846 1
2.0%
7845 1
2.0%
7844 1
2.0%
7843 1
2.0%
7842 1
2.0%
7841 1
2.0%
7840 1
2.0%
7839 1
2.0%

apt_cd
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-10T22:22:41.856840image/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 rowAPT1168041664910045000001
2nd rowAPT1168010500100002000001
3rd rowAPT1168010500100646000001
4th rowAPT1168010800100168000001
5th rowAPT1168011300100056000001
ValueCountFrequency (%)
apt1168041664910045000001 1
 
2.0%
apt1168030050860322000001 1
 
2.0%
apt1168031210220213000001 1
 
2.0%
apt1168030050860110000001 1
 
2.0%
apt1168030050860117000001 1
 
2.0%
apt1168041661840016000001 1
 
2.0%
apt1168030050860118000001 1
 
2.0%
apt1168030050860122000001 1
 
2.0%
apt1168030050860123000001 1
 
2.0%
apt1168030050860203000001 1
 
2.0%
Other values (40) 40
80.0%
2023-12-10T22:22:42.525738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 512
41.0%
1 210
16.8%
6 94
 
7.5%
2 87
 
7.0%
8 80
 
6.4%
A 50
 
4.0%
P 50
 
4.0%
T 50
 
4.0%
3 48
 
3.8%
5 41
 
3.3%
Other values (3) 28
 
2.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 512
46.5%
1 210
19.1%
6 94
 
8.5%
2 87
 
7.9%
8 80
 
7.3%
3 48
 
4.4%
5 41
 
3.7%
4 17
 
1.5%
7 8
 
0.7%
9 3
 
0.3%
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 (%)
0 512
46.5%
1 210
19.1%
6 94
 
8.5%
2 87
 
7.9%
8 80
 
7.3%
3 48
 
4.4%
5 41
 
3.7%
4 17
 
1.5%
7 8
 
0.7%
9 3
 
0.3%
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 (%)
0 512
41.0%
1 210
16.8%
6 94
 
7.5%
2 87
 
7.0%
8 80
 
6.4%
A 50
 
4.0%
P 50
 
4.0%
T 50
 
4.0%
3 48
 
3.8%
5 41
 
3.3%
Other values (3) 28
 
2.2%

apt_nm
Text

Distinct49
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-10T22:22:43.013372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length14.5
Mean length6.88
Min length2

Characters and Unicode

Total characters344
Distinct characters125
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 row풍림아이원2차
2nd row브르넨삼성
3rd row위레벤646
4th rowN168
5th row세곡2지구 도시형생활주택(유현리엔아파트)
ValueCountFrequency (%)
대우디오빌 2
 
3.6%
아이파크 2
 
3.6%
개포현대200동 1
 
1.8%
개포경남 1
 
1.8%
우성4 1
 
1.8%
강남서해더블루 1
 
1.8%
우성캐릭터199 1
 
1.8%
우성캐릭터빌 1
 
1.8%
한신(개포 1
 
1.8%
매봉삼성 1
 
1.8%
Other values (44) 44
78.6%
2023-12-10T22:22:43.850476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
 
3.5%
1 10
 
2.9%
대 9
 
2.6%
현 9
 
2.6%
0 9
 
2.6%
( 8
 
2.3%
) 8
 
2.3%
이 8
 
2.3%
삼 8
 
2.3%
리 7
 
2.0%
Other values (115) 256
74.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 260
75.6%
Decimal Number 50
 
14.5%
Uppercase Letter 9
 
2.6%
Open Punctuation 8
 
2.3%
Close Punctuation 8
 
2.3%
Space Separator 6
 
1.7%
Dash Punctuation 2
 
0.6%
Math Symbol 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 9
 
3.5%
현 9
 
3.5%
이 8
 
3.1%
삼 8
 
3.1%
리 7
 
2.7%
아 7
 
2.7%
성 7
 
2.7%
빌 7
 
2.7%
포 6
 
2.3%
우 6
 
2.3%
Other values (93) 186
71.5%
Decimal Number
ValueCountFrequency (%)
2 12
24.0%
1 10
20.0%
0 9
18.0%
6 7
14.0%
4 4
 
8.0%
9 3
 
6.0%
8 2
 
4.0%
7 2
 
4.0%
3 1
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
S 2
22.2%
E 1
11.1%
K 1
11.1%
N 1
11.1%
T 1
11.1%
R 1
11.1%
W 1
11.1%
O 1
11.1%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 260
75.6%
Common 75
 
21.8%
Latin 9
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 9
 
3.5%
현 9
 
3.5%
이 8
 
3.1%
삼 8
 
3.1%
리 7
 
2.7%
아 7
 
2.7%
성 7
 
2.7%
빌 7
 
2.7%
포 6
 
2.3%
우 6
 
2.3%
Other values (93) 186
71.5%
Common
ValueCountFrequency (%)
2 12
16.0%
1 10
13.3%
0 9
12.0%
( 8
10.7%
) 8
10.7%
6 7
9.3%
6
8.0%
4 4
 
5.3%
9 3
 
4.0%
- 2
 
2.7%
Other values (4) 6
8.0%
Latin
ValueCountFrequency (%)
S 2
22.2%
E 1
11.1%
K 1
11.1%
N 1
11.1%
T 1
11.1%
R 1
11.1%
W 1
11.1%
O 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 260
75.6%
ASCII 84
 
24.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
14.3%
1 10
11.9%
0 9
10.7%
( 8
9.5%
) 8
9.5%
6 7
8.3%
6
 
7.1%
4 4
 
4.8%
9 3
 
3.6%
S 2
 
2.4%
Other values (12) 15
17.9%
Hangul
ValueCountFrequency (%)
대 9
 
3.5%
현 9
 
3.5%
이 8
 
3.1%
삼 8
 
3.1%
리 7
 
2.7%
아 7
 
2.7%
성 7
 
2.7%
빌 7
 
2.7%
포 6
 
2.3%
우 6
 
2.3%
Other values (93) 186
71.5%

rdnmadr
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-10T22:22:44.304827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length17.64
Min length15

Characters and Unicode

Total characters882
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 선릉로72길 45
2nd row서울특별시 강남구 영동대로122길 2
3rd row서울특별시 강남구 영동대로 646
4th row서울특별시 강남구 학동로 168
5th row서울특별시 강남구 밤고개로21길 56
ValueCountFrequency (%)
서울특별시 50
25.0%
강남구 50
25.0%
언주로 24
12.0%
영동대로 7
 
3.5%
강남대로 4
 
2.0%
논현로 4
 
2.0%
남부순환로 3
 
1.5%
도산대로 2
 
1.0%
16 1
 
0.5%
123 1
 
0.5%
Other values (54) 54
27.0%
2023-12-10T22:22:44.936832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
150
17.0%
남 57
 
6.5%
강 54
 
6.1%
서 50
 
5.7%
특 50
 
5.7%
별 50
 
5.7%
시 50
 
5.7%
구 50
 
5.7%
울 50
 
5.7%
로 50
 
5.7%
Other values (32) 271
30.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 576
65.3%
Decimal Number 155
 
17.6%
Space Separator 150
 
17.0%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 57
9.9%
강 54
9.4%
서 50
8.7%
특 50
8.7%
별 50
8.7%
시 50
8.7%
구 50
8.7%
울 50
8.7%
로 50
8.7%
주 24
 
4.2%
Other values (20) 91
15.8%
Decimal Number
ValueCountFrequency (%)
2 36
23.2%
1 23
14.8%
0 20
12.9%
3 17
11.0%
6 16
10.3%
5 15
9.7%
4 13
 
8.4%
7 9
 
5.8%
8 4
 
2.6%
9 2
 
1.3%
Space Separator
ValueCountFrequency (%)
150
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 576
65.3%
Common 306
34.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 57
9.9%
강 54
9.4%
서 50
8.7%
특 50
8.7%
별 50
8.7%
시 50
8.7%
구 50
8.7%
울 50
8.7%
로 50
8.7%
주 24
 
4.2%
Other values (20) 91
15.8%
Common
ValueCountFrequency (%)
150
49.0%
2 36
 
11.8%
1 23
 
7.5%
0 20
 
6.5%
3 17
 
5.6%
6 16
 
5.2%
5 15
 
4.9%
4 13
 
4.2%
7 9
 
2.9%
8 4
 
1.3%
Other values (2) 3
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 576
65.3%
ASCII 306
34.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
150
49.0%
2 36
 
11.8%
1 23
 
7.5%
0 20
 
6.5%
3 17
 
5.6%
6 16
 
5.2%
5 15
 
4.9%
4 13
 
4.2%
7 9
 
2.9%
8 4
 
1.3%
Other values (2) 3
 
1.0%
Hangul
ValueCountFrequency (%)
남 57
9.9%
강 54
9.4%
서 50
8.7%
특 50
8.7%
별 50
8.7%
시 50
8.7%
구 50
8.7%
울 50
8.7%
로 50
8.7%
주 24
 
4.2%
Other values (20) 91
15.8%

legaldong_cd
Real number (ℝ)

Distinct10
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1680108 × 109
Minimum1.1680101 × 109
Maximum1.1680118 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:22:45.160431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1680101 × 109
5-th percentile1.1680101 × 109
Q11.1680103 × 109
median1.1680106 × 109
Q31.1680118 × 109
95-th percentile1.1680118 × 109
Maximum1.1680118 × 109
Range1700
Interquartile range (IQR)1500

Descriptive statistics

Standard deviation689.93936
Coefficient of variation (CV)5.9069602 × 10-7
Kurtosis-1.4983316
Mean1.1680108 × 109
Median Absolute Deviation (MAD)500
Skewness0.461111
Sum5.8400542 × 1010
Variance476016.33
MonotonicityNot monotonic
2023-12-10T22:22:45.345150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1168011800 15
30.0%
1168010100 11
22.0%
1168010300 7
14.0%
1168010800 5
 
10.0%
1168010600 4
 
8.0%
1168010500 4
 
8.0%
1168011300 1
 
2.0%
1168010700 1
 
2.0%
1168010400 1
 
2.0%
1168011400 1
 
2.0%
ValueCountFrequency (%)
1168010100 11
22.0%
1168010300 7
14.0%
1168010400 1
 
2.0%
1168010500 4
 
8.0%
1168010600 4
 
8.0%
1168010700 1
 
2.0%
1168010800 5
 
10.0%
1168011300 1
 
2.0%
1168011400 1
 
2.0%
1168011800 15
30.0%
ValueCountFrequency (%)
1168011800 15
30.0%
1168011400 1
 
2.0%
1168011300 1
 
2.0%
1168010800 5
 
10.0%
1168010700 1
 
2.0%
1168010600 4
 
8.0%
1168010500 4
 
8.0%
1168010400 1
 
2.0%
1168010300 7
14.0%
1168010100 11
22.0%

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

2023-12-10T22:22:45.530759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:22:45.696167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 50
100.0%

cctv_cnt_250mblw
Real number (ℝ)

Distinct25
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.26
Minimum2
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:22:45.876042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q19.25
median13
Q319.75
95-th percentile26.55
Maximum33
Range31
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation7.2416313
Coefficient of variation (CV)0.50782828
Kurtosis-0.18037584
Mean14.26
Median Absolute Deviation (MAD)4.5
Skewness0.57130925
Sum713
Variance52.441224
MonotonicityNot monotonic
2023-12-10T22:22:46.081895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
10 5
 
10.0%
20 4
 
8.0%
13 4
 
8.0%
12 4
 
8.0%
5 4
 
8.0%
16 3
 
6.0%
9 3
 
6.0%
7 2
 
4.0%
17 2
 
4.0%
11 2
 
4.0%
Other values (15) 17
34.0%
ValueCountFrequency (%)
2 1
 
2.0%
3 1
 
2.0%
5 4
8.0%
6 1
 
2.0%
7 2
 
4.0%
8 1
 
2.0%
9 3
6.0%
10 5
10.0%
11 2
 
4.0%
12 4
8.0%
ValueCountFrequency (%)
33 1
 
2.0%
30 1
 
2.0%
27 1
 
2.0%
26 2
4.0%
24 1
 
2.0%
23 1
 
2.0%
22 1
 
2.0%
21 1
 
2.0%
20 4
8.0%
19 2
4.0%

cctv_cnt_250movr_500mblw
Real number (ℝ)

Distinct36
Distinct (%)72.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.42
Minimum10
Maximum73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:22:46.272170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile12.9
Q120.25
median31
Q343.75
95-th percentile64.3
Maximum73
Range63
Interquartile range (IQR)23.5

Descriptive statistics

Standard deviation16.228081
Coefficient of variation (CV)0.48557992
Kurtosis-0.11974925
Mean33.42
Median Absolute Deviation (MAD)11.5
Skewness0.70465821
Sum1671
Variance263.35061
MonotonicityNot monotonic
2023-12-10T22:22:46.554883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
31 3
 
6.0%
36 2
 
4.0%
44 2
 
4.0%
24 2
 
4.0%
39 2
 
4.0%
19 2
 
4.0%
20 2
 
4.0%
29 2
 
4.0%
21 2
 
4.0%
61 2
 
4.0%
Other values (26) 29
58.0%
ValueCountFrequency (%)
10 1
2.0%
11 1
2.0%
12 1
2.0%
14 2
4.0%
15 1
2.0%
16 1
2.0%
17 2
4.0%
19 2
4.0%
20 2
4.0%
21 2
4.0%
ValueCountFrequency (%)
73 1
2.0%
72 1
2.0%
67 1
2.0%
61 2
4.0%
53 1
2.0%
52 1
2.0%
50 1
2.0%
49 1
2.0%
47 1
2.0%
45 1
2.0%

cctv_cnt_500movr_1kmblw
Real number (ℝ)

Distinct41
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean121.76
Minimum22
Maximum229
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:22:46.956293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile70.7
Q190.25
median122
Q3149.25
95-th percentile179.3
Maximum229
Range207
Interquartile range (IQR)59

Descriptive statistics

Standard deviation38.876865
Coefficient of variation (CV)0.31929094
Kurtosis0.36298888
Mean121.76
Median Absolute Deviation (MAD)30.5
Skewness0.16384666
Sum6088
Variance1511.4106
MonotonicityNot monotonic
2023-12-10T22:22:47.327745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
137 3
 
6.0%
78 2
 
4.0%
116 2
 
4.0%
154 2
 
4.0%
90 2
 
4.0%
147 2
 
4.0%
129 2
 
4.0%
122 2
 
4.0%
120 1
 
2.0%
132 1
 
2.0%
Other values (31) 31
62.0%
ValueCountFrequency (%)
22 1
2.0%
64 1
2.0%
68 1
2.0%
74 1
2.0%
76 1
2.0%
78 2
4.0%
80 1
2.0%
83 1
2.0%
85 1
2.0%
89 1
2.0%
ValueCountFrequency (%)
229 1
2.0%
196 1
2.0%
182 1
2.0%
176 1
2.0%
168 1
2.0%
167 1
2.0%
165 1
2.0%
157 1
2.0%
154 2
4.0%
153 1
2.0%

cctv_idx
Real number (ℝ)

Distinct7
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.52
Minimum3
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:22:47.615798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile5
Q16.25
median8
Q39
95-th percentile9.55
Maximum10
Range7
Interquartile range (IQR)2.75

Descriptive statistics

Standard deviation1.4879105
Coefficient of variation (CV)0.19786043
Kurtosis0.35628162
Mean7.52
Median Absolute Deviation (MAD)1
Skewness-0.58249711
Sum376
Variance2.2138776
MonotonicityNot monotonic
2023-12-10T22:22:47.861596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
8 14
28.0%
9 11
22.0%
6 9
18.0%
7 9
18.0%
10 3
 
6.0%
5 3
 
6.0%
3 1
 
2.0%
ValueCountFrequency (%)
3 1
 
2.0%
5 3
 
6.0%
6 9
18.0%
7 9
18.0%
8 14
28.0%
9 11
22.0%
10 3
 
6.0%
ValueCountFrequency (%)
10 3
 
6.0%
9 11
22.0%
8 14
28.0%
7 9
18.0%
6 9
18.0%
5 3
 
6.0%
3 1
 
2.0%

cctv_info_1kmblw
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-10T22:22:48.347821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length1024
Mean length1024
Min length1024

Characters and Unicode

Total characters51200
Distinct characters43
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": 33, "latitude": 37.5011401, "agency_nm": "서울특별시 강남구청", "longitude": 127.0551521}, {"dist": 78, "latitude": 37.50146199999998, "agency_nm": "서울특별시 강남구청", "longitude": 127.053896}, {"dist": 82, "latitude": 37.501879399999986, "agency_nm": "서울특별시 강남구청", "longitude": 127.05517979999999}, {"dist": 103, "latitude": 37.50051939999999, "agency_nm": "서울특별시 강남구청", "longitude": 127.05515319999998}, {"dist": 113, "latitude": 37.5006955, "agency_nm": "서울특별시 강남구청", "longitude": 127.05381079999997}, {"dist": 118, "latitude": 37.50032289999999, "agency_nm": "서울특별시 강남구청", "longitude": 127.0544869}, {"dist": 148, "latitude": 37.50080809999999, "agency_nm": "서울특별시 강남구청", "longitude": 127.0560908}, {"dist": 150, "latitude": 37.5022636, "agency_nm": "서울특별시 강남구청", "longitude": 127.05394509999998}, {"dist": 161, "latitude": 37.50150610000001, "agency_nm": "서울특별시 강남구청", "longitude": 127.0562732}, {"dist": 167, "latitude": 37.499969000000014, "agency_nm": "서울특별시 강남구청", "longitude": 127.054851}, {"dist": 173, "latit
2nd row{"data": [{"dist": 52, "latitude": 37.516805300000016, "agency_nm": "서울특별시 강남구청", "longitude": 127.0600216}, {"dist": 62, "latitude": 37.516496700000005, "agency_nm": "서울특별시 강남구청", "longitude": 127.0600498}, {"dist": 117, "latitude": 37.516097699999996, "agency_nm": "서울특별시 강남구청", "longitude": 127.0602751}, {"dist": 135, "latitude": 37.51731549999999, "agency_nm": "서울특별시 강남구청", "longitude": 127.06057929999997}, {"dist": 147, "latitude": 37.5169975, "agency_nm": "서울특별시 강남구청", "longitude": 127.0608544}, {"dist": 207, "latitude": 37.51644340000001, "agency_nm": "서울특별시 강남구청", "longitude": 127.06138170000001}, {"dist": 209, "latitude": 37.51767829999999, "agency_nm": "서울특별시 강남구청", "longitude": 127.0610797}, {"dist": 211, "latitude": 37.5153721, "agency_nm": "서울특별시 강남구청", "longitude": 127.05846790000001}, {"dist": 231, "latitude": 37.51546569999999, "agency_nm": "서울특별시 강남구청", "longitude": 127.06092950000001}, {"dist": 238, "latitude": 37.5169062, "agency_nm": "서울특별시 강남구청", "longitude": 127.06169129999999}, {"dist":
3rd row{"data": [{"dist": 83, "latitude": 37.5194826, "agency_nm": "서울특별시 강남구청", "longitude": 127.0570135}, {"dist": 88, "latitude": 37.51988459999998, "agency_nm": "서울특별시 강남구청", "longitude": 127.05868720000001}, {"dist": 89, "latitude": 37.51974380000001, "agency_nm": "서울특별시 강남구청", "longitude": 127.0568571}, {"dist": 118, "latitude": 37.51926049999999, "agency_nm": "서울특별시 강남구청", "longitude": 127.05899969999999}, {"dist": 169, "latitude": 37.5210713, "agency_nm": "서울특별시 강남구청", "longitude": 127.0577579}, {"dist": 192, "latitude": 37.52085670000002, "agency_nm": "서울특별시 강남구청", "longitude": 127.05900409999998}, {"dist": 201, "latitude": 37.51912810000002, "agency_nm": "서울특별시 강남구청", "longitude": 127.05605039999998}, {"dist": 204, "latitude": 37.52131160000001, "agency_nm": "서울특별시 강남구청", "longitude": 127.05762519999998}, {"dist": 248, "latitude": 37.5204381, "agency_nm": "서울특별시 강남구청", "longitude": 127.0555734}, {"dist": 255, "latitude": 37.5190164, "agency_nm": "서울특별시 강남구청", "longitude": 127.0555839}, {"dist": 292, "latit
4th row{"data": [{"dist": 62, "latitude": 37.513595399999986, "agency_nm": "서울특별시 강남구청", "longitude": 127.0299038}, {"dist": 65, "latitude": 37.512953, "agency_nm": "서울특별시 강남구청", "longitude": 127.030212}, {"dist": 116, "latitude": 37.51222, "agency_nm": "서울특별시 강남구청", "longitude": 127.030146}, {"dist": 136, "latitude": 37.514331299999995, "agency_nm": "서울특별시 강남구청", "longitude": 127.0294517}, {"dist": 143, "latitude": 37.51230369999998, "agency_nm": "서울특별시 강남구청", "longitude": 127.0306364}, {"dist": 148, "latitude": 37.512973200000005, "agency_nm": "서울특별시 강남구청", "longitude": 127.02790430000002}, {"dist": 155, "latitude": 37.51197230000001, "agency_nm": "서울특별시 강남구청", "longitude": 127.0285786}, {"dist": 166, "latitude": 37.51284750000001, "agency_nm": "서울특별시 강남구청", "longitude": 127.03111910000001}, {"dist": 172, "latitude": 37.51391599999998, "agency_nm": "서울특별시 강남구청", "longitude": 127.030806}, {"dist": 195, "latitude": 37.513842299999986, "agency_nm": "서울특별시 강남구청", "longitude": 127.03107809999997}, {"dist": 203, "latitu
5th row{"data": [{"dist": 74, "latitude": 37.47370010000001, "agency_nm": "서울특별시 강남구청", "longitude": 127.112149}, {"dist": 172, "latitude": 37.4743217, "agency_nm": "서울특별시 강남구청", "longitude": 127.11174130000002}, {"dist": 303, "latitude": 37.475139099999986, "agency_nm": "서울특별시 강남구청", "longitude": 127.1111727}, {"dist": 355, "latitude": 37.47225399999999, "agency_nm": "서울특별시 강남구청", "longitude": 127.1095801}, {"dist": 382, "latitude": 37.4741463, "agency_nm": "서울특별시 강남구청", "longitude": 127.10927970000002}, {"dist": 383, "latitude": 37.47415570000001, "agency_nm": "서울특별시 강남구청", "longitude": 127.10927030000002}, {"dist": 389, "latitude": 37.4717637, "agency_nm": "서울특별시 강남구청", "longitude": 127.10954859999998}, {"dist": 404, "latitude": 37.475760599999994, "agency_nm": "서울특별시 강남구청", "longitude": 127.11071130000002}, {"dist": 432, "latitude": 37.472734200000005, "agency_nm": "서울특별시 강남구청", "longitude": 127.10869620000001}, {"dist": 449, "latitude": 37.47184849999999, "agency_nm": "서울특별시 강남구청", "longitude": 127.108889799999
ValueCountFrequency (%)
dist 532
 
11.5%
latitude 509
 
11.0%
longitude 501
 
10.8%
agency_nm 501
 
10.8%
서울특별시 482
 
10.4%
강남구청 482
 
10.4%
data 50
 
1.1%
서초구청 19
 
0.4%
148 10
 
0.2%
116 8
 
0.2%
Other values (886) 1532
33.1%
2023-12-10T22:22:49.049667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 5203
 
10.2%
4583
 
9.0%
9 3494
 
6.8%
0 2325
 
4.5%
t 2112
 
4.1%
: 2089
 
4.1%
, 2015
 
3.9%
7 1694
 
3.3%
d 1596
 
3.1%
i 1549
 
3.0%
Other values (33) 24540
47.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15308
29.9%
Lowercase Letter 14958
29.2%
Other Punctuation 10309
20.1%
Space Separator 4583
 
9.0%
Other Letter 4414
 
8.6%
Open Punctuation 637
 
1.2%
Connector Punctuation 501
 
1.0%
Close Punctuation 490
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2112
14.1%
d 1596
10.7%
i 1549
10.4%
e 1511
10.1%
n 1503
10.0%
a 1117
7.5%
l 1020
6.8%
u 1011
6.8%
g 1002
6.7%
s 533
 
3.6%
Other values (4) 2004
13.4%
Decimal Number
ValueCountFrequency (%)
9 3494
22.8%
0 2325
15.2%
7 1694
11.1%
1 1509
9.9%
2 1286
 
8.4%
3 1267
 
8.3%
4 1184
 
7.7%
5 924
 
6.0%
8 907
 
5.9%
6 718
 
4.7%
Other Letter
ValueCountFrequency (%)
청 501
11.4%
구 501
11.4%
서 501
11.4%
남 482
10.9%
강 482
10.9%
시 482
10.9%
별 482
10.9%
특 482
10.9%
울 482
10.9%
초 19
 
0.4%
Other Punctuation
ValueCountFrequency (%)
" 5203
50.5%
: 2089
20.3%
, 2015
 
19.5%
. 1002
 
9.7%
Open Punctuation
ValueCountFrequency (%)
{ 587
92.2%
[ 50
 
7.8%
Space Separator
ValueCountFrequency (%)
4583
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 501
100.0%
Close Punctuation
ValueCountFrequency (%)
} 490
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 31828
62.2%
Latin 14958
29.2%
Hangul 4414
 
8.6%

Most frequent character per script

Common
ValueCountFrequency (%)
" 5203
16.3%
4583
14.4%
9 3494
11.0%
0 2325
 
7.3%
: 2089
 
6.6%
, 2015
 
6.3%
7 1694
 
5.3%
1 1509
 
4.7%
2 1286
 
4.0%
3 1267
 
4.0%
Other values (9) 6363
20.0%
Latin
ValueCountFrequency (%)
t 2112
14.1%
d 1596
10.7%
i 1549
10.4%
e 1511
10.1%
n 1503
10.0%
a 1117
7.5%
l 1020
6.8%
u 1011
6.8%
g 1002
6.7%
s 533
 
3.6%
Other values (4) 2004
13.4%
Hangul
ValueCountFrequency (%)
청 501
11.4%
구 501
11.4%
서 501
11.4%
남 482
10.9%
강 482
10.9%
시 482
10.9%
별 482
10.9%
특 482
10.9%
울 482
10.9%
초 19
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46786
91.4%
Hangul 4414
 
8.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 5203
 
11.1%
4583
 
9.8%
9 3494
 
7.5%
0 2325
 
5.0%
t 2112
 
4.5%
: 2089
 
4.5%
, 2015
 
4.3%
7 1694
 
3.6%
d 1596
 
3.4%
i 1549
 
3.3%
Other values (23) 20126
43.0%
Hangul
ValueCountFrequency (%)
청 501
11.4%
구 501
11.4%
서 501
11.4%
남 482
10.9%
강 482
10.9%
시 482
10.9%
별 482
10.9%
특 482
10.9%
울 482
10.9%
초 19
 
0.4%

fire_statn_cnt_3kmblw
Categorical

Distinct5
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
3
26 
1
9 
2
8 
0
4 
4
3 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row1
5th row1

Common Values

ValueCountFrequency (%)
3 26
52.0%
1 9
 
18.0%
2 8
 
16.0%
0 4
 
8.0%
4 3
 
6.0%

Length

2023-12-10T22:22:49.301765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:22:49.505913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 26
52.0%
1 9
 
18.0%
2 8
 
16.0%
0 4
 
8.0%
4 3
 
6.0%

fire_statn_cnt_3kmovr_5kmblw
Real number (ℝ)

Distinct8
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.28
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:22:49.671134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median4
Q35
95-th percentile7
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.6664762
Coefficient of variation (CV)0.38936359
Kurtosis1.441873
Mean4.28
Median Absolute Deviation (MAD)1
Skewness0.74686667
Sum214
Variance2.7771429
MonotonicityNot monotonic
2023-12-10T22:22:49.946331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
4 22
44.0%
5 7
 
14.0%
3 6
 
12.0%
2 4
 
8.0%
6 4
 
8.0%
7 3
 
6.0%
1 2
 
4.0%
9 2
 
4.0%
ValueCountFrequency (%)
1 2
 
4.0%
2 4
 
8.0%
3 6
 
12.0%
4 22
44.0%
5 7
 
14.0%
6 4
 
8.0%
7 3
 
6.0%
9 2
 
4.0%
ValueCountFrequency (%)
9 2
 
4.0%
7 3
 
6.0%
6 4
 
8.0%
5 7
 
14.0%
4 22
44.0%
3 6
 
12.0%
2 4
 
8.0%
1 2
 
4.0%

fire_statn_cnt_5kmovr_7kmblw
Real number (ℝ)

Distinct8
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5
Minimum3
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:22:50.265279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3
Q14
median5
Q37
95-th percentile9
Maximum13
Range10
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.1116779
Coefficient of variation (CV)0.38394144
Kurtosis1.8073437
Mean5.5
Median Absolute Deviation (MAD)1
Skewness1.2123386
Sum275
Variance4.4591837
MonotonicityNot monotonic
2023-12-10T22:22:50.483856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
5 15
30.0%
4 11
22.0%
3 7
14.0%
8 5
 
10.0%
9 4
 
8.0%
7 4
 
8.0%
6 3
 
6.0%
13 1
 
2.0%
ValueCountFrequency (%)
3 7
14.0%
4 11
22.0%
5 15
30.0%
6 3
 
6.0%
7 4
 
8.0%
8 5
 
10.0%
9 4
 
8.0%
13 1
 
2.0%
ValueCountFrequency (%)
13 1
 
2.0%
9 4
 
8.0%
8 5
 
10.0%
7 4
 
8.0%
6 3
 
6.0%
5 15
30.0%
4 11
22.0%
3 7
14.0%

fire_statn_idx
Categorical

Distinct4
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
7
40 
6
5 
8
 
3
5
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7
2nd row7
3rd row7
4th row8
5th row5

Common Values

ValueCountFrequency (%)
7 40
80.0%
6 5
 
10.0%
8 3
 
6.0%
5 2
 
4.0%

Length

2023-12-10T22:22:50.738506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:22:50.912053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7 40
80.0%
6 5
 
10.0%
8 3
 
6.0%
5 2
 
4.0%

fire_statn_info_7kmblw
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-10T22:22:51.223476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length1024
Mean length1018.18
Min length927

Characters and Unicode

Total characters50909
Distinct characters94
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": 1832, "poi_nm": "강남소방서 상황실", "latitude": 37.510280274235605, "longitude": 127.066831554939}, {"dist": 1841, "poi_nm": "강남소방서", "latitude": 37.5102874233474, "longitude": 127.06693561802402}, {"dist": 2550, "poi_nm": "종합운동장119안전센터", "latitude": 37.51420981460559, "longitude": 127.071015642767}, {"dist": 3529, "poi_nm": "서초119안전센터", "latitude": 37.488033895517695, "longitude": 127.027593988144}, {"dist": 3750, "poi_nm": "개포119안전센터", "latitude": 37.47468805366239, "longitude": 127.04987830749896}, {"dist": 4429, "poi_nm": "잠실119안전센터", "latitude": 37.50733178533758, "longitude": 127.09390748426799}, {"dist": 4474, "poi_nm": "우면119안전센터", "latitude": 37.480660857746784, "longitude": 127.023846713984}, {"dist": 4792, "poi_nm": "잠원119안전센터", "latitude": 37.499084696418976, "longitude": 127.011611900567}, {"dist": 6559, "poi_nm": "가락119안전센터", "latitude": 37.49651694457059, "longitude": 127.11349145321998}, {"dist": 6992, "poi_nm": "서초소방서", "latitude": 37.4984416680043, "longitude": 126.99185771647402
2nd row{"data": [{"dist": 1212, "poi_nm": "강남소방서 상황실", "latitude": 37.510280274235605, "longitude": 127.066831554939}, {"dist": 1219, "poi_nm": "강남소방서", "latitude": 37.5102874233474, "longitude": 127.06693561802402}, {"dist": 1323, "poi_nm": "종합운동장119안전센터", "latitude": 37.51420981460559, "longitude": 127.071015642767}, {"dist": 4044, "poi_nm": "잠실119안전센터", "latitude": 37.50733178533758, "longitude": 127.09390748426799}, {"dist": 5267, "poi_nm": "능동119안전센터", "latitude": 37.5516804850798, "longitude": 127.07701285191297}, {"dist": 5354, "poi_nm": "서초119안전센터", "latitude": 37.488033895517695, "longitude": 127.027593988144}, {"dist": 5630, "poi_nm": "성동소방서", "latitude": 37.553704646830695, "longitude": 127.03940378173}, {"dist": 5858, "poi_nm": "잠원119안전센터", "latitude": 37.499084696418976, "longitude": 127.011611900567}, {"dist": 5990, "poi_nm": "개포119안전센터", "latitude": 37.47468805366239, "longitude": 127.04987830749896}, {"dist": 6418, "poi_nm": "우면119안전센터", "latitude": 37.480660857746784, "longitude": 127.023846713984},
3rd row{"data": [{"dist": 1626, "poi_nm": "강남소방서 상황실", "latitude": 37.510280274235605, "longitude": 127.066831554939}, {"dist": 1629, "poi_nm": "종합운동장119안전센터", "latitude": 37.51420981460559, "longitude": 127.071015642767}, {"dist": 1632, "poi_nm": "강남소방서", "latitude": 37.5102874233474, "longitude": 127.06693561802402}, {"dist": 4348, "poi_nm": "잠실119안전센터", "latitude": 37.50733178533758, "longitude": 127.09390748426799}, {"dist": 4951, "poi_nm": "능동119안전센터", "latitude": 37.5516804850798, "longitude": 127.07701285191297}, {"dist": 5174, "poi_nm": "성동소방서", "latitude": 37.553704646830695, "longitude": 127.03940378173}, {"dist": 5548, "poi_nm": "서초119안전센터", "latitude": 37.488033895517695, "longitude": 127.027593988144}, {"dist": 5887, "poi_nm": "잠원119안전센터", "latitude": 37.499084696418976, "longitude": 127.011611900567}, {"dist": 6075, "poi_nm": "금호119안전센터", "latitude": 37.55407812474659, "longitude": 127.02432729995297}, {"dist": 6269, "poi_nm": "동대문소방서", "latitude": 37.5639655788764, "longitude": 127.066648583867}, {"di
4th row{"data": [{"dist": 2767, "poi_nm": "잠원119안전센터", "latitude": 37.499084696418976, "longitude": 127.011611900567}, {"dist": 3490, "poi_nm": "서초119안전센터", "latitude": 37.488033895517695, "longitude": 127.027593988144}, {"dist": 3948, "poi_nm": "서빙고119안전센터", "latitude": 37.5208336115307, "longitude": 126.995027198306}, {"dist": 4158, "poi_nm": "강남소방서 상황실", "latitude": 37.510280274235605, "longitude": 127.066831554939}, {"dist": 4169, "poi_nm": "강남소방서", "latitude": 37.5102874233474, "longitude": 127.06693561802402}, {"dist": 4561, "poi_nm": "우면119안전센터", "latitude": 37.480660857746784, "longitude": 127.023846713984}, {"dist": 4610, "poi_nm": "종합운동장119안전센터", "latitude": 37.51420981460559, "longitude": 127.071015642767}, {"dist": 4643, "poi_nm": "서초소방서", "latitude": 37.4984416680043, "longitude": 126.99185771647402}, {"dist": 4643, "poi_nm": "서초119구조대", "latitude": 37.4984308562398, "longitude": 126.991862241138}, {"dist": 4750, "poi_nm": "이태원119안전센터", "latitude": 37.5343738986394, "longitude": 126.99581376426701}, {"d
5th row{"data": [{"dist": 710, "poi_nm": "세곡119안전센터", "latitude": 37.470447677010604, "longitude": 127.107162202314}, {"dist": 3242, "poi_nm": "가락119안전센터", "latitude": 37.49651694457059, "longitude": 127.11349145321998}, {"dist": 3757, "poi_nm": "위례119안전센터", "latitude": 37.4619358824684, "longitude": 127.143623283317}, {"dist": 4982, "poi_nm": "송파소방서", "latitude": 37.499930794793876, "longitude": 127.14263750750702}, {"dist": 5206, "poi_nm": "잠실119안전센터", "latitude": 37.50733178533758, "longitude": 127.09390748426799}, {"dist": 5579, "poi_nm": "성남소방서", "latitude": 37.43670495994908, "longitude": 127.133505008989}, {"dist": 5582, "poi_nm": "수진119안전센터", "latitude": 37.43668333052369, "longitude": 127.13350949033702}, {"dist": 6376, "poi_nm": "은행의용소방대", "latitude": 37.45709440175349, "longitude": 127.16654451046097}, {"dist": 6861, "poi_nm": "성남소방서 (2021년12월예정)", "latitude": 37.4279107282916, "longitude": 127.13693305226299}, {"dist": 6976, "poi_nm": "개포119안전센터", "latitude": 37.47468805366239, "longitude": 127.049878307
ValueCountFrequency (%)
poi_nm 497
 
12.1%
latitude 497
 
12.1%
longitude 497
 
12.1%
dist 497
 
12.1%
강남소방서 98
 
2.4%
data 50
 
1.2%
잠원119안전센터 49
 
1.2%
127.027593988144 49
 
1.2%
37.488033895517695 49
 
1.2%
서초119안전센터 49
 
1.2%
Other values (559) 1775
43.2%
2023-12-10T22:22:51.756479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 5083
 
10.0%
4058
 
8.0%
1 2579
 
5.1%
7 2314
 
4.5%
t 2038
 
4.0%
: 2038
 
4.0%
i 1989
 
3.9%
, 1972
 
3.9%
9 1960
 
3.9%
4 1904
 
3.7%
Other values (84) 24974
49.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18890
37.1%
Lowercase Letter 13131
25.8%
Other Punctuation 10087
19.8%
Space Separator 4058
 
8.0%
Other Letter 3124
 
6.1%
Open Punctuation 629
 
1.2%
Connector Punctuation 497
 
1.0%
Close Punctuation 493
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 326
 
10.4%
전 326
 
10.4%
터 326
 
10.4%
센 326
 
10.4%
서 258
 
8.3%
방 148
 
4.7%
소 139
 
4.4%
초 111
 
3.6%
남 100
 
3.2%
강 98
 
3.1%
Other values (49) 966
30.9%
Lowercase Letter
ValueCountFrequency (%)
t 2038
15.5%
i 1989
15.1%
d 1549
11.8%
e 994
7.6%
o 994
7.6%
n 994
7.6%
u 994
7.6%
l 994
7.6%
a 597
 
4.5%
g 497
 
3.8%
Other values (3) 1491
11.4%
Decimal Number
ValueCountFrequency (%)
1 2579
13.7%
7 2314
12.2%
9 1960
10.4%
4 1904
10.1%
3 1888
10.0%
0 1770
9.4%
6 1709
9.0%
8 1669
8.8%
2 1616
8.6%
5 1481
7.8%
Other Punctuation
ValueCountFrequency (%)
" 5083
50.4%
: 2038
20.2%
, 1972
 
19.5%
. 994
 
9.9%
Open Punctuation
ValueCountFrequency (%)
{ 578
91.9%
[ 50
 
7.9%
( 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
} 489
99.2%
] 3
 
0.6%
) 1
 
0.2%
Space Separator
ValueCountFrequency (%)
4058
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 497
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34654
68.1%
Latin 13131
 
25.8%
Hangul 3124
 
6.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 326
 
10.4%
전 326
 
10.4%
터 326
 
10.4%
센 326
 
10.4%
서 258
 
8.3%
방 148
 
4.7%
소 139
 
4.4%
초 111
 
3.6%
남 100
 
3.2%
강 98
 
3.1%
Other values (49) 966
30.9%
Common
ValueCountFrequency (%)
" 5083
14.7%
4058
11.7%
1 2579
 
7.4%
7 2314
 
6.7%
: 2038
 
5.9%
, 1972
 
5.7%
9 1960
 
5.7%
4 1904
 
5.5%
3 1888
 
5.4%
0 1770
 
5.1%
Other values (12) 9088
26.2%
Latin
ValueCountFrequency (%)
t 2038
15.5%
i 1989
15.1%
d 1549
11.8%
e 994
7.6%
o 994
7.6%
n 994
7.6%
u 994
7.6%
l 994
7.6%
a 597
 
4.5%
g 497
 
3.8%
Other values (3) 1491
11.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47785
93.9%
Hangul 3124
 
6.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 5083
 
10.6%
4058
 
8.5%
1 2579
 
5.4%
7 2314
 
4.8%
t 2038
 
4.3%
: 2038
 
4.3%
i 1989
 
4.2%
, 1972
 
4.1%
9 1960
 
4.1%
4 1904
 
4.0%
Other values (25) 21850
45.7%
Hangul
ValueCountFrequency (%)
안 326
 
10.4%
전 326
 
10.4%
터 326
 
10.4%
센 326
 
10.4%
서 258
 
8.3%
방 148
 
4.7%
소 139
 
4.4%
초 111
 
3.6%
남 100
 
3.2%
강 98
 
3.1%
Other values (49) 966
30.9%

police_statn_cnt_2kmblw
Real number (ℝ)

Distinct8
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.08
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:22:52.052747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q36
95-th percentile7
Maximum8
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.6393129
Coefficient of variation (CV)0.3226994
Kurtosis-0.010079436
Mean5.08
Median Absolute Deviation (MAD)1
Skewness-0.62553063
Sum254
Variance2.6873469
MonotonicityNot monotonic
2023-12-10T22:22:52.328252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
6 16
32.0%
5 10
20.0%
4 9
18.0%
7 6
 
12.0%
2 5
 
10.0%
8 2
 
4.0%
1 1
 
2.0%
3 1
 
2.0%
ValueCountFrequency (%)
1 1
 
2.0%
2 5
 
10.0%
3 1
 
2.0%
4 9
18.0%
5 10
20.0%
6 16
32.0%
7 6
 
12.0%
8 2
 
4.0%
ValueCountFrequency (%)
8 2
 
4.0%
7 6
 
12.0%
6 16
32.0%
5 10
20.0%
4 9
18.0%
3 1
 
2.0%
2 5
 
10.0%
1 1
 
2.0%

police_statn_cnt_2kmovr_3kmblw
Real number (ℝ)

Distinct11
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.36
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:22:52.539348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median5
Q37
95-th percentile10
Maximum11
Range10
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.5853591
Coefficient of variation (CV)0.48234311
Kurtosis-0.51727493
Mean5.36
Median Absolute Deviation (MAD)2
Skewness0.49938778
Sum268
Variance6.6840816
MonotonicityNot monotonic
2023-12-10T22:22:52.766439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
3 9
18.0%
5 8
16.0%
4 7
14.0%
7 6
12.0%
6 6
12.0%
10 5
10.0%
2 3
 
6.0%
1 2
 
4.0%
9 2
 
4.0%
11 1
 
2.0%
ValueCountFrequency (%)
1 2
 
4.0%
2 3
 
6.0%
3 9
18.0%
4 7
14.0%
5 8
16.0%
6 6
12.0%
7 6
12.0%
8 1
 
2.0%
9 2
 
4.0%
10 5
10.0%
ValueCountFrequency (%)
11 1
 
2.0%
10 5
10.0%
9 2
 
4.0%
8 1
 
2.0%
7 6
12.0%
6 6
12.0%
5 8
16.0%
4 7
14.0%
3 9
18.0%
2 3
 
6.0%

police_statn_cnt_3kmovr_5kmblw
Real number (ℝ)

Distinct12
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.6
Minimum9
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:22:53.004066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile9.45
Q112.25
median14
Q317
95-th percentile20
Maximum21
Range12
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation3.350297
Coefficient of variation (CV)0.2294724
Kurtosis-0.79586787
Mean14.6
Median Absolute Deviation (MAD)2
Skewness0.21436363
Sum730
Variance11.22449
MonotonicityNot monotonic
2023-12-10T22:22:53.180004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
14 9
18.0%
19 7
14.0%
13 6
12.0%
15 5
10.0%
10 4
8.0%
12 4
8.0%
17 3
 
6.0%
9 3
 
6.0%
16 3
 
6.0%
20 2
 
4.0%
Other values (2) 4
8.0%
ValueCountFrequency (%)
9 3
 
6.0%
10 4
8.0%
11 2
 
4.0%
12 4
8.0%
13 6
12.0%
14 9
18.0%
15 5
10.0%
16 3
 
6.0%
17 3
 
6.0%
19 7
14.0%
ValueCountFrequency (%)
21 2
 
4.0%
20 2
 
4.0%
19 7
14.0%
17 3
 
6.0%
16 3
 
6.0%
15 5
10.0%
14 9
18.0%
13 6
12.0%
12 4
8.0%
11 2
 
4.0%

police_statn_idx
Categorical

Distinct4
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
9
26 
8
17 
7
4 
6
3 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9
2nd row9
3rd row9
4th row9
5th row6

Common Values

ValueCountFrequency (%)
9 26
52.0%
8 17
34.0%
7 4
 
8.0%
6 3
 
6.0%

Length

2023-12-10T22:22:53.375208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:22:53.827065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9 26
52.0%
8 17
34.0%
7 4
 
8.0%
6 3
 
6.0%

police_statn_info_5kmblw
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-10T22:22:54.246307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length1024
Mean length1024
Min length1024

Characters and Unicode

Total characters51200
Distinct characters96
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": 839, "poi_nm": "은마치안센터", "latitude": 37.4983574726281, "longitude": 127.06148321554397}, {"dist": 1209, "poi_nm": "도곡지구대", "latitude": 37.50134591470668, "longitude": 127.043707660284}, {"dist": 1242, "poi_nm": "대치지구대", "latitude": 37.494860970170784, "longitude": 127.062620214175}, {"dist": 1308, "poi_nm": "코엑스치안센터", "latitude": 37.51000319180728, "longitude": 127.05928043856298}, {"dist": 1769, "poi_nm": "서울강남경찰서", "latitude": 37.509389946371506, "longitude": 127.067070541137}, {"dist": 1803, "poi_nm": "역삼지구대", "latitude": 37.50835309597459, "longitude": 127.041019912837}, {"dist": 1981, "poi_nm": "삼성2파출소", "latitude": 37.51225812788648, "longitude": 127.04332379983299}, {"dist": 1996, "poi_nm": "삼성1파출소", "latitude": 37.514849940015594, "longitude": 127.060569224451}, {"dist": 2697, "poi_nm": "역서치안센터", "latitude": 37.493885669346476, "longitude": 127.03221886755499}, {"dist": 2706, "poi_nm": "수서경찰서", "latitude": 37.49349726534249, "longitude": 127.07714304432699}, {"dist": 2727, "poi_nm":
2nd row{"data": [{"dist": 283, "poi_nm": "삼성1파출소", "latitude": 37.514849940015594, "longitude": 127.060569224451}, {"dist": 789, "poi_nm": "청담파출소", "latitude": 37.5208140333536, "longitude": 127.05428451685599}, {"dist": 940, "poi_nm": "코엑스치안센터", "latitude": 37.51000319180728, "longitude": 127.05928043856298}, {"dist": 1324, "poi_nm": "서울강남경찰서", "latitude": 37.509389946371506, "longitude": 127.067070541137}, {"dist": 1515, "poi_nm": "청담2치안센터", "latitude": 37.5227233274492, "longitude": 127.04787403756299}, {"dist": 1885, "poi_nm": "삼성2파출소", "latitude": 37.51225812788648, "longitude": 127.04332379983299}, {"dist": 2350, "poi_nm": "역삼지구대", "latitude": 37.50835309597459, "longitude": 127.041019912837}, {"dist": 2583, "poi_nm": "은마치안센터", "latitude": 37.4983574726281, "longitude": 127.06148321554397}, {"dist": 2745, "poi_nm": "자양파출소", "latitude": 37.53386932579772, "longitude": 127.07160903488301}, {"dist": 2770, "poi_nm": "도곡지구대", "latitude": 37.50134591470668, "longitude": 127.043707660284}, {"dist": 3084, "poi_nm": "대
3rd row{"data": [{"dist": 400, "poi_nm": "청담파출소", "latitude": 37.5208140333536, "longitude": 127.05428451685599}, {"dist": 714, "poi_nm": "삼성1파출소", "latitude": 37.514849940015594, "longitude": 127.060569224451}, {"dist": 1163, "poi_nm": "청담2치안센터", "latitude": 37.5227233274492, "longitude": 127.04787403756299}, {"dist": 1336, "poi_nm": "코엑스치안센터", "latitude": 37.51000319180728, "longitude": 127.05928043856298}, {"dist": 1743, "poi_nm": "서울강남경찰서", "latitude": 37.509389946371506, "longitude": 127.067070541137}, {"dist": 1906, "poi_nm": "삼성2파출소", "latitude": 37.51225812788648, "longitude": 127.04332379983299}, {"dist": 2436, "poi_nm": "역삼지구대", "latitude": 37.50835309597459, "longitude": 127.041019912837}, {"dist": 2494, "poi_nm": "자양파출소", "latitude": 37.53386932579772, "longitude": 127.07160903488301}, {"dist": 2786, "poi_nm": "압구정파출소", "latitude": 37.52931126233199, "longitude": 127.035682418555}, {"dist": 2876, "poi_nm": "성수1치안센터", "latitude": 37.53966796707461, "longitude": 127.051193360363}, {"dist": 2891, "poi_nm":
4th row{"data": [{"dist": 76, "poi_nm": "논현1파출소", "latitude": 37.513895960544396, "longitude": 127.02929564136299}, {"dist": 914, "poi_nm": "신사파출소", "latitude": 37.518423769141194, "longitude": 127.02413925718898}, {"dist": 1422, "poi_nm": "역삼지구대", "latitude": 37.50835309597459, "longitude": 127.041019912837}, {"dist": 1526, "poi_nm": "반포치안센터", "latitude": 37.50791567423121, "longitude": 127.01718238918599}, {"dist": 1527, "poi_nm": "삼성2파출소", "latitude": 37.51225812788648, "longitude": 127.04332379983299}, {"dist": 1722, "poi_nm": "잠원치안센터", "latitude": 37.514994399674684, "longitude": 127.01387208550597}, {"dist": 2259, "poi_nm": "도곡지구대", "latitude": 37.50134591470668, "longitude": 127.043707660284}, {"dist": 2344, "poi_nm": "압구정파출소", "latitude": 37.52931126233199, "longitude": 127.035682418555}, {"dist": 2424, "poi_nm": "압구정치안센터", "latitude": 37.53061104904198, "longitude": 127.03053309533598}, {"dist": 2438, "poi_nm": "청담2치안센터", "latitude": 37.5227233274492, "longitude": 127.04787403756299}, {"dist": 2682, "poi_nm
5th row{"data": [{"dist": 1240, "poi_nm": "대왕파출소", "latitude": 37.465182021764804, "longitude": 127.10732650262102}, {"dist": 1709, "poi_nm": "문정지구대", "latitude": 37.47820193694737, "longitude": 127.12699437525097}, {"dist": 2333, "poi_nm": "문정2치안센터", "latitude": 37.4899815107379, "longitude": 127.111102478057}, {"dist": 3527, "poi_nm": "가락2치안센터", "latitude": 37.49321762101341, "longitude": 127.132384277696}, {"dist": 4091, "poi_nm": "성남위례파출소", "latitude": 37.47238279344789, "longitude": 127.149676636786}, {"dist": 4213, "poi_nm": "일원지구대", "latitude": 37.49241542744999, "longitude": 127.083374799614}, {"dist": 4312, "poi_nm": "서울송파경찰서", "latitude": 37.5019757297179, "longitude": 127.12716129352496}, {"dist": 4576, "poi_nm": "성남수정경찰서", "latitude": 37.44221226542422, "longitude": 127.12668040081499}, {"dist": 4638, "poi_nm": "송파1치안센터", "latitude": 37.506352627643594, "longitude": 127.10934429266999}, {"dist": 4676, "poi_nm": "삼전지구대", "latitude": 37.502674504337286, "longitude": 127.092749226974}, {"dist": 4703, "poi_n
ValueCountFrequency (%)
dist 550
 
13.0%
poi_nm 545
 
12.9%
latitude 500
 
11.8%
longitude 500
 
11.8%
data 50
 
1.2%
도곡지구대 44
 
1.0%
37.50134591470668 44
 
1.0%
127.043707660284 44
 
1.0%
127.03221886755499 37
 
0.9%
역서치안센터 37
 
0.9%
Other values (636) 1877
44.4%
2023-12-10T22:22:54.935057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 5320
 
10.4%
4187
 
8.2%
7 2539
 
5.0%
: 2141
 
4.2%
i 2100
 
4.1%
t 2100
 
4.1%
2 2099
 
4.1%
, 2050
 
4.0%
3 1974
 
3.9%
1 1952
 
3.8%
Other values (86) 24738
48.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18356
35.9%
Lowercase Letter 13642
26.6%
Other Punctuation 10511
20.5%
Space Separator 4187
 
8.2%
Other Letter 2805
 
5.5%
Open Punctuation 650
 
1.3%
Connector Punctuation 549
 
1.1%
Close Punctuation 500
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 187
 
6.7%
치 179
 
6.4%
구 159
 
5.7%
지 151
 
5.4%
파 149
 
5.3%
출 146
 
5.2%
소 146
 
5.2%
안 144
 
5.1%
터 141
 
5.0%
센 141
 
5.0%
Other values (54) 1262
45.0%
Lowercase Letter
ValueCountFrequency (%)
i 2100
15.4%
t 2100
15.4%
d 1600
11.7%
o 1050
7.7%
n 1047
7.7%
l 1000
7.3%
e 1000
7.3%
u 1000
7.3%
a 600
 
4.4%
p 550
 
4.0%
Other values (3) 1595
11.7%
Decimal Number
ValueCountFrequency (%)
7 2539
13.8%
2 2099
11.4%
3 1974
10.8%
1 1952
10.6%
4 1928
10.5%
9 1859
10.1%
0 1683
9.2%
5 1640
8.9%
8 1443
7.9%
6 1239
6.7%
Other Punctuation
ValueCountFrequency (%)
" 5320
50.6%
: 2141
20.4%
, 2050
 
19.5%
. 1000
 
9.5%
Open Punctuation
ValueCountFrequency (%)
{ 600
92.3%
[ 50
 
7.7%
Space Separator
ValueCountFrequency (%)
4187
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 549
100.0%
Close Punctuation
ValueCountFrequency (%)
} 500
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34753
67.9%
Latin 13642
 
26.6%
Hangul 2805
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 187
 
6.7%
치 179
 
6.4%
구 159
 
5.7%
지 151
 
5.4%
파 149
 
5.3%
출 146
 
5.2%
소 146
 
5.2%
안 144
 
5.1%
터 141
 
5.0%
센 141
 
5.0%
Other values (54) 1262
45.0%
Common
ValueCountFrequency (%)
" 5320
15.3%
4187
12.0%
7 2539
 
7.3%
: 2141
 
6.2%
2 2099
 
6.0%
, 2050
 
5.9%
3 1974
 
5.7%
1 1952
 
5.6%
4 1928
 
5.5%
9 1859
 
5.3%
Other values (9) 8704
25.0%
Latin
ValueCountFrequency (%)
i 2100
15.4%
t 2100
15.4%
d 1600
11.7%
o 1050
7.7%
n 1047
7.7%
l 1000
7.3%
e 1000
7.3%
u 1000
7.3%
a 600
 
4.4%
p 550
 
4.0%
Other values (3) 1595
11.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48395
94.5%
Hangul 2805
 
5.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 5320
 
11.0%
4187
 
8.7%
7 2539
 
5.2%
: 2141
 
4.4%
i 2100
 
4.3%
t 2100
 
4.3%
2 2099
 
4.3%
, 2050
 
4.2%
3 1974
 
4.1%
1 1952
 
4.0%
Other values (22) 21933
45.3%
Hangul
ValueCountFrequency (%)
대 187
 
6.7%
치 179
 
6.4%
구 159
 
5.7%
지 151
 
5.4%
파 149
 
5.3%
출 146
 
5.2%
소 146
 
5.2%
안 144
 
5.1%
터 141
 
5.0%
센 141
 
5.0%
Other values (54) 1262
45.0%

lo
Real number (ℝ)

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.04848
Minimum127.02941
Maximum127.11274
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:22:55.227246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.02941
5-th percentile127.03206
Q1127.03918
median127.04628
Q3127.05395
95-th percentile127.06904
Maximum127.11274
Range0.083330978
Interquartile range (IQR)0.014763146

Descriptive statistics

Standard deviation0.014058069
Coefficient of variation (CV)0.00011065122
Kurtosis7.8423943
Mean127.04848
Median Absolute Deviation (MAD)0.0071621038
Skewness2.084071
Sum6352.424
Variance0.0001976293
MonotonicityNot monotonic
2023-12-10T22:22:55.456600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.054719015615 1
 
2.0%
127.036351933213 1
 
2.0%
127.049298793106 1
 
2.0%
127.039114548945 1
 
2.0%
127.051880882698 1
 
2.0%
127.051003157318 1
 
2.0%
127.048829672038 1
 
2.0%
127.048730912287 1
 
2.0%
127.046289918215 1
 
2.0%
127.045968749644 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
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%
127.034385507106 1
2.0%
127.034845549184 1
2.0%
127.035868808941 1
2.0%
127.035878982388 1
2.0%
127.036351933213 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%
127.060483984218 1
2.0%
127.059418422668 1
2.0%
127.059365680062 1
2.0%
127.057829498346 1
2.0%
127.057218089165 1
2.0%

la
Real number (ℝ)

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.496221
Minimum37.473165
Maximum37.523684
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T22:22:55.687395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.473165
5-th percentile37.478359
Q137.486484
median37.49252
Q337.50645
95-th percentile37.519071
Maximum37.523684
Range0.050519605
Interquartile range (IQR)0.01996575

Descriptive statistics

Standard deviation0.01316303
Coefficient of variation (CV)0.00035104951
Kurtosis-0.804681
Mean37.496221
Median Absolute Deviation (MAD)0.0083634414
Skewness0.39604713
Sum1874.811
Variance0.00017326536
MonotonicityNot monotonic
2023-12-10T22:22:55.946349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5012685169127 1
 
2.0%
37.5116200294638 1
 
2.0%
37.485349608008896 1
 
2.0%
37.4928940766838 1
 
2.0%
37.486638753585694 1
 
2.0%
37.4870848920094 1
 
2.0%
37.486731832591 1
 
2.0%
37.48917300218591 1
 
2.0%
37.4962280404637 1
 
2.0%
37.4965465137377 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 (%)
37.52368419807831 1
2.0%
37.521092184631506 1
2.0%
37.5196629002269 1
2.0%
37.518348072455105 1
2.0%
37.5167639969676 1
2.0%
37.514721392611904 1
2.0%
37.5138822721222 1
2.0%
37.51311643403751 1
2.0%
37.5116200294638 1
2.0%
37.510587940782706 1
2.0%

Sample

uidapt_cdapt_nmrdnmadrlegaldong_cdstrd_yearcctv_cnt_250mblwcctv_cnt_250movr_500mblwcctv_cnt_500movr_1kmblwcctv_idxcctv_info_1kmblwfire_statn_cnt_3kmblwfire_statn_cnt_3kmovr_5kmblwfire_statn_cnt_5kmovr_7kmblwfire_statn_idxfire_statn_info_7kmblwpolice_statn_cnt_2kmblwpolice_statn_cnt_2kmovr_3kmblwpolice_statn_cnt_3kmovr_5kmblwpolice_statn_idxpolice_statn_info_5kmblwlola
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