Overview

Dataset statistics

Number of variables8
Number of observations253
Missing cells15
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.2 KiB
Average record size in memory65.5 B

Variable types

Numeric1
Categorical1
Text5
DateTime1

Dataset

Description인천광역시 서구에 소재한 경로당의 현황(연번, 동명, 경로당명, 우편번호, 소재지, 전화번호 등)을 제공합니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3078098&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
순번 is highly overall correlated with 동명High correlation
동명 is highly overall correlated with 순번High correlation
전화번호 has 15 (5.9%) missing valuesMissing
순번 has unique valuesUnique
소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2024-01-28 10:23:59.791834
Analysis finished2024-01-28 10:24:00.408231
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct253
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127
Minimum1
Maximum253
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-01-28T19:24:00.462889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.6
Q164
median127
Q3190
95-th percentile240.4
Maximum253
Range252
Interquartile range (IQR)126

Descriptive statistics

Standard deviation73.179004
Coefficient of variation (CV)0.57621263
Kurtosis-1.2
Mean127
Median Absolute Deviation (MAD)63
Skewness0
Sum32131
Variance5355.1667
MonotonicityStrictly increasing
2024-01-28T19:24:00.566142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
175 1
 
0.4%
162 1
 
0.4%
163 1
 
0.4%
164 1
 
0.4%
165 1
 
0.4%
166 1
 
0.4%
167 1
 
0.4%
168 1
 
0.4%
169 1
 
0.4%
Other values (243) 243
96.0%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
253 1
0.4%
252 1
0.4%
251 1
0.4%
250 1
0.4%
249 1
0.4%
248 1
0.4%
247 1
0.4%
246 1
0.4%
245 1
0.4%
244 1
0.4%

동명
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
오류왕길동
25 
검단동
25 
검암경서동
17 
연희동
17 
불로대곡동
17 
Other values (18)
152 

Length

Max length5
Median length4
Mean length3.9644269
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
오류왕길동 25
 
9.9%
검단동 25
 
9.9%
검암경서동 17
 
6.7%
연희동 17
 
6.7%
불로대곡동 17
 
6.7%
청라2동 12
 
4.7%
당하동 12
 
4.7%
가좌2동 12
 
4.7%
청라1동 11
 
4.3%
청라3동 11
 
4.3%
Other values (13) 94
37.2%

Length

2024-01-28T19:24:00.692176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
오류왕길동 25
 
9.9%
검단동 25
 
9.9%
검암경서동 17
 
6.7%
연희동 17
 
6.7%
불로대곡동 17
 
6.7%
청라2동 12
 
4.7%
당하동 12
 
4.7%
가좌2동 12
 
4.7%
청라1동 11
 
4.3%
청라3동 11
 
4.3%
Other values (13) 94
37.2%

경로당명
Text

Distinct247
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-01-28T19:24:00.851600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length10.525692
Min length5

Characters and Unicode

Total characters2663
Distinct characters236
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

Unique241 ?
Unique (%)95.3%

Sample

1st row시천경로당
2nd row경서동경로당
3rd row검암2차풍림아파트경로당
4th row공촌경로당
5th row검암1차신명아파트경로당
ValueCountFrequency (%)
경로당 14
 
5.2%
원흥아파트경로당 2
 
0.7%
동남아파트경로당 2
 
0.7%
현대아파트경로당 2
 
0.7%
태화아파트경로당 2
 
0.7%
동진아파트경로당 2
 
0.7%
효정아파트경로당 2
 
0.7%
현대아이파크아파트 1
 
0.4%
마전동남아파트경로당 1
 
0.4%
풍림아이원아파트 1
 
0.4%
Other values (241) 241
89.3%
2024-01-28T19:24:01.108112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
당 265
 
10.0%
로 260
 
9.8%
경 259
 
9.7%
아 192
 
7.2%
트 191
 
7.2%
파 180
 
6.8%
차 46
 
1.7%
동 45
 
1.7%
라 40
 
1.5%
단 40
 
1.5%
Other values (226) 1145
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2527
94.9%
Decimal Number 82
 
3.1%
Uppercase Letter 22
 
0.8%
Space Separator 17
 
0.6%
Close Punctuation 4
 
0.2%
Open Punctuation 4
 
0.2%
Lowercase Letter 4
 
0.2%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 265
 
10.5%
로 260
 
10.3%
경 259
 
10.2%
아 192
 
7.6%
트 191
 
7.6%
파 180
 
7.1%
차 46
 
1.8%
동 45
 
1.8%
라 40
 
1.6%
단 40
 
1.6%
Other values (202) 1009
39.9%
Uppercase Letter
ValueCountFrequency (%)
L 5
22.7%
H 4
18.2%
S 3
13.6%
K 3
13.6%
C 2
 
9.1%
G 1
 
4.5%
W 1
 
4.5%
E 1
 
4.5%
V 1
 
4.5%
I 1
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 30
36.6%
2 29
35.4%
3 10
 
12.2%
4 6
 
7.3%
5 3
 
3.7%
0 1
 
1.2%
6 1
 
1.2%
8 1
 
1.2%
7 1
 
1.2%
Space Separator
ValueCountFrequency (%)
17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2527
94.9%
Common 110
 
4.1%
Latin 26
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 265
 
10.5%
로 260
 
10.3%
경 259
 
10.2%
아 192
 
7.6%
트 191
 
7.6%
파 180
 
7.1%
차 46
 
1.8%
동 45
 
1.8%
라 40
 
1.6%
단 40
 
1.6%
Other values (202) 1009
39.9%
Common
ValueCountFrequency (%)
1 30
27.3%
2 29
26.4%
17
15.5%
3 10
 
9.1%
4 6
 
5.5%
) 4
 
3.6%
( 4
 
3.6%
- 3
 
2.7%
5 3
 
2.7%
0 1
 
0.9%
Other values (3) 3
 
2.7%
Latin
ValueCountFrequency (%)
L 5
19.2%
e 4
15.4%
H 4
15.4%
S 3
11.5%
K 3
11.5%
C 2
 
7.7%
G 1
 
3.8%
W 1
 
3.8%
E 1
 
3.8%
V 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2527
94.9%
ASCII 136
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
당 265
 
10.5%
로 260
 
10.3%
경 259
 
10.2%
아 192
 
7.6%
트 191
 
7.6%
파 180
 
7.1%
차 46
 
1.8%
동 45
 
1.8%
라 40
 
1.6%
단 40
 
1.6%
Other values (202) 1009
39.9%
ASCII
ValueCountFrequency (%)
1 30
22.1%
2 29
21.3%
17
12.5%
3 10
 
7.4%
4 6
 
4.4%
L 5
 
3.7%
) 4
 
2.9%
( 4
 
2.9%
e 4
 
2.9%
H 4
 
2.9%
Other values (14) 23
16.9%

우편번호
Text

Distinct138
Distinct (%)54.5%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-01-28T19:24:01.382845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0237154
Min length5

Characters and Unicode

Total characters1271
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

Unique71 ?
Unique (%)28.1%

Sample

1st row22686
2nd row22692
3rd row22704
4th row22698
5th row22697
ValueCountFrequency (%)
22815 6
 
2.4%
22765 5
 
2.0%
22766 4
 
1.6%
22779 4
 
1.6%
22611 4
 
1.6%
22631 4
 
1.6%
22600 4
 
1.6%
22678 4
 
1.6%
22657 4
 
1.6%
22811 4
 
1.6%
Other values (128) 210
83.0%
2024-01-28T19:24:01.774776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 548
43.1%
6 148
 
11.6%
7 139
 
10.9%
8 101
 
7.9%
1 82
 
6.5%
0 72
 
5.7%
3 53
 
4.2%
5 47
 
3.7%
4 41
 
3.2%
9 37
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1268
99.8%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 548
43.2%
6 148
 
11.7%
7 139
 
11.0%
8 101
 
8.0%
1 82
 
6.5%
0 72
 
5.7%
3 53
 
4.2%
5 47
 
3.7%
4 41
 
3.2%
9 37
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1271
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 548
43.1%
6 148
 
11.6%
7 139
 
10.9%
8 101
 
7.9%
1 82
 
6.5%
0 72
 
5.7%
3 53
 
4.2%
5 47
 
3.7%
4 41
 
3.2%
9 37
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1271
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 548
43.1%
6 148
 
11.6%
7 139
 
10.9%
8 101
 
7.9%
1 82
 
6.5%
0 72
 
5.7%
3 53
 
4.2%
5 47
 
3.7%
4 41
 
3.2%
9 37
 
2.9%

소재지(지번)
Text

Distinct252
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-01-28T19:24:02.039434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length17.905138
Min length14

Characters and Unicode

Total characters4530
Distinct characters59
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique251 ?
Unique (%)99.2%

Sample

1st row인천광역시 서구 시천동 113-1
2nd row인천광역시 서구 경서동 744-13
3rd row인천광역시 서구 검암동 501-1
4th row인천광역시 서구 검암동 657-4
5th row인천광역시 서구 검암동 629-1
ValueCountFrequency (%)
인천광역시 253
25.1%
서구 253
25.1%
청라동 34
 
3.4%
가좌동 30
 
3.0%
마전동 29
 
2.9%
당하동 19
 
1.9%
석남동 19
 
1.9%
가정동 19
 
1.9%
왕길동 16
 
1.6%
불로동 12
 
1.2%
Other values (263) 325
32.2%
2024-01-28T19:24:02.409904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
770
17.0%
서 258
 
5.7%
시 256
 
5.7%
1 255
 
5.6%
천 254
 
5.6%
인 253
 
5.6%
구 253
 
5.6%
동 253
 
5.6%
역 253
 
5.6%
광 253
 
5.6%
Other values (49) 1472
32.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2542
56.1%
Decimal Number 1010
 
22.3%
Space Separator 770
 
17.0%
Dash Punctuation 202
 
4.5%
Uppercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 258
10.1%
시 256
10.1%
천 254
10.0%
인 253
10.0%
구 253
10.0%
동 253
10.0%
역 253
10.0%
광 253
10.0%
가 52
 
2.0%
청 34
 
1.3%
Other values (34) 423
16.6%
Decimal Number
ValueCountFrequency (%)
1 255
25.2%
2 119
11.8%
3 100
 
9.9%
0 98
 
9.7%
5 88
 
8.7%
9 87
 
8.6%
7 72
 
7.1%
4 72
 
7.1%
6 68
 
6.7%
8 51
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
50.0%
A 2
33.3%
L 1
 
16.7%
Space Separator
ValueCountFrequency (%)
770
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 202
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2542
56.1%
Common 1982
43.8%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 258
10.1%
시 256
10.1%
천 254
10.0%
인 253
10.0%
구 253
10.0%
동 253
10.0%
역 253
10.0%
광 253
10.0%
가 52
 
2.0%
청 34
 
1.3%
Other values (34) 423
16.6%
Common
ValueCountFrequency (%)
770
38.8%
1 255
 
12.9%
- 202
 
10.2%
2 119
 
6.0%
3 100
 
5.0%
0 98
 
4.9%
5 88
 
4.4%
9 87
 
4.4%
7 72
 
3.6%
4 72
 
3.6%
Other values (2) 119
 
6.0%
Latin
ValueCountFrequency (%)
B 3
50.0%
A 2
33.3%
L 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2542
56.1%
ASCII 1988
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
770
38.7%
1 255
 
12.8%
- 202
 
10.2%
2 119
 
6.0%
3 100
 
5.0%
0 98
 
4.9%
5 88
 
4.4%
9 87
 
4.4%
7 72
 
3.6%
4 72
 
3.6%
Other values (5) 125
 
6.3%
Hangul
ValueCountFrequency (%)
서 258
10.1%
시 256
10.1%
천 254
10.0%
인 253
10.0%
구 253
10.0%
동 253
10.0%
역 253
10.0%
광 253
10.0%
가 52
 
2.0%
청 34
 
1.3%
Other values (34) 423
16.6%

소재지(도로명)
Text

UNIQUE 

Distinct253
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-01-28T19:24:02.655436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length41
Mean length32.466403
Min length16

Characters and Unicode

Total characters8214
Distinct characters259
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique253 ?
Unique (%)100.0%

Sample

1st row인천광역시 서구 아라로105번길 1-8 (시천동)
2nd row인천광역시 서구 경서로55번길 7 (경서동)
3rd row인천광역시 서구 검암로 53 (검암동)
4th row인천광역시 서구 승학로402번길 15 (검암동)
5th row인천광역시 서구 승학로 447 (검암동)
ValueCountFrequency (%)
인천광역시 253
 
17.3%
서구 253
 
17.3%
청라동 31
 
2.1%
가좌동 31
 
2.1%
마전동 28
 
1.9%
석남동 20
 
1.4%
왕길동 17
 
1.2%
당하동 16
 
1.1%
가정동 15
 
1.0%
불로동 13
 
0.9%
Other values (508) 785
53.7%
2024-01-28T19:24:02.998458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1406
 
17.1%
서 278
 
3.4%
로 271
 
3.3%
동 271
 
3.3%
천 260
 
3.2%
인 259
 
3.2%
시 258
 
3.1%
광 257
 
3.1%
구 253
 
3.1%
역 253
 
3.1%
Other values (249) 4448
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5098
62.1%
Space Separator 1406
 
17.1%
Decimal Number 979
 
11.9%
Open Punctuation 246
 
3.0%
Close Punctuation 246
 
3.0%
Other Punctuation 197
 
2.4%
Dash Punctuation 24
 
0.3%
Uppercase Letter 13
 
0.2%
Lowercase Letter 3
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 278
 
5.5%
로 271
 
5.3%
동 271
 
5.3%
천 260
 
5.1%
인 259
 
5.1%
시 258
 
5.1%
광 257
 
5.0%
구 253
 
5.0%
역 253
 
5.0%
아 152
 
3.0%
Other values (223) 2586
50.7%
Decimal Number
ValueCountFrequency (%)
1 194
19.8%
2 133
13.6%
3 127
13.0%
4 102
10.4%
5 83
8.5%
7 76
 
7.8%
6 72
 
7.4%
0 69
 
7.0%
8 67
 
6.8%
9 56
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
S 3
23.1%
K 3
23.1%
C 2
15.4%
B 1
 
7.7%
V 1
 
7.7%
I 1
 
7.7%
E 1
 
7.7%
W 1
 
7.7%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%
Space Separator
ValueCountFrequency (%)
1406
100.0%
Open Punctuation
ValueCountFrequency (%)
( 246
100.0%
Close Punctuation
ValueCountFrequency (%)
) 246
100.0%
Other Punctuation
ValueCountFrequency (%)
, 197
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5098
62.1%
Common 3098
37.7%
Latin 18
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 278
 
5.5%
로 271
 
5.3%
동 271
 
5.3%
천 260
 
5.1%
인 259
 
5.1%
시 258
 
5.1%
광 257
 
5.0%
구 253
 
5.0%
역 253
 
5.0%
아 152
 
3.0%
Other values (223) 2586
50.7%
Common
ValueCountFrequency (%)
1406
45.4%
( 246
 
7.9%
) 246
 
7.9%
, 197
 
6.4%
1 194
 
6.3%
2 133
 
4.3%
3 127
 
4.1%
4 102
 
3.3%
5 83
 
2.7%
7 76
 
2.5%
Other values (5) 288
 
9.3%
Latin
ValueCountFrequency (%)
S 3
16.7%
e 3
16.7%
K 3
16.7%
C 2
11.1%
B 1
 
5.6%
Ⅱ 1
 
5.6%
Ⅰ 1
 
5.6%
V 1
 
5.6%
I 1
 
5.6%
E 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5098
62.1%
ASCII 3114
37.9%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1406
45.2%
( 246
 
7.9%
) 246
 
7.9%
, 197
 
6.3%
1 194
 
6.2%
2 133
 
4.3%
3 127
 
4.1%
4 102
 
3.3%
5 83
 
2.7%
7 76
 
2.4%
Other values (14) 304
 
9.8%
Hangul
ValueCountFrequency (%)
서 278
 
5.5%
로 271
 
5.3%
동 271
 
5.3%
천 260
 
5.1%
인 259
 
5.1%
시 258
 
5.1%
광 257
 
5.0%
구 253
 
5.0%
역 253
 
5.0%
아 152
 
3.0%
Other values (223) 2586
50.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%

전화번호
Text

MISSING 

Distinct238
Distinct (%)100.0%
Missing15
Missing (%)5.9%
Memory size2.1 KiB
2024-01-28T19:24:03.208850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.033613
Min length12

Characters and Unicode

Total characters2864
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

Unique238 ?
Unique (%)100.0%

Sample

1st row032-561-2544
2nd row032-562-0122
3rd row032-561-1533
4th row032-561-8547
5th row032-564-7580
ValueCountFrequency (%)
032-563-4849 1
 
0.4%
032-263-1248 1
 
0.4%
032-565-2694 1
 
0.4%
032-567-6066 1
 
0.4%
032-562-8188 1
 
0.4%
032-266-5600 1
 
0.4%
032-563-0389 1
 
0.4%
032-564-2689 1
 
0.4%
032-274-0881 1
 
0.4%
032-565-1077 1
 
0.4%
Other values (228) 228
95.8%
2024-01-28T19:24:03.503315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 476
16.6%
2 387
13.5%
0 376
13.1%
3 372
13.0%
5 307
10.7%
6 257
9.0%
7 196
6.8%
1 135
 
4.7%
8 129
 
4.5%
4 123
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2388
83.4%
Dash Punctuation 476
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 387
16.2%
0 376
15.7%
3 372
15.6%
5 307
12.9%
6 257
10.8%
7 196
8.2%
1 135
 
5.7%
8 129
 
5.4%
4 123
 
5.2%
9 106
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 476
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2864
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 476
16.6%
2 387
13.5%
0 376
13.1%
3 372
13.0%
5 307
10.7%
6 257
9.0%
7 196
6.8%
1 135
 
4.7%
8 129
 
4.5%
4 123
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2864
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 476
16.6%
2 387
13.5%
0 376
13.1%
3 372
13.0%
5 307
10.7%
6 257
9.0%
7 196
6.8%
1 135
 
4.7%
8 129
 
4.5%
4 123
 
4.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2023-06-08 00:00:00
Maximum2023-06-08 00:00:00
2024-01-28T19:24:03.593700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:24:03.663294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-28T19:24:00.186122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T19:24:03.715636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번동명
순번1.0000.979
동명0.9791.000
2024-01-28T19:24:03.778466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번동명
순번1.0000.854
동명0.8541.000

Missing values

2024-01-28T19:24:00.279417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T19:24:00.369992image/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

순번동명경로당명우편번호소재지(지번)소재지(도로명)전화번호데이터기준일자
01검암경서동시천경로당22686인천광역시 서구 시천동 113-1인천광역시 서구 아라로105번길 1-8 (시천동)032-561-25442023-06-08
12검암경서동경서동경로당22692인천광역시 서구 경서동 744-13인천광역시 서구 경서로55번길 7 (경서동)032-562-01222023-06-08
23검암경서동검암2차풍림아파트경로당22704인천광역시 서구 검암동 501-1인천광역시 서구 검암로 53 (검암동)032-561-15332023-06-08
34검암경서동공촌경로당22698인천광역시 서구 검암동 657-4인천광역시 서구 승학로402번길 15 (검암동)032-561-85472023-06-08
45검암경서동검암1차신명아파트경로당22697인천광역시 서구 검암동 629-1인천광역시 서구 승학로 447 (검암동)032-564-75802023-06-08
56검암경서동검암2차신명아파트경로당22703인천광역시 서구 검암동 535-1인천광역시 서구 검암로10번길 54 (검암동, 검암2차신명스카이뷰)032-278-90032023-06-08
67검암경서동검암서해그랑블아파트경로당22695인천광역시 서구 검암동 595-3인천광역시 서구 승학로495번길 7 (검암동, 서해그랑블)032-263-41742023-06-08
78검암경서동삼보해피하임2차아파트경로당22703인천광역시 서구 검암동 512-1인천광역시 서구 검암로20번길 52 (검암동, 삼보해피하임)032-262-77482023-06-08
89검암경서동검암1차삼보해피하임아파트경로당22697인천광역시 서구 검암동 628인천광역시 서구 승학로 457 (검암동, 삼보해피하임)032-565-56102023-06-08
910검암경서동풍림아이원1차아파트경로당22703인천광역시 서구 검암동 511인천광역시 서구 검암로20번길 47 (검암동, 풍림아이원)032-562-07462023-06-08
순번동명경로당명우편번호소재지(지번)소재지(도로명)전화번호데이터기준일자
243244마전동검단1차대주피오레아파트경로당22638인천광역시 서구 마전동 1029-2인천광역시 서구 완정로65번안길 10 (마전동, 검단1차 대주피오레아파트)032-201-84542023-06-08
244245마전동우림필유경로당22640인천광역시 서구 마전동 999-8인천광역시 서구 완정로34번길 29 (마전동, 검단우림필유아파트)032-566-04042023-06-08
245246마전동검단2차아이파크경로당22640인천광역시 서구 마전동 999-1인천광역시 서구 검단로540번길 59 (마전동, 검단2차아이파크)032-565-39932023-06-08
246247아라동검단LH20단지아파트경로당404-320인천광역시 서구 원당동 1096인천광역시 서구 이음3로 220<NA>2023-06-08
247248아라동검단신도시우미린더시그니처아파트경로당22867인천광역시 서구 원당동 검단신도시 AB15-1인천광역시 서구 이음5로 39<NA>2023-06-08
248249아라동검단한신더휴아파트경로당22868인천광역시 서구 당하동 1254-1인천광역시 서구 이음3로 125<NA>2023-06-08
249250아라동호반써밋1차아파트경로당22867인천광역시 서구 원당동 1022인천광역시 서구 이음5로 15<NA>2023-06-08
250251아라동검단푸르지오더베뉴아파트경로당22868인천광역시 서구 원당동 163인천광역시 서구 이음6로 33<NA>2023-06-08
251252아라동검단유승한내들에듀파크아파트경로당404-818인천광역시 서구 당하동 259-16인천광역시 서구 이음3로 130<NA>2023-06-08
252253아라동검단금호어울림센트럴아파트경로당22864인천광역시 서구 원당동 검단신도시 AB-14BL인천광역시 서구 이음5로 65<NA>2023-06-08