Overview

Dataset statistics

Number of variables7
Number of observations648
Missing cells354
Missing cells (%)7.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory36.8 KiB
Average record size in memory58.2 B

Variable types

Numeric2
Categorical1
Text4

Dataset

Description인천광역시 소재의 공공청사 도로명주소 현황(관할군구, 기관명, 도로명주소, 전화번호, 우편번호, 인터넷주소 ) 데이터 입니다.
Author인천광역시
URLhttps://www.data.go.kr/data/15048910/fileData.do

Alerts

연번 is highly overall correlated with 우편번호 and 1 other fieldsHigh correlation
우편번호 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
관할군구 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
인터넷주소 has 349 (53.9%) missing valuesMissing
연번 has unique valuesUnique
기 관 명 has unique valuesUnique

Reproduction

Analysis started2024-04-20 20:28:06.316925
Analysis finished2024-04-20 20:28:09.186917
Duration2.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct648
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean324.5
Minimum1
Maximum648
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-04-21T05:28:09.403760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile33.35
Q1162.75
median324.5
Q3486.25
95-th percentile615.65
Maximum648
Range647
Interquartile range (IQR)323.5

Descriptive statistics

Standard deviation187.20577
Coefficient of variation (CV)0.5769053
Kurtosis-1.2
Mean324.5
Median Absolute Deviation (MAD)162
Skewness0
Sum210276
Variance35046
MonotonicityStrictly increasing
2024-04-21T05:28:09.842627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
447 1
 
0.2%
429 1
 
0.2%
430 1
 
0.2%
431 1
 
0.2%
432 1
 
0.2%
433 1
 
0.2%
434 1
 
0.2%
435 1
 
0.2%
436 1
 
0.2%
Other values (638) 638
98.5%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
648 1
0.2%
647 1
0.2%
646 1
0.2%
645 1
0.2%
644 1
0.2%
643 1
0.2%
642 1
0.2%
641 1
0.2%
640 1
0.2%
639 1
0.2%

관할군구
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
강화군
89 
남동구
86 
부평구
71 
서구
69 
미추홀구
64 
Other values (5)
269 

Length

Max length4
Median length3
Mean length2.8425926
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강화군 89
13.7%
남동구 86
13.3%
부평구 71
11.0%
서구 69
10.6%
미추홀구 64
9.9%
연수구 63
9.7%
중구 62
9.6%
옹진군 55
8.5%
계양구 54
8.3%
동구 35
 
5.4%

Length

2024-04-21T05:28:10.252951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T05:28:10.485896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강화군 89
13.7%
남동구 86
13.3%
부평구 71
11.0%
서구 69
10.6%
미추홀구 64
9.9%
연수구 63
9.7%
중구 62
9.6%
옹진군 55
8.5%
계양구 54
8.3%
동구 35
 
5.4%

기 관 명
Text

UNIQUE 

Distinct648
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-04-21T05:28:11.140357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length13.743827
Min length5

Characters and Unicode

Total characters8906
Distinct characters255
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique648 ?
Unique (%)100.0%

Sample

1st row인천광역시 강화군청
2nd row인천광역시 강화군의회
3rd row인천광역시 강화군 강화읍사무소
4th row인천광역시 강화군보건소
5th row인천광역시 강화군 교동면사무소
ValueCountFrequency (%)
인천광역시 252
 
17.1%
행정복지센터 136
 
9.2%
강화군 33
 
2.2%
옹진군 31
 
2.1%
남동구 29
 
2.0%
부평구 27
 
1.8%
서구 24
 
1.6%
미추홀구 23
 
1.6%
인천중부경찰서 19
 
1.3%
연수구 16
 
1.1%
Other values (669) 887
60.1%
2024-04-21T05:28:12.060721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
837
 
9.4%
인 521
 
5.8%
천 520
 
5.8%
서 312
 
3.5%
동 271
 
3.0%
역 269
 
3.0%
시 267
 
3.0%
광 257
 
2.9%
구 255
 
2.9%
지 236
 
2.6%
Other values (245) 5161
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7716
86.6%
Space Separator 837
 
9.4%
Decimal Number 333
 
3.7%
Other Punctuation 7
 
0.1%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Uppercase Letter 3
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 521
 
6.8%
천 520
 
6.7%
서 312
 
4.0%
동 271
 
3.5%
역 269
 
3.5%
시 267
 
3.5%
광 257
 
3.3%
구 255
 
3.3%
지 236
 
3.1%
터 224
 
2.9%
Other values (227) 4584
59.4%
Decimal Number
ValueCountFrequency (%)
1 170
51.1%
9 65
 
19.5%
2 46
 
13.8%
3 24
 
7.2%
4 14
 
4.2%
6 6
 
1.8%
5 6
 
1.8%
7 1
 
0.3%
8 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
I 1
33.3%
T 1
33.3%
G 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
· 1
 
14.3%
Space Separator
ValueCountFrequency (%)
837
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7716
86.6%
Common 1187
 
13.3%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 521
 
6.8%
천 520
 
6.7%
서 312
 
4.0%
동 271
 
3.5%
역 269
 
3.5%
시 267
 
3.5%
광 257
 
3.3%
구 255
 
3.3%
지 236
 
3.1%
터 224
 
2.9%
Other values (227) 4584
59.4%
Common
ValueCountFrequency (%)
837
70.5%
1 170
 
14.3%
9 65
 
5.5%
2 46
 
3.9%
3 24
 
2.0%
4 14
 
1.2%
6 6
 
0.5%
5 6
 
0.5%
, 6
 
0.5%
( 4
 
0.3%
Other values (5) 9
 
0.8%
Latin
ValueCountFrequency (%)
I 1
33.3%
T 1
33.3%
G 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7716
86.6%
ASCII 1189
 
13.4%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
837
70.4%
1 170
 
14.3%
9 65
 
5.5%
2 46
 
3.9%
3 24
 
2.0%
4 14
 
1.2%
6 6
 
0.5%
5 6
 
0.5%
, 6
 
0.5%
( 4
 
0.3%
Other values (7) 11
 
0.9%
Hangul
ValueCountFrequency (%)
인 521
 
6.8%
천 520
 
6.7%
서 312
 
4.0%
동 271
 
3.5%
역 269
 
3.5%
시 267
 
3.5%
광 257
 
3.3%
구 255
 
3.3%
지 236
 
3.1%
터 224
 
2.9%
Other values (227) 4584
59.4%
None
ValueCountFrequency (%)
· 1
100.0%

도로명주소
Text

Distinct606
Distinct (%)93.7%
Missing1
Missing (%)0.2%
Memory size5.2 KiB
2024-04-21T05:28:13.256776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length32
Mean length19.823802
Min length14

Characters and Unicode

Total characters12826
Distinct characters265
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

Unique570 ?
Unique (%)88.1%

Sample

1st row인천광역시 강화군 강화읍 강화대로 394
2nd row인천광역시 강화군 강화읍 강화대로 394
3rd row인천광역시 강화군 강화읍 강화대로440번길 10
4th row인천광역시 강화군 강화읍 충렬사로 26-1
5th row인천광역시 강화군 교동면 교동동로 485-13
ValueCountFrequency (%)
인천광역시 646
23.4%
강화군 89
 
3.2%
남동구 86
 
3.1%
부평구 71
 
2.6%
서구 69
 
2.5%
미추홀구 65
 
2.4%
연수구 63
 
2.3%
중구 63
 
2.3%
계양구 54
 
2.0%
옹진군 53
 
1.9%
Other values (781) 1505
54.5%
2024-04-21T05:28:14.896372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2144
 
16.7%
인 702
 
5.5%
천 666
 
5.2%
시 657
 
5.1%
역 650
 
5.1%
광 648
 
5.1%
로 625
 
4.9%
구 515
 
4.0%
1 388
 
3.0%
2 295
 
2.3%
Other values (255) 5536
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8430
65.7%
Space Separator 2144
 
16.7%
Decimal Number 2100
 
16.4%
Dash Punctuation 65
 
0.5%
Close Punctuation 32
 
0.2%
Open Punctuation 32
 
0.2%
Other Punctuation 18
 
0.1%
Uppercase Letter 3
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 702
 
8.3%
천 666
 
7.9%
시 657
 
7.8%
역 650
 
7.7%
광 648
 
7.7%
로 625
 
7.4%
구 515
 
6.1%
길 209
 
2.5%
동 195
 
2.3%
번 177
 
2.1%
Other values (236) 3386
40.2%
Decimal Number
ValueCountFrequency (%)
1 388
18.5%
2 295
14.0%
3 219
10.4%
4 217
10.3%
7 180
8.6%
5 180
8.6%
6 180
8.6%
0 150
 
7.1%
9 147
 
7.0%
8 144
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
T 1
33.3%
C 1
33.3%
K 1
33.3%
Space Separator
ValueCountFrequency (%)
2144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8430
65.7%
Common 4393
34.3%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 702
 
8.3%
천 666
 
7.9%
시 657
 
7.8%
역 650
 
7.7%
광 648
 
7.7%
로 625
 
7.4%
구 515
 
6.1%
길 209
 
2.5%
동 195
 
2.3%
번 177
 
2.1%
Other values (236) 3386
40.2%
Common
ValueCountFrequency (%)
2144
48.8%
1 388
 
8.8%
2 295
 
6.7%
3 219
 
5.0%
4 217
 
4.9%
7 180
 
4.1%
5 180
 
4.1%
6 180
 
4.1%
0 150
 
3.4%
9 147
 
3.3%
Other values (6) 293
 
6.7%
Latin
ValueCountFrequency (%)
T 1
33.3%
C 1
33.3%
K 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8430
65.7%
ASCII 4396
34.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2144
48.8%
1 388
 
8.8%
2 295
 
6.7%
3 219
 
5.0%
4 217
 
4.9%
7 180
 
4.1%
5 180
 
4.1%
6 180
 
4.1%
0 150
 
3.4%
9 147
 
3.3%
Other values (9) 296
 
6.7%
Hangul
ValueCountFrequency (%)
인 702
 
8.3%
천 666
 
7.9%
시 657
 
7.8%
역 650
 
7.7%
광 648
 
7.7%
로 625
 
7.4%
구 515
 
6.1%
길 209
 
2.5%
동 195
 
2.3%
번 177
 
2.1%
Other values (236) 3386
40.2%

전화번호(교환)
Text

Distinct633
Distinct (%)98.0%
Missing2
Missing (%)0.3%
Memory size5.2 KiB
2024-04-21T05:28:15.952919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length11.98452
Min length7

Characters and Unicode

Total characters7742
Distinct characters24
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

Unique625 ?
Unique (%)96.7%

Sample

1st row032-930-3114
2nd row032-930-3746
3rd row032-930-4400
4th row032-930-4061
5th row032-930-4500
ValueCountFrequency (%)
032-182 5
 
0.8%
032-760-7114 3
 
0.5%
032-562-5301 3
 
0.5%
032-453-3811 2
 
0.3%
032-770-0200 2
 
0.3%
032-884-1119 2
 
0.3%
032-585-7100 2
 
0.3%
032-749-6915 2
 
0.3%
032-718-9305 1
 
0.2%
032-453-0500 1
 
0.2%
Other values (623) 623
96.4%
2024-04-21T05:28:17.339273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1433
18.5%
- 1282
16.6%
3 1137
14.7%
2 982
12.7%
5 478
 
6.2%
1 466
 
6.0%
7 409
 
5.3%
8 406
 
5.2%
4 405
 
5.2%
6 367
 
4.7%
Other values (14) 377
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6435
83.1%
Dash Punctuation 1282
 
16.6%
Other Letter 9
 
0.1%
Math Symbol 8
 
0.1%
Space Separator 6
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1433
22.3%
3 1137
17.7%
2 982
15.3%
5 478
 
7.4%
1 466
 
7.2%
7 409
 
6.4%
8 406
 
6.3%
4 405
 
6.3%
6 367
 
5.7%
9 352
 
5.5%
Other Letter
ValueCountFrequency (%)
중 1
11.1%
소 1
11.1%
기 1
11.1%
업 1
11.1%
통 1
11.1%
합 1
11.1%
콜 1
11.1%
센 1
11.1%
터 1
11.1%
Dash Punctuation
ValueCountFrequency (%)
- 1282
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7733
99.9%
Hangul 9
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1433
18.5%
- 1282
16.6%
3 1137
14.7%
2 982
12.7%
5 478
 
6.2%
1 466
 
6.0%
7 409
 
5.3%
8 406
 
5.3%
4 405
 
5.2%
6 367
 
4.7%
Other values (5) 368
 
4.8%
Hangul
ValueCountFrequency (%)
중 1
11.1%
소 1
11.1%
기 1
11.1%
업 1
11.1%
통 1
11.1%
합 1
11.1%
콜 1
11.1%
센 1
11.1%
터 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7733
99.9%
Hangul 9
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1433
18.5%
- 1282
16.6%
3 1137
14.7%
2 982
12.7%
5 478
 
6.2%
1 466
 
6.0%
7 409
 
5.3%
8 406
 
5.3%
4 405
 
5.2%
6 367
 
4.7%
Other values (5) 368
 
4.8%
Hangul
ValueCountFrequency (%)
중 1
11.1%
소 1
11.1%
기 1
11.1%
업 1
11.1%
통 1
11.1%
합 1
11.1%
콜 1
11.1%
센 1
11.1%
터 1
11.1%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct378
Distinct (%)58.5%
Missing2
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean22185.749
Minimum21007
Maximum23136
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-04-21T05:28:17.757874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21007
5-th percentile21068
Q121566.75
median22219.5
Q322784
95-th percentile23110.5
Maximum23136
Range2129
Interquartile range (IQR)1217.25

Descriptive statistics

Standard deviation665.61503
Coefficient of variation (CV)0.030001918
Kurtosis-1.241727
Mean22185.749
Median Absolute Deviation (MAD)618
Skewness-0.13456896
Sum14331994
Variance443043.37
MonotonicityNot monotonic
2024-04-21T05:28:18.185796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21066 7
 
1.1%
23031 6
 
0.9%
23018 6
 
0.9%
23130 6
 
0.9%
23019 5
 
0.8%
21589 5
 
0.8%
22371 5
 
0.8%
22372 5
 
0.8%
21007 5
 
0.8%
23101 5
 
0.8%
Other values (368) 591
91.2%
ValueCountFrequency (%)
21007 5
0.8%
21011 1
 
0.2%
21018 1
 
0.2%
21024 1
 
0.2%
21026 1
 
0.2%
21028 1
 
0.2%
21030 1
 
0.2%
21031 1
 
0.2%
21034 3
0.5%
21039 1
 
0.2%
ValueCountFrequency (%)
23136 2
 
0.3%
23135 1
 
0.2%
23133 1
 
0.2%
23132 2
 
0.3%
23130 6
0.9%
23128 3
0.5%
23127 2
 
0.3%
23125 3
0.5%
23123 1
 
0.2%
23119 4
0.6%

인터넷주소
Text

MISSING 

Distinct229
Distinct (%)76.6%
Missing349
Missing (%)53.9%
Memory size5.2 KiB
2024-04-21T05:28:18.864548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length94
Median length51
Mean length37.749164
Min length1

Characters and Unicode

Total characters11287
Distinct characters51
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique211 ?
Unique (%)70.6%

Sample

1st rowganghwa.go.kr
2nd rowcouncil.ganghwa.go.kr
3rd rowganghwa.go.kr/open_content/dong
4th rowclinic.ganghwa.go.kr
5th rowganghwa.go.kr/open_content/agriculture
ValueCountFrequency (%)
https://www.icjg.go.kr/dong/index 12
 
4.0%
http://hnrl.michu.incheon.kr 11
 
3.7%
https://www.incheon.go.kr/119/index 10
 
3.3%
https://www.icpolice.go.kr/board/rg4_board/pcontent.php?&bbs_code=jb001&bd_num=159&mcode=05:07 7
 
2.3%
yspubliclib.go.kr 7
 
2.3%
https://www.gygl.go.kr/main 7
 
2.3%
https://www.namdonglib.go.kr 5
 
1.7%
incheon.go.kr/119/index 4
 
1.3%
https://www.kcg.go.kr/inchoncgs/main.do 4
 
1.3%
icpolice.go.kr/police.phpdcode=jb 4
 
1.3%
Other values (219) 228
76.3%
2024-04-21T05:28:20.001341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 936
 
8.3%
. 926
 
8.2%
/ 921
 
8.2%
n 805
 
7.1%
g 687
 
6.1%
t 562
 
5.0%
w 549
 
4.9%
i 494
 
4.4%
p 472
 
4.2%
d 465
 
4.1%
Other values (41) 4470
39.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8536
75.6%
Other Punctuation 2172
 
19.2%
Decimal Number 344
 
3.0%
Math Symbol 133
 
1.2%
Connector Punctuation 87
 
0.8%
Uppercase Letter 13
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 936
 
11.0%
n 805
 
9.4%
g 687
 
8.0%
t 562
 
6.6%
w 549
 
6.4%
i 494
 
5.8%
p 472
 
5.5%
d 465
 
5.4%
e 425
 
5.0%
r 409
 
4.8%
Other values (15) 2732
32.0%
Decimal Number
ValueCountFrequency (%)
1 74
21.5%
0 60
17.4%
2 51
14.8%
9 38
11.0%
4 36
10.5%
5 27
 
7.8%
3 25
 
7.3%
7 16
 
4.7%
8 10
 
2.9%
6 7
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
N 3
23.1%
G 2
15.4%
P 2
15.4%
I 2
15.4%
S 2
15.4%
C 1
 
7.7%
E 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
. 926
42.6%
/ 921
42.4%
: 209
 
9.6%
? 91
 
4.2%
& 24
 
1.1%
# 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
= 133
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 87
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8549
75.7%
Common 2738
 
24.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 936
 
10.9%
n 805
 
9.4%
g 687
 
8.0%
t 562
 
6.6%
w 549
 
6.4%
i 494
 
5.8%
p 472
 
5.5%
d 465
 
5.4%
e 425
 
5.0%
r 409
 
4.8%
Other values (22) 2745
32.1%
Common
ValueCountFrequency (%)
. 926
33.8%
/ 921
33.6%
: 209
 
7.6%
= 133
 
4.9%
? 91
 
3.3%
_ 87
 
3.2%
1 74
 
2.7%
0 60
 
2.2%
2 51
 
1.9%
9 38
 
1.4%
Other values (9) 148
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11287
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 936
 
8.3%
. 926
 
8.2%
/ 921
 
8.2%
n 805
 
7.1%
g 687
 
6.1%
t 562
 
5.0%
w 549
 
4.9%
i 494
 
4.4%
p 472
 
4.2%
d 465
 
4.1%
Other values (41) 4470
39.6%

Interactions

2024-04-21T05:28:07.498508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T05:28:06.988204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T05:28:07.753417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T05:28:07.245802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T05:28:20.245217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관할군구우편번호
연번1.0000.9910.981
관할군구0.9911.0000.997
우편번호0.9810.9971.000
2024-04-21T05:28:20.484712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호관할군구
연번1.000-0.6300.829
우편번호-0.6301.0000.894
관할군구0.8290.8941.000

Missing values

2024-04-21T05:28:08.296451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T05:28:08.708550image/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.
2024-04-21T05:28:09.024159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번관할군구기 관 명도로명주소전화번호(교환)우편번호인터넷주소
01강화군인천광역시 강화군청인천광역시 강화군 강화읍 강화대로 394032-930-311423031ganghwa.go.kr
12강화군인천광역시 강화군의회인천광역시 강화군 강화읍 강화대로 394032-930-374623031council.ganghwa.go.kr
23강화군인천광역시 강화군 강화읍사무소인천광역시 강화군 강화읍 강화대로440번길 10032-930-440023032ganghwa.go.kr/open_content/dong
34강화군인천광역시 강화군보건소인천광역시 강화군 강화읍 충렬사로 26-1032-930-406123037clinic.ganghwa.go.kr
45강화군인천광역시 강화군 교동면사무소인천광역시 강화군 교동면 교동동로 485-13032-930-450023002<NA>
56강화군인천광역시 강화군 교동보건지소인천광역시 강화군 교동면 교동동로 485-13032-932-880823002<NA>
67강화군인천광역시 강화군 정원관리사업소(화개정원)인천광역시 강화군 교동면 교동동로471번길 6-62032-932-233623001<NA>
78강화군인천광역시 강화군 길상면사무소인천광역시 강화군 길상면 마니산로 21032-930-443023050<NA>
89강화군인천광역시 강화군 길상보건지소인천광역시 강화군 길상면 강화동로 15-1032-937-021223050<NA>
910강화군인천광역시 강화군 내가면사무소인천광역시 강화군 내가면 강화서로 249032-930-446023018<NA>
연번관할군구기 관 명도로명주소전화번호(교환)우편번호인터넷주소
638639서구인천서부소방서 신현119안전센터인천광역시 서구 가정로 333-1032-572-011922782<NA>
639640서구인천서부소방서 석남119안전센터인천광역시 서구 석남로 102032-571-011922796<NA>
640641서구인천서부소방서 가좌119안전센터인천광역시 서구 백범로678번길 17032-578-011922825<NA>
641642서구인천서부소방서 청라119안전센터인천광역시 서구 청라한내로 77032-569-502622758<NA>
642643서구인천서부소방서 원당119안전센터인천광역시 서구 원당대로 881032-563-119522624<NA>
643644서구인천서부소방서 검단119안전센터인천광역시 서구 완정로 191032-565-011922616<NA>
644645서구인천서부소방서 오류119안전센터인천광역시 서구 대촌로 6032-566-111822656<NA>
645646서구인천서부소방서 정서진119수난구조대인천광역시 서구 정서진로 623032-568-367222694<NA>
646647서구인천검단소방서인천광역시 서구 원당대로 736032-562-011922679<NA>
647648서구정다운도서관인천광역시 서구 서곶로314번길 16032-562-120222714<NA>