Overview

Dataset statistics

Number of variables9
Number of observations866
Missing cells3
Missing cells (%)< 0.1%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory63.6 KiB
Average record size in memory75.2 B

Variable types

DateTime1
Categorical1
Text4
Numeric3

Dataset

Description경기도 청사 및 출장소 현황
Author가평군
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=4S17FIR05U0L2SOW82B712842838&infSeq=1

Alerts

Dataset has 1 (0.1%) duplicate rowsDuplicates
소재지우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation

Reproduction

Analysis started2024-03-23 01:16:33.036451
Analysis finished2024-03-23 01:16:37.921550
Duration4.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계일자
Date

Distinct25
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
Minimum2015-09-18 00:00:00
Maximum2024-03-14 00:00:00
2024-03-23T01:16:38.129112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:16:38.741884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
연천군
65 
수원시
63 
양평군
58 
성남시
 
52
화성시
 
51
Other values (26)
577 

Length

Max length4
Median length3
Mean length3.0969977
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연천군 65
 
7.5%
수원시 63
 
7.3%
양평군 58
 
6.7%
성남시 52
 
6.0%
화성시 51
 
5.9%
고양시 48
 
5.5%
양주시 47
 
5.4%
부천시 40
 
4.6%
용인시 35
 
4.0%
동두천시 35
 
4.0%
Other values (21) 372
43.0%

Length

2024-03-23T01:16:39.163057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연천군 65
 
7.5%
수원시 63
 
7.3%
양평군 58
 
6.7%
성남시 52
 
6.0%
화성시 51
 
5.9%
고양시 48
 
5.5%
양주시 47
 
5.4%
부천시 40
 
4.6%
용인시 35
 
4.0%
동두천시 35
 
4.0%
Other values (21) 372
43.0%

구분명
Text

Distinct839
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
2024-03-23T01:16:39.946048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length6.2667436
Min length2

Characters and Unicode

Total characters5427
Distinct characters274
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

Unique822 ?
Unique (%)94.9%

Sample

1st row평내동
2nd row다산 행정복지센터
3rd row다산2동
4th row호평평내 행정복지센터
5th row별내면
ValueCountFrequency (%)
행정복지센터 112
 
11.1%
수원시 12
 
1.2%
주민센터 10
 
1.0%
농업기술센터 6
 
0.6%
보건소 6
 
0.6%
중앙동 5
 
0.5%
과천시 4
 
0.4%
차량등록사업소 3
 
0.3%
환경사업소 3
 
0.3%
의정부시청 3
 
0.3%
Other values (822) 847
83.8%
2024-03-23T01:16:41.244961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 489
 
9.0%
정 273
 
5.0%
센 256
 
4.7%
터 256
 
4.7%
지 255
 
4.7%
행 230
 
4.2%
복 224
 
4.1%
145
 
2.7%
소 117
 
2.2%
면 104
 
1.9%
Other values (264) 3078
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4981
91.8%
Decimal Number 255
 
4.7%
Space Separator 145
 
2.7%
Close Punctuation 15
 
0.3%
Open Punctuation 15
 
0.3%
Dash Punctuation 9
 
0.2%
Uppercase Letter 6
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 489
 
9.8%
정 273
 
5.5%
센 256
 
5.1%
터 256
 
5.1%
지 255
 
5.1%
행 230
 
4.6%
복 224
 
4.5%
소 117
 
2.3%
면 104
 
2.1%
시 83
 
1.7%
Other values (245) 2694
54.1%
Decimal Number
ValueCountFrequency (%)
1 101
39.6%
2 85
33.3%
3 35
 
13.7%
4 12
 
4.7%
9 9
 
3.5%
5 4
 
1.6%
6 4
 
1.6%
7 3
 
1.2%
8 2
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
C 2
33.3%
T 1
16.7%
V 1
16.7%
E 1
16.7%
M 1
16.7%
Space Separator
ValueCountFrequency (%)
145
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4981
91.8%
Common 440
 
8.1%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 489
 
9.8%
정 273
 
5.5%
센 256
 
5.1%
터 256
 
5.1%
지 255
 
5.1%
행 230
 
4.6%
복 224
 
4.5%
소 117
 
2.3%
면 104
 
2.1%
시 83
 
1.7%
Other values (245) 2694
54.1%
Common
ValueCountFrequency (%)
145
33.0%
1 101
23.0%
2 85
19.3%
3 35
 
8.0%
) 15
 
3.4%
( 15
 
3.4%
4 12
 
2.7%
9 9
 
2.0%
- 9
 
2.0%
5 4
 
0.9%
Other values (4) 10
 
2.3%
Latin
ValueCountFrequency (%)
C 2
33.3%
T 1
16.7%
V 1
16.7%
E 1
16.7%
M 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4981
91.8%
ASCII 446
 
8.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 489
 
9.8%
정 273
 
5.5%
센 256
 
5.1%
터 256
 
5.1%
지 255
 
5.1%
행 230
 
4.6%
복 224
 
4.5%
소 117
 
2.3%
면 104
 
2.1%
시 83
 
1.7%
Other values (245) 2694
54.1%
ASCII
ValueCountFrequency (%)
145
32.5%
1 101
22.6%
2 85
19.1%
3 35
 
7.8%
) 15
 
3.4%
( 15
 
3.4%
4 12
 
2.7%
9 9
 
2.0%
- 9
 
2.0%
5 4
 
0.9%
Other values (9) 16
 
3.6%

전화번호안내
Text

Distinct802
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
2024-03-23T01:16:42.049505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length12.278291
Min length7

Characters and Unicode

Total characters10633
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique791 ?
Unique (%)91.3%

Sample

1st row031-590-2652
2nd row031-590-2656
3rd row031-590-4972
4th row031-590-8061
5th row031-590-2606
ValueCountFrequency (%)
032-320-3000 40
 
4.6%
031-1899-3300 9
 
1.0%
031-5189-2222 8
 
0.9%
031-909-9000 4
 
0.5%
031-860-3330 2
 
0.2%
031-980-5011 2
 
0.2%
031-860-3281 2
 
0.2%
031-590-2114 2
 
0.2%
031-860-2102 2
 
0.2%
031-8036-8036 2
 
0.2%
Other values (792) 793
91.6%
2024-03-23T01:16:43.259421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1999
18.8%
- 1738
16.3%
3 1427
13.4%
1 1308
12.3%
8 821
7.7%
2 748
 
7.0%
7 606
 
5.7%
6 555
 
5.2%
5 536
 
5.0%
4 490
 
4.6%
Other values (2) 405
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8879
83.5%
Dash Punctuation 1738
 
16.3%
Math Symbol 16
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1999
22.5%
3 1427
16.1%
1 1308
14.7%
8 821
9.2%
2 748
 
8.4%
7 606
 
6.8%
6 555
 
6.3%
5 536
 
6.0%
4 490
 
5.5%
9 389
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 1738
100.0%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10633
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1999
18.8%
- 1738
16.3%
3 1427
13.4%
1 1308
12.3%
8 821
7.7%
2 748
 
7.0%
7 606
 
5.7%
6 555
 
5.2%
5 536
 
5.0%
4 490
 
4.6%
Other values (2) 405
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10633
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1999
18.8%
- 1738
16.3%
3 1427
13.4%
1 1308
12.3%
8 821
7.7%
2 748
 
7.0%
7 606
 
5.7%
6 555
 
5.2%
5 536
 
5.0%
4 490
 
4.6%
Other values (2) 405
 
3.8%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct741
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75446.582
Minimum3307
Maximum471858
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2024-03-23T01:16:43.775665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3307
5-th percentile10356.5
Q111419
median13927.5
Q316690.5
95-th percentile462059
Maximum471858
Range468551
Interquartile range (IQR)5271.5

Descriptive statistics

Standard deviation153939.13
Coefficient of variation (CV)2.0403724
Kurtosis2.3483135
Mean75446.582
Median Absolute Deviation (MAD)2590
Skewness2.0826788
Sum65336740
Variance2.3697255 × 1010
MonotonicityNot monotonic
2024-03-23T01:16:44.232257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11013 8
 
0.9%
11000 6
 
0.7%
11006 5
 
0.6%
11048 5
 
0.6%
11044 5
 
0.6%
11419 4
 
0.5%
11023 4
 
0.5%
18588 4
 
0.5%
12584 3
 
0.3%
11340 3
 
0.3%
Other values (731) 819
94.6%
ValueCountFrequency (%)
3307 1
0.1%
10011 1
0.1%
10016 1
0.1%
10019 1
0.1%
10024 1
0.1%
10025 1
0.1%
10040 1
0.1%
10056 1
0.1%
10057 1
0.1%
10066 1
0.1%
ValueCountFrequency (%)
471858 1
0.1%
471702 1
0.1%
471033 1
0.1%
471032 1
0.1%
471031 1
0.1%
471022 1
0.1%
471021 1
0.1%
471010 2
0.2%
463895 1
0.1%
463864 1
0.1%

소재지도로명주소
Text

Distinct836
Distinct (%)96.9%
Missing3
Missing (%)0.3%
Memory size6.9 KiB
2024-03-23T01:16:45.035417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length30
Mean length21.256083
Min length13

Characters and Unicode

Total characters18344
Distinct characters327
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

Unique812 ?
Unique (%)94.1%

Sample

1st row경기도 남양주시 경춘로 1286
2nd row경기도 남양주시 다산중앙로 7
3rd row경기도 남양주시 다산지금로16번길 75
4th row경기도 남양주시 호평로68번길 21
5th row경기도 남양주시 별내면 청학로8번길 22
ValueCountFrequency (%)
경기도 863
 
19.9%
연천군 65
 
1.5%
수원시 63
 
1.5%
양평군 58
 
1.3%
화성시 51
 
1.2%
성남시 51
 
1.2%
고양시 47
 
1.1%
양주시 47
 
1.1%
부천시 40
 
0.9%
동두천시 35
 
0.8%
Other values (1460) 3007
69.5%
2024-03-23T01:16:46.183378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3464
 
18.9%
기 889
 
4.8%
경 887
 
4.8%
도 887
 
4.8%
로 778
 
4.2%
시 773
 
4.2%
1 578
 
3.2%
동 417
 
2.3%
2 386
 
2.1%
구 320
 
1.7%
Other values (317) 8965
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11377
62.0%
Space Separator 3464
 
18.9%
Decimal Number 2775
 
15.1%
Close Punctuation 317
 
1.7%
Open Punctuation 317
 
1.7%
Dash Punctuation 81
 
0.4%
Other Punctuation 9
 
< 0.1%
Math Symbol 2
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 889
 
7.8%
경 887
 
7.8%
도 887
 
7.8%
로 778
 
6.8%
시 773
 
6.8%
동 417
 
3.7%
구 320
 
2.8%
양 313
 
2.8%
길 299
 
2.6%
천 250
 
2.2%
Other values (298) 5564
48.9%
Decimal Number
ValueCountFrequency (%)
1 578
20.8%
2 386
13.9%
3 305
11.0%
4 252
9.1%
5 232
8.4%
7 226
 
8.1%
6 226
 
8.1%
0 202
 
7.3%
9 195
 
7.0%
8 173
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 8
88.9%
. 1
 
11.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
3464
100.0%
Close Punctuation
ValueCountFrequency (%)
) 317
100.0%
Open Punctuation
ValueCountFrequency (%)
( 317
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11377
62.0%
Common 6965
38.0%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 889
 
7.8%
경 887
 
7.8%
도 887
 
7.8%
로 778
 
6.8%
시 773
 
6.8%
동 417
 
3.7%
구 320
 
2.8%
양 313
 
2.8%
길 299
 
2.6%
천 250
 
2.2%
Other values (298) 5564
48.9%
Common
ValueCountFrequency (%)
3464
49.7%
1 578
 
8.3%
2 386
 
5.5%
) 317
 
4.6%
( 317
 
4.6%
3 305
 
4.4%
4 252
 
3.6%
5 232
 
3.3%
7 226
 
3.2%
6 226
 
3.2%
Other values (7) 662
 
9.5%
Latin
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11377
62.0%
ASCII 6967
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3464
49.7%
1 578
 
8.3%
2 386
 
5.5%
) 317
 
4.6%
( 317
 
4.6%
3 305
 
4.4%
4 252
 
3.6%
5 232
 
3.3%
7 226
 
3.2%
6 226
 
3.2%
Other values (9) 664
 
9.5%
Hangul
ValueCountFrequency (%)
기 889
 
7.8%
경 887
 
7.8%
도 887
 
7.8%
로 778
 
6.8%
시 773
 
6.8%
동 417
 
3.7%
구 320
 
2.8%
양 313
 
2.8%
길 299
 
2.6%
천 250
 
2.2%
Other values (298) 5564
48.9%

소재지지번주소
Text

Distinct841
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
2024-03-23T01:16:46.962913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length27
Mean length20.267898
Min length13

Characters and Unicode

Total characters17552
Distinct characters251
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique819 ?
Unique (%)94.6%

Sample

1st row경기도 남양주시 평내동 588-2번지
2nd row경기도 남양주시 다산동 6150번지
3rd row경기도 남양주시 다산동 3065번지
4th row경기도 남양주시 호평동 669번지
5th row경기도 남양주시 별내면 광전리 122-6번지
ValueCountFrequency (%)
경기도 863
 
21.7%
연천군 65
 
1.6%
수원시 63
 
1.6%
양평군 58
 
1.5%
성남시 52
 
1.3%
화성시 51
 
1.3%
양주시 47
 
1.2%
고양시 47
 
1.2%
부천시 40
 
1.0%
용인시 35
 
0.9%
Other values (1482) 2654
66.8%
2024-03-23T01:16:48.184468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3115
 
17.7%
도 884
 
5.0%
기 882
 
5.0%
경 864
 
4.9%
시 756
 
4.3%
동 684
 
3.9%
1 632
 
3.6%
- 587
 
3.3%
지 539
 
3.1%
번 496
 
2.8%
Other values (241) 8113
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10529
60.0%
Decimal Number 3312
 
18.9%
Space Separator 3115
 
17.7%
Dash Punctuation 587
 
3.3%
Close Punctuation 4
 
< 0.1%
Open Punctuation 4
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 884
 
8.4%
기 882
 
8.4%
경 864
 
8.2%
시 756
 
7.2%
동 684
 
6.5%
지 539
 
5.1%
번 496
 
4.7%
양 305
 
2.9%
리 291
 
2.8%
구 278
 
2.6%
Other values (226) 4550
43.2%
Decimal Number
ValueCountFrequency (%)
1 632
19.1%
2 438
13.2%
3 375
11.3%
4 314
9.5%
5 301
9.1%
7 279
8.4%
6 278
8.4%
8 262
7.9%
0 228
 
6.9%
9 205
 
6.2%
Space Separator
ValueCountFrequency (%)
3115
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 587
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10529
60.0%
Common 7023
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 884
 
8.4%
기 882
 
8.4%
경 864
 
8.2%
시 756
 
7.2%
동 684
 
6.5%
지 539
 
5.1%
번 496
 
4.7%
양 305
 
2.9%
리 291
 
2.8%
구 278
 
2.6%
Other values (226) 4550
43.2%
Common
ValueCountFrequency (%)
3115
44.4%
1 632
 
9.0%
- 587
 
8.4%
2 438
 
6.2%
3 375
 
5.3%
4 314
 
4.5%
5 301
 
4.3%
7 279
 
4.0%
6 278
 
4.0%
8 262
 
3.7%
Other values (5) 442
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10529
60.0%
ASCII 7023
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3115
44.4%
1 632
 
9.0%
- 587
 
8.4%
2 438
 
6.2%
3 375
 
5.3%
4 314
 
4.5%
5 301
 
4.3%
7 279
 
4.0%
6 278
 
4.0%
8 262
 
3.7%
Other values (5) 442
 
6.3%
Hangul
ValueCountFrequency (%)
도 884
 
8.4%
기 882
 
8.4%
경 864
 
8.2%
시 756
 
7.2%
동 684
 
6.5%
지 539
 
5.1%
번 496
 
4.7%
양 305
 
2.9%
리 291
 
2.8%
구 278
 
2.6%
Other values (226) 4550
43.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct844
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.517131
Minimum36.943305
Maximum38.184783
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2024-03-23T01:16:48.613584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.943305
5-th percentile37.095925
Q137.305319
median37.469997
Q337.717144
95-th percentile38.031464
Maximum38.184783
Range1.2414784
Interquartile range (IQR)0.4118254

Descriptive statistics

Standard deviation0.27765823
Coefficient of variation (CV)0.0074008385
Kurtosis-0.54770377
Mean37.517131
Median Absolute Deviation (MAD)0.18724916
Skewness0.38670705
Sum32489.835
Variance0.077094091
MonotonicityNot monotonic
2024-03-23T01:16:49.056619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.1374720666 4
 
0.5%
37.89661147 3
 
0.3%
38.1830174044 2
 
0.2%
37.90341068 2
 
0.2%
37.30402833 2
 
0.2%
37.429812 2
 
0.2%
37.94229789 2
 
0.2%
37.89215013 2
 
0.2%
37.89088078 2
 
0.2%
38.1082239071 2
 
0.2%
Other values (834) 843
97.3%
ValueCountFrequency (%)
36.9433047732 1
0.1%
36.9651751 1
0.1%
36.9673461 1
0.1%
36.9752522325 1
0.1%
36.9825921 1
0.1%
36.9860335 1
0.1%
36.9892772 1
0.1%
36.9900397 1
0.1%
36.9901355 1
0.1%
36.990308 1
0.1%
ValueCountFrequency (%)
38.1847831469 1
0.1%
38.1846953717 1
0.1%
38.18302858 1
0.1%
38.1830174044 2
0.2%
38.1829428939 1
0.1%
38.1577316 1
0.1%
38.1358246086 1
0.1%
38.1353790792 1
0.1%
38.1105837722 2
0.2%
38.1088211469 1
0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct843
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.05321
Minimum126.55271
Maximum127.77069
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2024-03-23T01:16:49.512184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55271
5-th percentile126.751
Q1126.90393
median127.04676
Q3127.13489
95-th percentile127.53594
Maximum127.77069
Range1.2179708
Interquartile range (IQR)0.23096139

Descriptive statistics

Standard deviation0.22816989
Coefficient of variation (CV)0.0017958609
Kurtosis0.919787
Mean127.05321
Median Absolute Deviation (MAD)0.1167045
Skewness0.86951221
Sum110028.08
Variance0.052061499
MonotonicityNot monotonic
2024-03-23T01:16:49.939986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9240117072 4
 
0.5%
127.0517171 3
 
0.3%
127.0514001 2
 
0.2%
127.0968603028 2
 
0.2%
127.054489 2
 
0.2%
127.4876821 2
 
0.2%
127.0532318 2
 
0.2%
127.0615412 2
 
0.2%
126.986963 2
 
0.2%
127.0766731147 2
 
0.2%
Other values (833) 843
97.3%
ValueCountFrequency (%)
126.5527148 1
0.1%
126.5561377 1
0.1%
126.582541 1
0.1%
126.585215 1
0.1%
126.5920603 1
0.1%
126.596332 1
0.1%
126.6236784 1
0.1%
126.6254299 1
0.1%
126.6313345 1
0.1%
126.6314373 1
0.1%
ValueCountFrequency (%)
127.7706856 1
0.1%
127.770574 1
0.1%
127.764329 1
0.1%
127.761545 1
0.1%
127.754679 1
0.1%
127.751177 1
0.1%
127.750923 1
0.1%
127.736187 1
0.1%
127.713562 1
0.1%
127.7110756 1
0.1%

Interactions

2024-03-23T01:16:36.353918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:16:34.460187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:16:35.468264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:16:36.619824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:16:34.876642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:16:35.777986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:16:36.925499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:16:35.186208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:16:36.073641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T01:16:50.200776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
집계일자시군명소재지우편번호WGS84위도WGS84경도
집계일자1.0000.9990.8490.9200.904
시군명0.9991.0000.8780.9590.914
소재지우편번호0.8490.8781.0000.4000.456
WGS84위도0.9200.9590.4001.0000.585
WGS84경도0.9040.9140.4560.5851.000
2024-03-23T01:16:50.473532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명
소재지우편번호1.000-0.8250.2230.695
WGS84위도-0.8251.000-0.0590.756
WGS84경도0.223-0.0591.0000.623
시군명0.6950.7560.6231.000

Missing values

2024-03-23T01:16:37.310182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T01:16:37.766909image/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

집계일자시군명구분명전화번호안내소재지우편번호소재지도로명주소소재지지번주소WGS84위도WGS84경도
02024-03-14남양주시평내동031-590-265212223경기도 남양주시 경춘로 1286경기도 남양주시 평내동 588-2번지37.648389127.236076
12024-03-14남양주시다산 행정복지센터031-590-265612248경기도 남양주시 다산중앙로 7경기도 남양주시 다산동 6150번지37.613922127.155535
22024-03-14남양주시다산2동031-590-497212284경기도 남양주시 다산지금로16번길 75경기도 남양주시 다산동 3065번지37.607643127.169511
32024-03-14남양주시호평평내 행정복지센터031-590-806112151경기도 남양주시 호평로68번길 21경기도 남양주시 호평동 669번지37.654888127.248649
42024-03-14남양주시별내면031-590-260612090경기도 남양주시 별내면 청학로8번길 22경기도 남양주시 별내면 광전리 122-6번지37.7027127.12487
52024-03-14남양주시별내 행정복지센터031-590-849112112경기도 남양주시 별내3로 64-21경기도 남양주시 별내동 1028번지37.646159127.121878
62024-03-14남양주시동부출장소031-590-861412190경기도 남양주시 화도읍 경춘로2192번길 8-11경기도 남양주시 화도읍 월산리 371-237.653296127.331253
72024-03-14남양주시조안면031-590-260912282경기도 남양주시 조안면 북한강로 120경기도 남양주시 조안면 조안리 173-3번지37.535888127.303447
82024-03-14남양주시오남읍031-590-261512036경기도 남양주시 오남읍 진건오남로 806-34경기도 남양주시 오남읍 양지리 96-10번지37.698574127.20484
92024-03-14남양주시수동면031-590-260812031경기도 남양주시 수동면 비룡로 729경기도 남양주시 수동면 운수리 95-2번지37.703619127.325921
집계일자시군명구분명전화번호안내소재지우편번호소재지도로명주소소재지지번주소WGS84위도WGS84경도
8562015-09-18평택시평택시청031-8024-5000450702경기도 평택시 경기대로 245 (비전동)경기도 평택시 비전동 846번지36.9923127.112527
8572015-09-18평택시안중읍031-8024-8510451880경기도 평택시 안중읍 안현로 400 (안중리)경기도 평택시 안중읍 안중리 445-16번지36.986033126.931316
8582015-09-18평택시원평동031-8024-5710450040경기도 평택시 원평2로 9 (통복동)경기도 평택시 통복동 172-6번지36.989277127.080495
8592015-09-18평택시송북동031-8024-7070459110경기도 평택시 지산2로 113 (지산동)경기도 평택시 지산동 1011번지37.08165127.060232
8602015-09-18평택시송탄동031-8024-6990459060경기도 평택시 방여울로 117 (가재동)경기도 평택시 가재동 20-53번지37.044427127.094847
8612015-09-18평택시중앙동031-8024-6910459812경기도 평택시 서정역로 16 (서정동)경기도 평택시 서정동 342번지37.05556127.056056
8622015-09-18평택시청북면031-8024-8860451831경기도 평택시 청북읍 청원로 2 (현곡리)경기도 평택시 청북읍 현곡리 293-4번지37.039808126.934257
8632015-09-18평택시진위면031-8024-6712451864경기도 평택시 진위면 봉남길 61 (봉남리)경기도 평택시 진위면 봉남리 229번지37.100116127.090894
8642015-09-18평택시서탄면031-8024-6780451852경기도 평택시 서탄면 금암2길 122 (금암리)경기도 평택시 서탄면 금암리 247번지37.108241127.035331
8652015-09-18평택시고덕면031-8024-6840451842경기도 평택시 고덕면 고덕로 283 (좌교리)경기도 평택시 고덕면 좌교리 387-25번지37.042333127.017756

Duplicate rows

Most frequently occurring

집계일자시군명구분명전화번호안내소재지우편번호소재지도로명주소소재지지번주소WGS84위도WGS84경도# duplicates
02021-12-01동두천시꿈나무정보도서관031-860-328111349경기도 동두천시 지행로 38경기도 동두천시 지행동 717-437.89215127.05142