Overview

Dataset statistics

Number of variables9
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory80.5 B

Variable types

Text6
Numeric3

Dataset

Description시군별 고용복지플러스센터 현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=C5X1VS8VY0KL6GAZKZXC25564069&infSeq=1

Alerts

소재지우편번호 is highly overall correlated with WGS84위도High correlation
WGS84위도 is highly overall correlated with 소재지우편번호High correlation
시군명 has unique valuesUnique
기관명 has unique valuesUnique
소재지지번주소 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
소재지우편번호 has unique valuesUnique
WGS84위도 has unique valuesUnique
WGS84경도 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-03-12 23:29:56.636579
Analysis finished2024-03-12 23:29:57.640961
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-13T08:29:57.750740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.125
Min length3

Characters and Unicode

Total characters75
Distinct characters33
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

Unique24 ?
Unique (%)100.0%

Sample

1st row고양시
2nd row광명시
3rd row광주시
4th row구리시
5th row김포시
ValueCountFrequency (%)
고양시 1
 
4.2%
광명시 1
 
4.2%
하남시 1
 
4.2%
평택시 1
 
4.2%
파주시 1
 
4.2%
이천시 1
 
4.2%
의정부시 1
 
4.2%
의왕시 1
 
4.2%
용인시 1
 
4.2%
오산시 1
 
4.2%
Other values (14) 14
58.3%
2024-03-13T08:29:58.000447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 25
33.3%
주 4
 
5.3%
양 4
 
5.3%
남 3
 
4.0%
천 3
 
4.0%
안 3
 
4.0%
성 3
 
4.0%
의 2
 
2.7%
부 2
 
2.7%
산 2
 
2.7%
Other values (23) 24
32.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 75
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 25
33.3%
주 4
 
5.3%
양 4
 
5.3%
남 3
 
4.0%
천 3
 
4.0%
안 3
 
4.0%
성 3
 
4.0%
의 2
 
2.7%
부 2
 
2.7%
산 2
 
2.7%
Other values (23) 24
32.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 75
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 25
33.3%
주 4
 
5.3%
양 4
 
5.3%
남 3
 
4.0%
천 3
 
4.0%
안 3
 
4.0%
성 3
 
4.0%
의 2
 
2.7%
부 2
 
2.7%
산 2
 
2.7%
Other values (23) 24
32.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 75
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 25
33.3%
주 4
 
5.3%
양 4
 
5.3%
남 3
 
4.0%
천 3
 
4.0%
안 3
 
4.0%
성 3
 
4.0%
의 2
 
2.7%
부 2
 
2.7%
산 2
 
2.7%
Other values (23) 24
32.0%

기관명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-13T08:29:58.164244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length11.208333
Min length11

Characters and Unicode

Total characters269
Distinct characters42
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

Unique24 ?
Unique (%)100.0%

Sample

1st row고양고용복지플러스센터
2nd row광명고용복지플러스센터
3rd row경기광주고용복지플러스센터
4th row구리고용복지플러스센터
5th row김포고용복지플러스센터
ValueCountFrequency (%)
고양고용복지플러스센터 1
 
4.2%
광명고용복지플러스센터 1
 
4.2%
하남고용복지플러스센터 1
 
4.2%
평택고용복지플러스센터 1
 
4.2%
파주고용복지플러스센터 1
 
4.2%
이천고용복지플러스센터 1
 
4.2%
의정부고용복지플러스센터 1
 
4.2%
의왕고용복지플러스센터 1
 
4.2%
용인고용복지플러스센터 1
 
4.2%
오산고용복지플러스센터 1
 
4.2%
Other values (14) 14
58.3%
2024-03-13T08:29:58.426503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
고 25
9.3%
용 25
9.3%
복 24
8.9%
지 24
8.9%
플 24
8.9%
러 24
8.9%
스 24
8.9%
센 24
8.9%
터 24
8.9%
양 4
 
1.5%
Other values (32) 47
17.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 269
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 25
9.3%
용 25
9.3%
복 24
8.9%
지 24
8.9%
플 24
8.9%
러 24
8.9%
스 24
8.9%
센 24
8.9%
터 24
8.9%
양 4
 
1.5%
Other values (32) 47
17.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 269
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 25
9.3%
용 25
9.3%
복 24
8.9%
지 24
8.9%
플 24
8.9%
러 24
8.9%
스 24
8.9%
센 24
8.9%
터 24
8.9%
양 4
 
1.5%
Other values (32) 47
17.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 269
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
고 25
9.3%
용 25
9.3%
복 24
8.9%
지 24
8.9%
플 24
8.9%
러 24
8.9%
스 24
8.9%
센 24
8.9%
터 24
8.9%
양 4
 
1.5%
Other values (32) 47
17.5%

소재지지번주소
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-13T08:29:58.621222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length20.666667
Min length17

Characters and Unicode

Total characters496
Distinct characters88
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

Unique24 ?
Unique (%)100.0%

Sample

1st row경기도 고양시 일산동구 장항동 736-2번지
2nd row경기도 광명시 철산동 463-38번지 힐팰리스
3rd row경기도 광주시 경안동 416-2번지
4th row경기도 구리시 인창동 670-1번지
5th row경기도 김포시 장기동 1604번지
ValueCountFrequency (%)
경기도 24
 
22.9%
664-2번지 1
 
1.0%
의왕시 1
 
1.0%
581-1번지 1
 
1.0%
구갈동 1
 
1.0%
기흥구 1
 
1.0%
용인시 1
 
1.0%
34-5번지 1
 
1.0%
오산동 1
 
1.0%
오산시 1
 
1.0%
Other values (72) 72
68.6%
2024-03-13T08:29:58.913397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
81
 
16.3%
동 27
 
5.4%
기 27
 
5.4%
경 25
 
5.0%
도 25
 
5.0%
시 25
 
5.0%
번 24
 
4.8%
지 24
 
4.8%
- 19
 
3.8%
1 16
 
3.2%
Other values (78) 203
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 299
60.3%
Decimal Number 97
 
19.6%
Space Separator 81
 
16.3%
Dash Punctuation 19
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 27
 
9.0%
기 27
 
9.0%
경 25
 
8.4%
도 25
 
8.4%
시 25
 
8.4%
번 24
 
8.0%
지 24
 
8.0%
구 9
 
3.0%
산 6
 
2.0%
안 6
 
2.0%
Other values (66) 101
33.8%
Decimal Number
ValueCountFrequency (%)
1 16
16.5%
3 15
15.5%
6 13
13.4%
2 11
11.3%
4 9
9.3%
0 8
8.2%
5 7
7.2%
9 7
7.2%
8 6
 
6.2%
7 5
 
5.2%
Space Separator
ValueCountFrequency (%)
81
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 299
60.3%
Common 197
39.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 27
 
9.0%
기 27
 
9.0%
경 25
 
8.4%
도 25
 
8.4%
시 25
 
8.4%
번 24
 
8.0%
지 24
 
8.0%
구 9
 
3.0%
산 6
 
2.0%
안 6
 
2.0%
Other values (66) 101
33.8%
Common
ValueCountFrequency (%)
81
41.1%
- 19
 
9.6%
1 16
 
8.1%
3 15
 
7.6%
6 13
 
6.6%
2 11
 
5.6%
4 9
 
4.6%
0 8
 
4.1%
5 7
 
3.6%
9 7
 
3.6%
Other values (2) 11
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 299
60.3%
ASCII 197
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
81
41.1%
- 19
 
9.6%
1 16
 
8.1%
3 15
 
7.6%
6 13
 
6.6%
2 11
 
5.6%
4 9
 
4.6%
0 8
 
4.1%
5 7
 
3.6%
9 7
 
3.6%
Other values (2) 11
 
5.6%
Hangul
ValueCountFrequency (%)
동 27
 
9.0%
기 27
 
9.0%
경 25
 
8.4%
도 25
 
8.4%
시 25
 
8.4%
번 24
 
8.0%
지 24
 
8.0%
구 9
 
3.0%
산 6
 
2.0%
안 6
 
2.0%
Other values (66) 101
33.8%

소재지도로명주소
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-13T08:29:59.106309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length17.125
Min length14

Characters and Unicode

Total characters411
Distinct characters82
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

Unique24 ?
Unique (%)100.0%

Sample

1st row경기도 고양시 일산동구 고봉로 32-16
2nd row경기도 광명시 시청로 15
3rd row경기도 광주시 광주대로 62
4th row경기도 구리시 건원대로 44
5th row경기도 김포시 김포한강4로 125
ValueCountFrequency (%)
경기도 24
 
23.3%
984 2
 
1.9%
11 1
 
1.0%
의왕시 1
 
1.0%
3 1
 
1.0%
강남로 1
 
1.0%
기흥구 1
 
1.0%
용인시 1
 
1.0%
51 1
 
1.0%
경기동로 1
 
1.0%
Other values (69) 69
67.0%
2024-03-13T08:29:59.404130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
79
19.2%
경 28
 
6.8%
기 27
 
6.6%
시 27
 
6.6%
도 24
 
5.8%
로 23
 
5.6%
1 14
 
3.4%
3 10
 
2.4%
4 10
 
2.4%
5 9
 
2.2%
Other values (72) 160
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 263
64.0%
Space Separator 79
 
19.2%
Decimal Number 68
 
16.5%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 28
 
10.6%
기 27
 
10.3%
시 27
 
10.3%
도 24
 
9.1%
로 23
 
8.7%
대 8
 
3.0%
안 7
 
2.7%
구 7
 
2.7%
양 6
 
2.3%
주 6
 
2.3%
Other values (61) 100
38.0%
Decimal Number
ValueCountFrequency (%)
1 14
20.6%
3 10
14.7%
4 10
14.7%
5 9
13.2%
8 8
11.8%
9 7
10.3%
2 5
 
7.4%
6 3
 
4.4%
0 2
 
2.9%
Space Separator
ValueCountFrequency (%)
79
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 263
64.0%
Common 148
36.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 28
 
10.6%
기 27
 
10.3%
시 27
 
10.3%
도 24
 
9.1%
로 23
 
8.7%
대 8
 
3.0%
안 7
 
2.7%
구 7
 
2.7%
양 6
 
2.3%
주 6
 
2.3%
Other values (61) 100
38.0%
Common
ValueCountFrequency (%)
79
53.4%
1 14
 
9.5%
3 10
 
6.8%
4 10
 
6.8%
5 9
 
6.1%
8 8
 
5.4%
9 7
 
4.7%
2 5
 
3.4%
6 3
 
2.0%
0 2
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 263
64.0%
ASCII 148
36.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
79
53.4%
1 14
 
9.5%
3 10
 
6.8%
4 10
 
6.8%
5 9
 
6.1%
8 8
 
5.4%
9 7
 
4.7%
2 5
 
3.4%
6 3
 
2.0%
0 2
 
1.4%
Hangul
ValueCountFrequency (%)
경 28
 
10.6%
기 27
 
10.3%
시 27
 
10.3%
도 24
 
9.1%
로 23
 
8.7%
대 8
 
3.0%
안 7
 
2.7%
구 7
 
2.7%
양 6
 
2.3%
주 6
 
2.3%
Other values (61) 100
38.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14212.833
Minimum10083
Maximum18302
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-03-13T08:29:59.502384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10083
5-th percentile10448.9
Q111859.25
median14108.5
Q316606.5
95-th percentile18072.2
Maximum18302
Range8219
Interquartile range (IQR)4747.25

Descriptive statistics

Standard deviation2653.1334
Coefficient of variation (CV)0.18667168
Kurtosis-1.3438814
Mean14212.833
Median Absolute Deviation (MAD)2404.5
Skewness0.089192956
Sum341108
Variance7039116.9
MonotonicityNot monotonic
2024-03-13T08:29:59.600928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
10364 1
 
4.2%
14001 1
 
4.2%
18302 1
 
4.2%
12919 1
 
4.2%
17739 1
 
4.2%
10930 1
 
4.2%
17356 1
 
4.2%
11674 1
 
4.2%
16004 1
 
4.2%
16977 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
10083 1
4.2%
10364 1
4.2%
10930 1
4.2%
11357 1
4.2%
11498 1
4.2%
11674 1
4.2%
11921 1
4.2%
12237 1
4.2%
12757 1
4.2%
12919 1
4.2%
ValueCountFrequency (%)
18302 1
4.2%
18131 1
4.2%
17739 1
4.2%
17596 1
4.2%
17356 1
4.2%
16977 1
4.2%
16483 1
4.2%
16004 1
4.2%
15357 1
4.2%
15049 1
4.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.448373
Minimum37.001248
Maximum37.898718
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-03-13T08:29:59.697925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.001248
5-th percentile37.069028
Q137.284149
median37.405431
Q337.636345
95-th percentile37.781913
Maximum37.898718
Range0.89747005
Interquartile range (IQR)0.35219538

Descriptive statistics

Standard deviation0.23615691
Coefficient of variation (CV)0.0063061994
Kurtosis-0.6404912
Mean37.448373
Median Absolute Deviation (MAD)0.16889489
Skewness0.028041751
Sum898.76096
Variance0.055770085
MonotonicityNot monotonic
2024-03-13T08:29:59.799487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
37.66412943 1
 
4.2%
37.39874559 1
 
4.2%
37.21685827 1
 
4.2%
37.55464805 1
 
4.2%
37.05317713 1
 
4.2%
37.76483783 1
 
4.2%
37.28632256 1
 
4.2%
37.73865484 1
 
4.2%
37.39607866 1
 
4.2%
37.27101768 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
37.00124814 1
4.2%
37.05317713 1
4.2%
37.1588465 1
4.2%
37.21685827 1
4.2%
37.27101768 1
4.2%
37.27762883 1
4.2%
37.28632256 1
4.2%
37.31850765 1
4.2%
37.34886407 1
4.2%
37.35108611 1
4.2%
ValueCountFrequency (%)
37.89871819 1
4.2%
37.78492613 1
4.2%
37.76483783 1
4.2%
37.73865484 1
4.2%
37.66412943 1
4.2%
37.6446267 1
4.2%
37.63358377 1
4.2%
37.60500361 1
4.2%
37.55464805 1
4.2%
37.50306452 1
4.2%

WGS84경도
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.0145
Minimum126.66703
Maximum127.44952
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-03-13T08:29:59.896528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.66703
5-th percentile126.74632
Q1126.85445
median127.04286
Q3127.12963
95-th percentile127.26677
Maximum127.44952
Range0.7824894
Interquartile range (IQR)0.27518055

Descriptive statistics

Standard deviation0.19415752
Coefficient of variation (CV)0.0015286249
Kurtosis-0.3229649
Mean127.0145
Median Absolute Deviation (MAD)0.13286165
Skewness0.10162973
Sum3048.3479
Variance0.037697141
MonotonicityNot monotonic
2024-03-13T08:30:00.011101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
126.7659068 1
 
4.2%
126.9207325 1
 
4.2%
126.9582896 1
 
4.2%
127.1864558 1
 
4.2%
127.0604194 1
 
4.2%
126.7746763 1
 
4.2%
127.4495189 1
 
4.2%
127.0404339 1
 
4.2%
126.9843386 1
 
4.2%
127.1261006 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
126.6670295 1
4.2%
126.7428655 1
4.2%
126.7659068 1
4.2%
126.7746763 1
4.2%
126.7813789 1
4.2%
126.8273298 1
4.2%
126.8634849 1
4.2%
126.9207325 1
4.2%
126.9582896 1
4.2%
126.9843386 1
4.2%
ValueCountFrequency (%)
127.4495189 1
4.2%
127.2678441 1
4.2%
127.2607033 1
4.2%
127.207699 1
4.2%
127.1864558 1
4.2%
127.1402049 1
4.2%
127.1261006 1
4.2%
127.1094904 1
4.2%
127.0772925 1
4.2%
127.0604194 1
4.2%

전화번호
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-13T08:30:00.165844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.041667
Min length12

Characters and Unicode

Total characters289
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

Unique24 ?
Unique (%)100.0%

Sample

1st row031-920-3937
2nd row02-2680-1500
3rd row031-799-2760
4th row031-560-5800
5th row031-999-0900
ValueCountFrequency (%)
031-920-3937 1
 
4.2%
02-2680-1500 1
 
4.2%
031-730-7000 1
 
4.2%
031-646-1205 1
 
4.2%
031-860-0401 1
 
4.2%
031-644-3820 1
 
4.2%
031-828-0900 1
 
4.2%
031-463-7460 1
 
4.2%
031-289-2210 1
 
4.2%
031-8024-9805 1
 
4.2%
Other values (14) 14
58.3%
2024-03-13T08:30:00.409720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 72
24.9%
- 48
16.6%
3 34
11.8%
1 34
11.8%
9 19
 
6.6%
6 18
 
6.2%
2 17
 
5.9%
8 15
 
5.2%
7 13
 
4.5%
4 12
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 241
83.4%
Dash Punctuation 48
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 72
29.9%
3 34
14.1%
1 34
14.1%
9 19
 
7.9%
6 18
 
7.5%
2 17
 
7.1%
8 15
 
6.2%
7 13
 
5.4%
4 12
 
5.0%
5 7
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 289
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 72
24.9%
- 48
16.6%
3 34
11.8%
1 34
11.8%
9 19
 
6.6%
6 18
 
6.2%
2 17
 
5.9%
8 15
 
5.2%
7 13
 
4.5%
4 12
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 289
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 72
24.9%
- 48
16.6%
3 34
11.8%
1 34
11.8%
9 19
 
6.6%
6 18
 
6.2%
2 17
 
5.9%
8 15
 
5.2%
7 13
 
4.5%
4 12
 
4.2%

홈페이지URL
Text

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-13T08:30:00.576797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length35
Mean length30.958333
Min length27

Characters and Unicode

Total characters743
Distinct characters23
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

Unique22 ?
Unique (%)91.7%

Sample

1st rowwww.work.go.kr/goyang/main.do
2nd rowwww.work.go.kr/gwangmyeong/main.do
3rd rowwww.work.go.kr/gyeongingwangju/main.do
4th rowwww.work.go.kr/guri/main.do
5th rowwww.work.go.kr/gimpo/main.do
ValueCountFrequency (%)
www.work.go.kr/guri/main.do 2
 
8.3%
www.work.go.kr/goyang/main.do 1
 
4.2%
www.work.go.kr/anyang/main.do 1
 
4.2%
http://www.work.go.kr/hanam/main.do 1
 
4.2%
www.work.go.kr/pyeongtaek/main.do 1
 
4.2%
www.work.go.kr/paju/main.do 1
 
4.2%
www.work.go.kr/icheon/main.do 1
 
4.2%
www.work.go.kr/uijeongbu/main.do 1
 
4.2%
http://www.work.go.kr/uiwang/main.do 1
 
4.2%
www.work.go.kr/yongin/main.do 1
 
4.2%
Other values (13) 13
54.2%
2024-03-13T08:30:00.854251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 101
13.6%
. 96
12.9%
o 86
11.6%
/ 56
7.5%
n 53
7.1%
r 50
 
6.7%
k 49
 
6.6%
g 47
 
6.3%
a 43
 
5.8%
i 33
 
4.4%
Other values (13) 129
17.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 587
79.0%
Other Punctuation 156
 
21.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 101
17.2%
o 86
14.7%
n 53
9.0%
r 50
8.5%
k 49
8.3%
g 47
8.0%
a 43
7.3%
i 33
 
5.6%
m 29
 
4.9%
d 24
 
4.1%
Other values (10) 72
12.3%
Other Punctuation
ValueCountFrequency (%)
. 96
61.5%
/ 56
35.9%
: 4
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 587
79.0%
Common 156
 
21.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 101
17.2%
o 86
14.7%
n 53
9.0%
r 50
8.5%
k 49
8.3%
g 47
8.0%
a 43
7.3%
i 33
 
5.6%
m 29
 
4.9%
d 24
 
4.1%
Other values (10) 72
12.3%
Common
ValueCountFrequency (%)
. 96
61.5%
/ 56
35.9%
: 4
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 743
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 101
13.6%
. 96
12.9%
o 86
11.6%
/ 56
7.5%
n 53
7.1%
r 50
 
6.7%
k 49
 
6.6%
g 47
 
6.3%
a 43
 
5.8%
i 33
 
4.4%
Other values (13) 129
17.4%

Interactions

2024-03-13T08:29:57.286331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:29:56.917150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:29:57.096078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:29:57.347677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:29:56.970899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:29:57.152363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:29:57.409974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:29:57.026571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:29:57.214587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:30:00.934691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명기관명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도전화번호홈페이지URL
시군명1.0001.0001.0001.0001.0001.0001.0001.0001.000
기관명1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지우편번호1.0001.0001.0001.0001.0000.8640.6761.0000.938
WGS84위도1.0001.0001.0001.0000.8641.0000.2891.0000.000
WGS84경도1.0001.0001.0001.0000.6760.2891.0001.0000.950
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
홈페이지URL1.0001.0001.0001.0000.9380.0000.9501.0001.000
2024-03-13T08:30:01.028522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도
소재지우편번호1.000-0.9350.277
WGS84위도-0.9351.000-0.285
WGS84경도0.277-0.2851.000

Missing values

2024-03-13T08:29:57.501110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:29:57.599731image/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

시군명기관명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도전화번호홈페이지URL
0고양시고양고용복지플러스센터경기도 고양시 일산동구 장항동 736-2번지경기도 고양시 일산동구 고봉로 32-161036437.664129126.765907031-920-3937www.work.go.kr/goyang/main.do
1광명시광명고용복지플러스센터경기도 광명시 철산동 463-38번지 힐팰리스경기도 광명시 시청로 151421637.478268126.86348502-2680-1500www.work.go.kr/gwangmyeong/main.do
2광주시경기광주고용복지플러스센터경기도 광주시 경안동 416-2번지경기도 광주시 광주대로 621275737.412116127.260703031-799-2760www.work.go.kr/gyeongingwangju/main.do
3구리시구리고용복지플러스센터경기도 구리시 인창동 670-1번지경기도 구리시 건원대로 441192137.605004127.140205031-560-5800www.work.go.kr/guri/main.do
4김포시김포고용복지플러스센터경기도 김포시 장기동 1604번지경기도 김포시 김포한강4로 1251008337.644627126.667029031-999-0900www.work.go.kr/gimpo/main.do
5남양주시남양주고용복지플러스센터경기도 남양주시 금곡동 430-11번지경기도 남양주시 경춘로 9531223737.633584127.207699031-560-1919www.work.go.kr/namyangju/main.do
6동두천시동두천고용복지플러스센터경기도 동두천시 생연동 369-8번지경기도 동두천시 삼육사로 9841135737.898718127.059013031-860-1700www.work.go.kr/guri/main.do
7부천시부천고용복지플러스센터경기도 부천시 중동 1086-3번지경기도 부천시 길주로 3511453037.503065126.781379032-320-8900www.work.go.kr/bucheon/main.do
8성남시성남고용복지플러스센터경기도 성남시 분당구 구미동 23-3번지경기도 성남시 분당구 성남대로 1461362737.348864127.10949031-739-3177www.work.go.kr/seongnam/main.do
9수원시수원고용복지플러스센터경기도 수원시 팔달구 인계동 939번지경기도 수원시 팔달구 경수대로 5841648337.277629127.031386031-231-7864www.work.go.kr/suwon/main.do
시군명기관명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도전화번호홈페이지URL
14양주시양주고용복지플러스센터경기도 양주시 남방동 1-1번지경기도 양주시 부흥로 15331149837.784926127.045293031-849-2300http://www.work.go.kr/yangju/main.do
15오산시오산고용복지플러스센터경기도 오산시 오산동 34-5번지경기도 오산시 경기동로 511813137.158847127.077292031-8024-9805www.work.go.kr/osan/main.do
16용인시용인고용복지플러스센터경기도 용인시 기흥구 구갈동 581-1번지경기도 용인시 기흥구 강남로 31697737.271018127.126101031-289-2210www.work.go.kr/yongin/main.do
17의왕시의왕고용복지플러스센터경기도 의왕시 포일동 664-2번지경기도 의왕시 안양판교로 891600437.396079126.984339031-463-7460http://www.work.go.kr/uiwang/main.do
18의정부시의정부고용복지플러스센터경기도 의정부시 가능동 754번지 신동아파라디움경기도 의정부시 시민로 491167437.738655127.040434031-828-0900www.work.go.kr/uijeongbu/main.do
19이천시이천고용복지플러스센터경기도 이천시 창전동 443-37번지경기도 이천시 이섭대천로 13091735637.286323127.449519031-644-3820www.work.go.kr/icheon/main.do
20파주시파주고용복지플러스센터경기도 파주시 금촌동 329-158번지경기도 파주시 중앙로 3281093037.764838126.774676031-860-0401www.work.go.kr/paju/main.do
21평택시평택고용복지플러스센터경기도 평택시 이충동 608번지경기도 평택시 경기대로 11941773937.053177127.060419031-646-1205www.work.go.kr/pyeongtaek/main.do
22하남시하남고용복지플러스센터경기도 하남시 풍산동 522번지경기도 하남시 미사강변대로 521291937.554648127.186456031-730-7000http://www.work.go.kr/hanam/main.do
23화성시화성고용복지플러스센터경기도 화성시 봉담읍 동화리 599-2번지경기도 화성시 봉담읍 동화길 851830237.216858126.95829031-290-0800www.work.go.kr/hwaseong/main.do