Overview

Dataset statistics

Number of variables9
Number of observations46
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory77.9 B

Variable types

Text5
Categorical1
Numeric3

Alerts

소재지우편번호 is highly overall correlated with WGS84위도High correlation
WGS84위도 is highly overall correlated with 소재지우편번호High correlation
운영방법 is highly imbalanced (74.2%)Imbalance
지역구분명 has unique valuesUnique
상담센터전화번호 has unique valuesUnique
소재지우편번호 has unique valuesUnique
소재지지번주소 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
WGS84위도 has unique valuesUnique
WGS84경도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:11:20.058342
Analysis finished2023-12-10 21:11:21.650596
Duration1.59 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

Distinct31
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-11T06:11:21.776502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0869565
Min length3

Characters and Unicode

Total characters142
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)47.8%

Sample

1st row가평군
2nd row고양시
3rd row고양시
4th row고양시
5th row과천시
ValueCountFrequency (%)
수원시 4
 
8.7%
용인시 3
 
6.5%
부천시 3
 
6.5%
성남시 3
 
6.5%
고양시 3
 
6.5%
안양시 2
 
4.3%
평택시 2
 
4.3%
안산시 2
 
4.3%
남양주시 2
 
4.3%
의정부시 1
 
2.2%
Other values (21) 21
45.7%
2023-12-11T06:11:22.059853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 44
31.0%
양 9
 
6.3%
천 8
 
5.6%
주 6
 
4.2%
남 6
 
4.2%
성 5
 
3.5%
안 5
 
3.5%
수 4
 
2.8%
원 4
 
2.8%
군 4
 
2.8%
Other values (28) 47
33.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 142
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 44
31.0%
양 9
 
6.3%
천 8
 
5.6%
주 6
 
4.2%
남 6
 
4.2%
성 5
 
3.5%
안 5
 
3.5%
수 4
 
2.8%
원 4
 
2.8%
군 4
 
2.8%
Other values (28) 47
33.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 142
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 44
31.0%
양 9
 
6.3%
천 8
 
5.6%
주 6
 
4.2%
남 6
 
4.2%
성 5
 
3.5%
안 5
 
3.5%
수 4
 
2.8%
원 4
 
2.8%
군 4
 
2.8%
Other values (28) 47
33.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 142
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 44
31.0%
양 9
 
6.3%
천 8
 
5.6%
주 6
 
4.2%
남 6
 
4.2%
성 5
 
3.5%
안 5
 
3.5%
수 4
 
2.8%
원 4
 
2.8%
군 4
 
2.8%
Other values (28) 47
33.1%

지역구분명
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-11T06:11:22.275656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.8695652
Min length3

Characters and Unicode

Total characters224
Distinct characters64
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row가평군
2nd row고양시 일산동구
3rd row고양시 덕양구
4th row고양시 일산서구
5th row과천시
ValueCountFrequency (%)
고양시 3
 
4.5%
부천시 3
 
4.5%
용인시 3
 
4.5%
성남시 3
 
4.5%
안양시 2
 
3.0%
안산시 2
 
3.0%
수원시 2
 
3.0%
남양주시 2
 
3.0%
평택시 2
 
3.0%
양평군 1
 
1.5%
Other values (43) 43
65.2%
2023-12-11T06:11:22.626569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 44
19.6%
20
 
8.9%
구 16
 
7.1%
양 11
 
4.9%
안 8
 
3.6%
천 8
 
3.6%
수 7
 
3.1%
남 6
 
2.7%
주 6
 
2.7%
원 6
 
2.7%
Other values (54) 92
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 204
91.1%
Space Separator 20
 
8.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 44
21.6%
구 16
 
7.8%
양 11
 
5.4%
안 8
 
3.9%
천 8
 
3.9%
수 7
 
3.4%
남 6
 
2.9%
주 6
 
2.9%
원 6
 
2.9%
성 5
 
2.5%
Other values (53) 87
42.6%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 204
91.1%
Common 20
 
8.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 44
21.6%
구 16
 
7.8%
양 11
 
5.4%
안 8
 
3.9%
천 8
 
3.9%
수 7
 
3.4%
남 6
 
2.9%
주 6
 
2.9%
원 6
 
2.9%
성 5
 
2.5%
Other values (53) 87
42.6%
Common
ValueCountFrequency (%)
20
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 204
91.1%
ASCII 20
 
8.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 44
21.6%
구 16
 
7.8%
양 11
 
5.4%
안 8
 
3.9%
천 8
 
3.9%
수 7
 
3.4%
남 6
 
2.9%
주 6
 
2.9%
원 6
 
2.9%
성 5
 
2.5%
Other values (53) 87
42.6%
ASCII
ValueCountFrequency (%)
20
100.0%

상담센터전화번호
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-11T06:11:22.892035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.23913
Min length12

Characters and Unicode

Total characters563
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row031-580-2849
2nd row031-8075-4850
3rd row031-8075-4800
4th row031-8075-4871
5th row02-2150-3573
ValueCountFrequency (%)
031-580-2849 1
 
2.2%
031-8036-6611 1
 
2.2%
031-790-6254 1
 
2.2%
031-481-6557 1
 
2.2%
031-678-3002 1
 
2.2%
031-8045-3038 1
 
2.2%
031-8045-6801 1
 
2.2%
031-8082-4306 1
 
2.2%
031-771-5773 1
 
2.2%
031-887-3685 1
 
2.2%
Other values (36) 36
78.3%
2023-12-11T06:11:23.251736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 92
16.3%
0 86
15.3%
3 73
13.0%
1 65
11.5%
8 50
8.9%
5 40
7.1%
2 38
6.7%
4 37
6.6%
6 31
 
5.5%
7 28
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 471
83.7%
Dash Punctuation 92
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 86
18.3%
3 73
15.5%
1 65
13.8%
8 50
10.6%
5 40
8.5%
2 38
8.1%
4 37
7.9%
6 31
 
6.6%
7 28
 
5.9%
9 23
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 563
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 92
16.3%
0 86
15.3%
3 73
13.0%
1 65
11.5%
8 50
8.9%
5 40
7.1%
2 38
6.7%
4 37
6.6%
6 31
 
5.5%
7 28
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 563
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 92
16.3%
0 86
15.3%
3 73
13.0%
1 65
11.5%
8 50
8.9%
5 40
7.1%
2 38
6.7%
4 37
6.6%
6 31
 
5.5%
7 28
 
5.0%

운영방법
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
직영
44 
위탁
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
직영 44
95.7%
위탁 2
 
4.3%

Length

2023-12-11T06:11:23.387326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:11:23.471325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
직영 44
95.7%
위탁 2
 
4.3%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14138.174
Minimum10097
Maximum18614
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-11T06:11:23.572453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10097
5-th percentile10431.75
Q112058
median13987
Q316421
95-th percentile17853.75
Maximum18614
Range8517
Interquartile range (IQR)4363

Descriptive statistics

Standard deviation2483.5542
Coefficient of variation (CV)0.17566301
Kurtosis-1.2248607
Mean14138.174
Median Absolute Deviation (MAD)2198.5
Skewness0.081636796
Sum650356
Variance6168041.4
MonotonicityNot monotonic
2023-12-11T06:11:23.714510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
12413 1
 
2.2%
16969 1
 
2.2%
17596 1
 
2.2%
14035 1
 
2.2%
13939 1
 
2.2%
11451 1
 
2.2%
12550 1
 
2.2%
12628 1
 
2.2%
11027 1
 
2.2%
18131 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
10097 1
2.2%
10353 1
2.2%
10410 1
2.2%
10497 1
2.2%
10937 1
2.2%
11027 1
2.2%
11161 1
2.2%
11344 1
2.2%
11451 1
2.2%
11653 1
2.2%
ValueCountFrequency (%)
18614 1
2.2%
18131 1
2.2%
17895 1
2.2%
17730 1
2.2%
17596 1
2.2%
17353 1
2.2%
17019 1
2.2%
16969 1
2.2%
16835 1
2.2%
16703 1
2.2%

소재지지번주소
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-11T06:11:24.019900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length24.5
Mean length21.217391
Min length16

Characters and Unicode

Total characters976
Distinct characters119
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

Unique46 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 가평읍 읍내리 624-1번지
2nd row경기도 고양시 일산동구 마두동 1010번지
3rd row경기도 고양시 덕양구 화정동 967-1번지
4th row경기도 고양시 일산서구 일산동 646-1번지
5th row경기도 과천시 중앙동 1-3번지
ValueCountFrequency (%)
경기도 46
 
21.6%
수원시 4
 
1.9%
성남시 3
 
1.4%
부천시 3
 
1.4%
용인시 3
 
1.4%
고양시 3
 
1.4%
안양시 2
 
0.9%
163-7번지 2
 
0.9%
평택시 2
 
0.9%
안산시 2
 
0.9%
Other values (142) 143
67.1%
2023-12-11T06:11:24.423258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
167
17.1%
지 50
 
5.1%
기 48
 
4.9%
도 47
 
4.8%
경 46
 
4.7%
번 46
 
4.7%
시 44
 
4.5%
동 43
 
4.4%
1 40
 
4.1%
- 28
 
2.9%
Other values (109) 417
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 605
62.0%
Decimal Number 176
 
18.0%
Space Separator 167
 
17.1%
Dash Punctuation 28
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 50
 
8.3%
기 48
 
7.9%
도 47
 
7.8%
경 46
 
7.6%
번 46
 
7.6%
시 44
 
7.3%
동 43
 
7.1%
구 18
 
3.0%
양 13
 
2.1%
천 12
 
2.0%
Other values (97) 238
39.3%
Decimal Number
ValueCountFrequency (%)
1 40
22.7%
6 22
12.5%
7 17
9.7%
3 16
 
9.1%
8 15
 
8.5%
5 15
 
8.5%
2 14
 
8.0%
0 14
 
8.0%
4 12
 
6.8%
9 11
 
6.2%
Space Separator
ValueCountFrequency (%)
167
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 605
62.0%
Common 371
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 50
 
8.3%
기 48
 
7.9%
도 47
 
7.8%
경 46
 
7.6%
번 46
 
7.6%
시 44
 
7.3%
동 43
 
7.1%
구 18
 
3.0%
양 13
 
2.1%
천 12
 
2.0%
Other values (97) 238
39.3%
Common
ValueCountFrequency (%)
167
45.0%
1 40
 
10.8%
- 28
 
7.5%
6 22
 
5.9%
7 17
 
4.6%
3 16
 
4.3%
8 15
 
4.0%
5 15
 
4.0%
2 14
 
3.8%
0 14
 
3.8%
Other values (2) 23
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 605
62.0%
ASCII 371
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
167
45.0%
1 40
 
10.8%
- 28
 
7.5%
6 22
 
5.9%
7 17
 
4.6%
3 16
 
4.3%
8 15
 
4.0%
5 15
 
4.0%
2 14
 
3.8%
0 14
 
3.8%
Other values (2) 23
 
6.2%
Hangul
ValueCountFrequency (%)
지 50
 
8.3%
기 48
 
7.9%
도 47
 
7.8%
경 46
 
7.6%
번 46
 
7.6%
시 44
 
7.3%
동 43
 
7.1%
구 18
 
3.0%
양 13
 
2.1%
천 12
 
2.0%
Other values (97) 238
39.3%

소재지도로명주소
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-11T06:11:24.743133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length24
Mean length19.23913
Min length14

Characters and Unicode

Total characters885
Distinct characters130
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 가평읍 가화로 155-18
2nd row경기도 고양시 일산동구 중앙로 1228
3rd row경기도 고양시 덕양구 화중로104번길 26
4th row경기도 고양시 일산서구 고양대로 688
5th row경기도 과천시 관문로 69
ValueCountFrequency (%)
경기도 46
 
21.7%
수원시 4
 
1.9%
부천시 3
 
1.4%
성남시 3
 
1.4%
고양시 3
 
1.4%
용인시 3
 
1.4%
5 2
 
0.9%
남양주시 2
 
0.9%
52 2
 
0.9%
평택시 2
 
0.9%
Other values (140) 142
67.0%
2023-12-11T06:11:25.238723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
166
18.8%
기 49
 
5.5%
경 48
 
5.4%
도 46
 
5.2%
로 45
 
5.1%
시 44
 
5.0%
1 39
 
4.4%
2 22
 
2.5%
5 21
 
2.4%
구 18
 
2.0%
Other values (120) 387
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 548
61.9%
Space Separator 166
 
18.8%
Decimal Number 164
 
18.5%
Dash Punctuation 6
 
0.7%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 49
 
8.9%
경 48
 
8.8%
도 46
 
8.4%
로 45
 
8.2%
시 44
 
8.0%
구 18
 
3.3%
길 15
 
2.7%
양 13
 
2.4%
번 12
 
2.2%
천 9
 
1.6%
Other values (107) 249
45.4%
Decimal Number
ValueCountFrequency (%)
1 39
23.8%
2 22
13.4%
5 21
12.8%
0 14
 
8.5%
4 13
 
7.9%
8 12
 
7.3%
9 12
 
7.3%
6 12
 
7.3%
3 11
 
6.7%
7 8
 
4.9%
Space Separator
ValueCountFrequency (%)
166
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 548
61.9%
Common 337
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 49
 
8.9%
경 48
 
8.8%
도 46
 
8.4%
로 45
 
8.2%
시 44
 
8.0%
구 18
 
3.3%
길 15
 
2.7%
양 13
 
2.4%
번 12
 
2.2%
천 9
 
1.6%
Other values (107) 249
45.4%
Common
ValueCountFrequency (%)
166
49.3%
1 39
 
11.6%
2 22
 
6.5%
5 21
 
6.2%
0 14
 
4.2%
4 13
 
3.9%
8 12
 
3.6%
9 12
 
3.6%
6 12
 
3.6%
3 11
 
3.3%
Other values (3) 15
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 548
61.9%
ASCII 337
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
166
49.3%
1 39
 
11.6%
2 22
 
6.5%
5 21
 
6.2%
0 14
 
4.2%
4 13
 
3.9%
8 12
 
3.6%
9 12
 
3.6%
6 12
 
3.6%
3 11
 
3.3%
Other values (3) 15
 
4.5%
Hangul
ValueCountFrequency (%)
기 49
 
8.9%
경 48
 
8.8%
도 46
 
8.4%
로 45
 
8.2%
시 44
 
8.0%
구 18
 
3.3%
길 15
 
2.7%
양 13
 
2.4%
번 12
 
2.2%
천 9
 
1.6%
Other values (107) 249
45.4%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.45434
Minimum36.996221
Maximum38.023551
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-11T06:11:25.387557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.996221
5-th percentile37.072857
Q137.296144
median37.43583
Q337.618495
95-th percentile37.849631
Maximum38.023551
Range1.0273302
Interquartile range (IQR)0.32235092

Descriptive statistics

Standard deviation0.23933684
Coefficient of variation (CV)0.0063900963
Kurtosis-0.25767451
Mean37.45434
Median Absolute Deviation (MAD)0.15769266
Skewness0.28618088
Sum1722.8997
Variance0.057282124
MonotonicityNot monotonic
2023-12-11T06:11:25.517038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
37.83348379 1
 
2.2%
37.27256447 1
 
2.2%
37.00019731 1
 
2.2%
37.38584843 1
 
2.2%
37.40478928 1
 
2.2%
37.83814511 1
 
2.2%
37.49662584 1
 
2.2%
37.29476875 1
 
2.2%
38.02355122 1
 
2.2%
37.15939316 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
36.99622103 1
2.2%
37.00019731 1
2.2%
37.06578489 1
2.2%
37.09407314 1
2.2%
37.15939316 1
2.2%
37.24115603 1
2.2%
37.25689587 1
2.2%
37.25874098 1
2.2%
37.27150183 1
2.2%
37.27256447 1
2.2%
ValueCountFrequency (%)
38.02355122 1
2.2%
37.89626288 1
2.2%
37.85346021 1
2.2%
37.83814511 1
2.2%
37.83348379 1
2.2%
37.74507962 1
2.2%
37.73553087 1
2.2%
37.7263415 1
2.2%
37.68365654 1
2.2%
37.65598192 1
2.2%

WGS84경도
Real number (ℝ)

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.04859
Minimum126.72115
Maximum127.63992
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-11T06:11:25.646055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.72115
5-th percentile126.77844
Q1126.88392
median127.05631
Q3127.15574
95-th percentile127.49196
Maximum127.63992
Range0.9187664
Interquartile range (IQR)0.27181625

Descriptive statistics

Standard deviation0.21100923
Coefficient of variation (CV)0.0016608546
Kurtosis0.60646244
Mean127.04859
Median Absolute Deviation (MAD)0.1220097
Skewness0.77164199
Sum5844.2349
Variance0.044524896
MonotonicityNot monotonic
2023-12-11T06:11:25.766867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
127.5106028 1
 
2.2%
127.1066781 1
 
2.2%
127.2698254 1
 
2.2%
126.9329501 1
 
2.2%
126.9645351 1
 
2.2%
127.068054 1
 
2.2%
127.5051587 1
 
2.2%
127.6399165 1
 
2.2%
127.0609862 1
 
2.2%
127.0778589 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
126.7211501 1
2.2%
126.7724138 1
2.2%
126.776153 1
2.2%
126.7852959 1
2.2%
126.7880124 1
2.2%
126.7960282 1
2.2%
126.805013 1
2.2%
126.8152687 1
2.2%
126.8176304 1
2.2%
126.8325306 1
2.2%
ValueCountFrequency (%)
127.6399165 1
2.2%
127.5106028 1
2.2%
127.5051587 1
2.2%
127.4523682 1
2.2%
127.3027658 1
2.2%
127.2698254 1
2.2%
127.211122 1
2.2%
127.1898416 1
2.2%
127.1857562 1
2.2%
127.1769695 1
2.2%

Interactions

2023-12-11T06:11:21.206066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:11:20.751670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:11:20.974017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:11:21.290387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:11:20.821576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:11:21.049757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:11:21.369719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:11:20.903530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:11:21.126549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:11:25.848046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명지역구분명상담센터전화번호운영방법소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
시군명1.0001.0001.0000.0000.9931.0001.0000.9730.983
지역구분명1.0001.0001.0001.0001.0001.0001.0001.0001.000
상담센터전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
운영방법0.0001.0001.0001.0000.0001.0001.0000.2070.406
소재지우편번호0.9931.0001.0000.0001.0001.0001.0000.8830.797
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
WGS84위도0.9731.0001.0000.2070.8831.0001.0001.0000.000
WGS84경도0.9831.0001.0000.4060.7971.0001.0000.0001.000
2023-12-11T06:11:25.956454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도운영방법
소재지우편번호1.000-0.9020.0990.000
WGS84위도-0.9021.000-0.1490.128
WGS84경도0.099-0.1491.0000.275
운영방법0.0000.1280.2751.000

Missing values

2023-12-11T06:11:21.468666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:11:21.590848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

시군명지역구분명상담센터전화번호운영방법소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
0가평군가평군031-580-2849직영12413경기도 가평군 가평읍 읍내리 624-1번지경기도 가평군 가평읍 가화로 155-1837.833484127.510603
1고양시고양시 일산동구031-8075-4850직영10410경기도 고양시 일산동구 마두동 1010번지경기도 고양시 일산동구 중앙로 122837.655982126.776153
2고양시고양시 덕양구031-8075-4800직영10497경기도 고양시 덕양구 화정동 967-1번지경기도 고양시 덕양구 화중로104번길 2637.635809126.832531
3고양시고양시 일산서구031-8075-4871직영10353경기도 고양시 일산서구 일산동 646-1번지경기도 고양시 일산서구 고양대로 68837.683657126.772414
4과천시과천시02-2150-3573직영13806경기도 과천시 중앙동 1-3번지경기도 과천시 관문로 6937.429495126.986637
5광명시광명시02-2680-6546직영14303경기도 광명시 하안동 230번지경기도 광명시 오리로 61337.455411126.878165
6광주시광주시031-760-2521직영12736경기도 광주시 초월읍 쌍동리 163-7번지경기도 광주시 초월읍 경충대로 1009-4037.368845127.302766
7구리시구리시031-550-8642직영11922경기도 구리시 인창동 674-3번지경기도 구리시 건원대로34번길 8437.604751127.145075
8군포시군포시031-389-4982직영15855경기도 군포시 당동 776-20번지경기도 군포시 군포로 52237.352576126.945666
9김포시김포시031-5186-4169직영10097경기도 김포시 북변동 817번지경기도 김포시 사우중로73번길 5237.623076126.72115
시군명지역구분명상담센터전화번호운영방법소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
36용인시용인시 처인구031-324-2700직영17019경기도 용인시 처인구 삼가동 556번지경기도 용인시 처인구 중부대로 119937.241156127.176969
37의왕시의왕시031-345-3851직영16076경기도 의왕시 고천동 108번지경기도 의왕시 오봉로 3437.343791126.972013
38의정부시의정부시031-870-6144직영11653경기도 의정부시 의정부동 551-1번지경기도 의정부시 범골로 12837.735531127.039642
39이천시이천시031-644-6455직영17353경기도 이천시 증포동 152-2번지경기도 이천시 증신로153번길 1337.288983127.452368
40파주시파주시031-940-3721직영10937경기도 파주시 조리읍 봉일천리 188-9번지경기도 파주시 조리읍 봉천로 6837.74508126.805013
41평택시평택시 평택031-8024-4399직영17895경기도 평택시 비전동 631번지경기도 평택시 중앙1로56번길 2536.996221127.089192
42평택시평택시 송탄031-8024-7302직영17730경기도 평택시 서정동 산12번지경기도 평택시 서정로 29537.065785127.0665
43포천시포천시031-538-4854직영11161경기도 포천시 선단동 629-1번지경기도 포천시 삼육사로2186번길 11-1537.85346127.159289
44하남시하남시031-790-6254직영12909경기도 하남시 망월동 980번지경기도 하남시 미사강변대로 20037.567641127.185756
45화성시화성시031-5189-6649직영18614경기도 화성시 향남읍 상신리 874번지경기도 화성시 향남읍 상신초교길 5237.094073126.901182