Overview

Dataset statistics

Number of variables7
Number of observations630
Missing cells343
Missing cells (%)7.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.8 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://data.incheon.go.kr/findData/publicDataDetail?dataId=15048910&srcSe=7661IVAWM27C61E190

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 342 (54.3%) missing valuesMissing
연번 has unique valuesUnique
기 관 명 has unique valuesUnique

Reproduction

Analysis started2024-01-28 06:18:23.381132
Analysis finished2024-01-28 06:18:24.280679
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct630
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean315.5
Minimum1
Maximum630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-01-28T15:18:24.344616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile32.45
Q1158.25
median315.5
Q3472.75
95-th percentile598.55
Maximum630
Range629
Interquartile range (IQR)314.5

Descriptive statistics

Standard deviation182.00962
Coefficient of variation (CV)0.5768926
Kurtosis-1.2
Mean315.5
Median Absolute Deviation (MAD)157.5
Skewness0
Sum198765
Variance33127.5
MonotonicityStrictly increasing
2024-01-28T15:18:24.463951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
425 1
 
0.2%
418 1
 
0.2%
419 1
 
0.2%
420 1
 
0.2%
421 1
 
0.2%
422 1
 
0.2%
423 1
 
0.2%
424 1
 
0.2%
426 1
 
0.2%
Other values (620) 620
98.4%
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 (%)
630 1
0.2%
629 1
0.2%
628 1
0.2%
627 1
0.2%
626 1
0.2%
625 1
0.2%
624 1
0.2%
623 1
0.2%
622 1
0.2%
621 1
0.2%

관할군구
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
강화군
89 
남동구
71 
부평구
71 
서구
68 
미추홀구
64 
Other values (5)
267 

Length

Max length4
Median length3
Mean length2.8412698
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강화군 89
14.1%
남동구 71
11.3%
부평구 71
11.3%
서구 68
10.8%
미추홀구 64
10.2%
연수구 63
10.0%
중구 61
9.7%
옹진군 55
8.7%
계양구 53
8.4%
동구 35
 
5.6%

Length

2024-01-28T15:18:24.577165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T15:18:24.683834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강화군 89
14.1%
남동구 71
11.3%
부평구 71
11.3%
서구 68
10.8%
미추홀구 64
10.2%
연수구 63
10.0%
중구 61
9.7%
옹진군 55
8.7%
계양구 53
8.4%
동구 35
 
5.6%

기 관 명
Text

UNIQUE 

Distinct630
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-01-28T15:18:24.855176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length13.822222
Min length5

Characters and Unicode

Total characters8708
Distinct characters249
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

Unique630 ?
Unique (%)100.0%

Sample

1st row인천광역시 강화군청
2nd row인천광역시 강화군의회
3rd row인천광역시 강화군 강화읍사무소
4th row인천광역시 강화군보건소
5th row인천광역시 강화군 교동면사무소
ValueCountFrequency (%)
인천광역시 249
 
17.3%
행정복지센터 135
 
9.4%
강화군 33
 
2.3%
옹진군 31
 
2.2%
부평구 27
 
1.9%
서구 24
 
1.7%
미추홀구 23
 
1.6%
남동구 22
 
1.5%
인천중부경찰서 19
 
1.3%
연수구 16
 
1.1%
Other values (651) 862
59.8%
2024-01-28T15:18:25.108501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
819
 
9.4%
인 517
 
5.9%
천 517
 
5.9%
서 310
 
3.6%
역 265
 
3.0%
시 263
 
3.0%
동 261
 
3.0%
광 254
 
2.9%
구 247
 
2.8%
지 226
 
2.6%
Other values (239) 5029
57.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7538
86.6%
Space Separator 819
 
9.4%
Decimal Number 332
 
3.8%
Other Punctuation 6
 
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 517
 
6.9%
천 517
 
6.9%
서 310
 
4.1%
역 265
 
3.5%
시 263
 
3.5%
동 261
 
3.5%
광 254
 
3.4%
구 247
 
3.3%
지 226
 
3.0%
센 219
 
2.9%
Other values (222) 4459
59.2%
Decimal Number
ValueCountFrequency (%)
1 170
51.2%
9 65
 
19.6%
2 45
 
13.6%
3 24
 
7.2%
4 14
 
4.2%
5 6
 
1.8%
6 6
 
1.8%
7 1
 
0.3%
8 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
T 1
33.3%
I 1
33.3%
G 1
33.3%
Space Separator
ValueCountFrequency (%)
819
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
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 7538
86.6%
Common 1167
 
13.4%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 517
 
6.9%
천 517
 
6.9%
서 310
 
4.1%
역 265
 
3.5%
시 263
 
3.5%
동 261
 
3.5%
광 254
 
3.4%
구 247
 
3.3%
지 226
 
3.0%
센 219
 
2.9%
Other values (222) 4459
59.2%
Common
ValueCountFrequency (%)
819
70.2%
1 170
 
14.6%
9 65
 
5.6%
2 45
 
3.9%
3 24
 
2.1%
4 14
 
1.2%
5 6
 
0.5%
, 6
 
0.5%
6 6
 
0.5%
( 4
 
0.3%
Other values (4) 8
 
0.7%
Latin
ValueCountFrequency (%)
T 1
33.3%
I 1
33.3%
G 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7538
86.6%
ASCII 1170
 
13.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
819
70.0%
1 170
 
14.5%
9 65
 
5.6%
2 45
 
3.8%
3 24
 
2.1%
4 14
 
1.2%
5 6
 
0.5%
, 6
 
0.5%
6 6
 
0.5%
( 4
 
0.3%
Other values (7) 11
 
0.9%
Hangul
ValueCountFrequency (%)
인 517
 
6.9%
천 517
 
6.9%
서 310
 
4.1%
역 265
 
3.5%
시 263
 
3.5%
동 261
 
3.5%
광 254
 
3.4%
구 247
 
3.3%
지 226
 
3.0%
센 219
 
2.9%
Other values (222) 4459
59.2%

도로명주소
Text

Distinct589
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-01-28T15:18:25.371117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length32
Mean length19.719048
Min length14

Characters and Unicode

Total characters12423
Distinct characters257
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

Unique553 ?
Unique (%)87.8%

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 630
23.5%
강화군 89
 
3.3%
남동구 71
 
2.6%
부평구 71
 
2.6%
서구 68
 
2.5%
미추홀구 65
 
2.4%
연수구 63
 
2.3%
중구 62
 
2.3%
계양구 53
 
2.0%
옹진군 53
 
2.0%
Other values (750) 1458
54.3%
2024-01-28T15:18:25.750280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2078
 
16.7%
인 685
 
5.5%
천 649
 
5.2%
시 640
 
5.2%
역 634
 
5.1%
광 632
 
5.1%
로 608
 
4.9%
구 497
 
4.0%
1 376
 
3.0%
2 285
 
2.3%
Other values (247) 5339
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8172
65.8%
Space Separator 2078
 
16.7%
Decimal Number 2034
 
16.4%
Dash Punctuation 66
 
0.5%
Close Punctuation 29
 
0.2%
Open Punctuation 29
 
0.2%
Other Punctuation 11
 
0.1%
Uppercase Letter 3
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 685
 
8.4%
천 649
 
7.9%
시 640
 
7.8%
역 634
 
7.8%
광 632
 
7.7%
로 608
 
7.4%
구 497
 
6.1%
길 204
 
2.5%
동 178
 
2.2%
번 172
 
2.1%
Other values (228) 3273
40.1%
Decimal Number
ValueCountFrequency (%)
1 376
18.5%
2 285
14.0%
3 214
10.5%
4 211
10.4%
7 177
8.7%
6 174
8.6%
5 169
8.3%
9 145
 
7.1%
0 142
 
7.0%
8 141
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
T 1
33.3%
C 1
33.3%
K 1
33.3%
Space Separator
ValueCountFrequency (%)
2078
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8172
65.8%
Common 4248
34.2%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 685
 
8.4%
천 649
 
7.9%
시 640
 
7.8%
역 634
 
7.8%
광 632
 
7.7%
로 608
 
7.4%
구 497
 
6.1%
길 204
 
2.5%
동 178
 
2.2%
번 172
 
2.1%
Other values (228) 3273
40.1%
Common
ValueCountFrequency (%)
2078
48.9%
1 376
 
8.9%
2 285
 
6.7%
3 214
 
5.0%
4 211
 
5.0%
7 177
 
4.2%
6 174
 
4.1%
5 169
 
4.0%
9 145
 
3.4%
0 142
 
3.3%
Other values (6) 277
 
6.5%
Latin
ValueCountFrequency (%)
T 1
33.3%
C 1
33.3%
K 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8172
65.8%
ASCII 4251
34.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2078
48.9%
1 376
 
8.8%
2 285
 
6.7%
3 214
 
5.0%
4 211
 
5.0%
7 177
 
4.2%
6 174
 
4.1%
5 169
 
4.0%
9 145
 
3.4%
0 142
 
3.3%
Other values (9) 280
 
6.6%
Hangul
ValueCountFrequency (%)
인 685
 
8.4%
천 649
 
7.9%
시 640
 
7.8%
역 634
 
7.8%
광 632
 
7.7%
로 608
 
7.4%
구 497
 
6.1%
길 204
 
2.5%
동 178
 
2.2%
번 172
 
2.1%
Other values (228) 3273
40.1%

전화번호(교환)
Text

Distinct617
Distinct (%)98.1%
Missing1
Missing (%)0.2%
Memory size5.1 KiB
2024-01-28T15:18:25.950484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length11.980922
Min length7

Characters and Unicode

Total characters7536
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

Unique610 ?
Unique (%)97.0%

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%
032-770-0200 2
 
0.3%
032-585-7100 2
 
0.3%
032-884-1119 2
 
0.3%
032-749-6915 2
 
0.3%
032-454-9311 1
 
0.2%
032-469-3655 1
 
0.2%
032-454-9706 1
 
0.2%
Other values (607) 607
96.5%
2024-01-28T15:18:26.247847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1392
18.5%
- 1248
16.6%
3 1095
14.5%
2 962
12.8%
1 462
 
6.1%
5 452
 
6.0%
8 403
 
5.3%
7 402
 
5.3%
4 385
 
5.1%
6 364
 
4.8%
Other values (14) 371
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6263
83.1%
Dash Punctuation 1248
 
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 1392
22.2%
3 1095
17.5%
2 962
15.4%
1 462
 
7.4%
5 452
 
7.2%
8 403
 
6.4%
7 402
 
6.4%
4 385
 
6.1%
6 364
 
5.8%
9 346
 
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 (%)
- 1248
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 7527
99.9%
Hangul 9
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1392
18.5%
- 1248
16.6%
3 1095
14.5%
2 962
12.8%
1 462
 
6.1%
5 452
 
6.0%
8 403
 
5.4%
7 402
 
5.3%
4 385
 
5.1%
6 364
 
4.8%
Other values (5) 362
 
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 7527
99.9%
Hangul 9
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1392
18.5%
- 1248
16.6%
3 1095
14.5%
2 962
12.8%
1 462
 
6.1%
5 452
 
6.0%
8 403
 
5.4%
7 402
 
5.3%
4 385
 
5.1%
6 364
 
4.8%
Other values (5) 362
 
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 

Distinct370
Distinct (%)58.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22199.968
Minimum21007
Maximum23136
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-01-28T15:18:26.362650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21007
5-th percentile21067.45
Q121579
median22227.5
Q322796
95-th percentile23111
Maximum23136
Range2129
Interquartile range (IQR)1217

Descriptive statistics

Standard deviation666.42262
Coefficient of variation (CV)0.03001908
Kurtosis-1.2189733
Mean22199.968
Median Absolute Deviation (MAD)623.5
Skewness-0.17955403
Sum13985980
Variance444119.11
MonotonicityNot monotonic
2024-01-28T15:18:26.470081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21066 7
 
1.1%
23031 6
 
1.0%
23018 6
 
1.0%
23130 6
 
1.0%
21007 5
 
0.8%
22371 5
 
0.8%
23101 5
 
0.8%
23037 5
 
0.8%
23038 5
 
0.8%
23005 5
 
0.8%
Other values (360) 575
91.3%
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
1.0%
23128 3
0.5%
23127 2
 
0.3%
23125 3
0.5%
23123 1
 
0.2%
23119 4
0.6%

인터넷주소
Text

MISSING 

Distinct216
Distinct (%)75.0%
Missing342
Missing (%)54.3%
Memory size5.1 KiB
2024-01-28T15:18:26.640269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length94
Median length51
Mean length38.260417
Min length1

Characters and Unicode

Total characters11019
Distinct characters49
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

Unique198 ?
Unique (%)68.8%

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.incheon.go.kr/119/index 12
 
4.2%
https://www.icjg.go.kr/dong/index 11
 
3.8%
http://hnrl.michu.incheon.kr 11
 
3.8%
https://www.gygl.go.kr/main/index.asp 7
 
2.4%
https://www.icpolice.go.kr/board/rg4_board/pcontent.php?&bbs_code=jb001&bd_num=159&mcode=05:07 7
 
2.4%
yspubliclib.go.kr 7
 
2.4%
https://www.namdonglib.go.kr 5
 
1.7%
https://www.kcg.go.kr/inchoncgs/main.do 4
 
1.4%
icpolice.go.kr/police.phpdcode=jb 4
 
1.4%
incheon.go.kr/119/index 4
 
1.4%
Other values (206) 216
75.0%
2024-01-28T15:18:26.972530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 918
 
8.3%
. 897
 
8.1%
/ 888
 
8.1%
n 794
 
7.2%
g 675
 
6.1%
t 538
 
4.9%
w 513
 
4.7%
i 493
 
4.5%
d 465
 
4.2%
p 463
 
4.2%
Other values (39) 4375
39.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8348
75.8%
Other Punctuation 2097
 
19.0%
Decimal Number 341
 
3.1%
Math Symbol 133
 
1.2%
Connector Punctuation 87
 
0.8%
Uppercase Letter 11
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 918
 
11.0%
n 794
 
9.5%
g 675
 
8.1%
t 538
 
6.4%
w 513
 
6.1%
i 493
 
5.9%
d 465
 
5.6%
p 463
 
5.5%
e 427
 
5.1%
r 388
 
4.6%
Other values (15) 2674
32.0%
Decimal Number
ValueCountFrequency (%)
1 74
21.7%
0 58
17.0%
2 51
15.0%
9 39
11.4%
4 37
10.9%
5 26
 
7.6%
3 25
 
7.3%
7 15
 
4.4%
8 9
 
2.6%
6 7
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
S 2
18.2%
P 2
18.2%
I 2
18.2%
G 2
18.2%
N 2
18.2%
C 1
9.1%
Other Punctuation
ValueCountFrequency (%)
. 897
42.8%
/ 888
42.3%
: 197
 
9.4%
? 91
 
4.3%
& 24
 
1.1%
Math Symbol
ValueCountFrequency (%)
= 133
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 87
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8359
75.9%
Common 2660
 
24.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 918
 
11.0%
n 794
 
9.5%
g 675
 
8.1%
t 538
 
6.4%
w 513
 
6.1%
i 493
 
5.9%
d 465
 
5.6%
p 463
 
5.5%
e 427
 
5.1%
r 388
 
4.6%
Other values (21) 2685
32.1%
Common
ValueCountFrequency (%)
. 897
33.7%
/ 888
33.4%
: 197
 
7.4%
= 133
 
5.0%
? 91
 
3.4%
_ 87
 
3.3%
1 74
 
2.8%
0 58
 
2.2%
2 51
 
1.9%
9 39
 
1.5%
Other values (8) 145
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11019
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 918
 
8.3%
. 897
 
8.1%
/ 888
 
8.1%
n 794
 
7.2%
g 675
 
6.1%
t 538
 
4.9%
w 513
 
4.7%
i 493
 
4.5%
d 465
 
4.2%
p 463
 
4.2%
Other values (39) 4375
39.7%

Interactions

2024-01-28T15:18:23.950705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:18:23.803492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:18:24.015614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:18:23.873872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T15:18:27.057414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관할군구우편번호
연번1.0000.9920.983
관할군구0.9921.0000.996
우편번호0.9830.9961.000
2024-01-28T15:18:27.129404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호관할군구
연번1.000-0.6310.840
우편번호-0.6311.0000.893
관할군구0.8400.8931.000

Missing values

2024-01-28T15:18:24.095303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T15:18:24.176484image/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.
2024-01-28T15:18:24.245795image/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
620621서구인천서부소방서 연희119안전센터인천광역시 서구 서곶로 292032-723-542122711<NA>
621622서구인천서부소방서 신현119안전센터인천광역시 서구 가정로 333-1032-572-011922782<NA>
622623서구인천서부소방서 석남119안전센터인천광역시 서구 석남로 102032-571-011922796<NA>
623624서구인천서부소방서 가좌119안전센터인천광역시 서구 백범로678번길 17032-578-011922825<NA>
624625서구인천서부소방서 청라119안전센터인천광역시 서구 청라한내로 77032-569-502622758<NA>
625626서구인천서부소방서 원당119안전센터인천광역시 서구 원당대로 881032-563-119522624<NA>
626627서구인천서부소방서 검단119안전센터인천광역시 서구 완정로 191032-565-011922616<NA>
627628서구인천서부소방서 오류119안전센터인천광역시 서구 대촌로 6032-566-111822656<NA>
628629서구인천서부소방서 정서진119수난구조대인천광역시 서구 정서진로 623032-568-367222694<NA>
629630서구인천검단소방서인천광역시 서구 원당대로 736032-562-011922679<NA>