Overview

Dataset statistics

Number of variables11
Number of observations5385
Missing cells8904
Missing cells (%)15.0%
Duplicate rows545
Duplicate rows (%)10.1%
Total size in memory489.2 KiB
Average record size in memory93.0 B

Variable types

Text4
Categorical1
Numeric5
DateTime1

Dataset

Description충청북도 단양군의 도시계획정보시스템(UPIS) 내 보유중인 용도구역 결정조서 데이터로 소분류 세분명, 지역명, 규모 등급, 폭, 선혛 연장 기정, 선형연장 변경후, 선형 면적 기정, 선형면적 변경후, 기점, 종점 등의 항목을 포함하고 있음.
Author충청북도 단양군
URLhttps://www.data.go.kr/data/15123402/fileData.do

Alerts

Dataset has 545 (10.1%) duplicate rowsDuplicates
폭 is highly overall correlated with 선형_연장_변경후 and 3 other fieldsHigh correlation
선형_연장_기정 is highly overall correlated with 선형_면적_기정High correlation
선형_연장_변경후 is highly overall correlated with 폭 and 2 other fieldsHigh correlation
선형_면적_기정 is highly overall correlated with 폭 and 3 other fieldsHigh correlation
선형_면적_변경후 is highly overall correlated with 폭 and 2 other fieldsHigh correlation
규모_등급 is highly overall correlated with 폭High correlation
폭 has 852 (15.8%) missing valuesMissing
선형_연장_기정 has 1599 (29.7%) missing valuesMissing
선형_연장_변경후 has 868 (16.1%) missing valuesMissing
선형_면적_기정 has 1338 (24.8%) missing valuesMissing
선형_면적_변경후 has 1353 (25.1%) missing valuesMissing
기점 has 1442 (26.8%) missing valuesMissing
종점 has 1452 (27.0%) missing valuesMissing
선형_면적_기정 is highly skewed (γ1 = 26.64279351)Skewed
선형_면적_변경후 is highly skewed (γ1 = 21.48648376)Skewed
폭 has 673 (12.5%) zerosZeros
선형_연장_기정 has 2429 (45.1%) zerosZeros
선형_연장_변경후 has 907 (16.8%) zerosZeros
선형_면적_기정 has 1426 (26.5%) zerosZeros
선형_면적_변경후 has 774 (14.4%) zerosZeros

Reproduction

Analysis started2023-12-12 00:45:57.734817
Analysis finished2023-12-12 00:46:02.586860
Duration4.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

소분류 세분명
Text

Distinct67
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size42.2 KiB
2023-12-12T09:46:02.769853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length4
Mean length4.5448468
Min length2

Characters and Unicode

Total characters24474
Distinct characters90
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)0.1%

Sample

1st row소로2류
2nd row소로2류
3rd row소로2류
4th row소로2류
5th row소로2류
ValueCountFrequency (%)
소로3류 1850
31.5%
소로2류 991
16.9%
기타 482
 
8.2%
소로1류 379
 
6.5%
유원지시설 317
 
5.4%
중로3류 259
 
4.4%
어린이공원 210
 
3.6%
근린공원 131
 
2.2%
중로2류 116
 
2.0%
교통광장시설 100
 
1.7%
Other values (58) 1032
17.6%
2023-12-12T09:46:03.148576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
류 3857
15.8%
로 3845
15.7%
소 3303
13.5%
3 2161
 
8.8%
2 1107
 
4.5%
시 809
 
3.3%
원 792
 
3.2%
설 760
 
3.1%
기 669
 
2.7%
타 654
 
2.7%
Other values (80) 6517
26.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20146
82.3%
Decimal Number 3844
 
15.7%
Space Separator 482
 
2.0%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
류 3857
19.1%
로 3845
19.1%
소 3303
16.4%
시 809
 
4.0%
원 792
 
3.9%
설 760
 
3.8%
기 669
 
3.3%
타 654
 
3.2%
공 497
 
2.5%
중 495
 
2.5%
Other values (73) 4465
22.2%
Decimal Number
ValueCountFrequency (%)
3 2161
56.2%
2 1107
28.8%
1 494
 
12.9%
4 82
 
2.1%
Space Separator
ValueCountFrequency (%)
482
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20146
82.3%
Common 4328
 
17.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
류 3857
19.1%
로 3845
19.1%
소 3303
16.4%
시 809
 
4.0%
원 792
 
3.9%
설 760
 
3.8%
기 669
 
3.3%
타 654
 
3.2%
공 497
 
2.5%
중 495
 
2.5%
Other values (73) 4465
22.2%
Common
ValueCountFrequency (%)
3 2161
49.9%
2 1107
25.6%
1 494
 
11.4%
482
 
11.1%
4 82
 
1.9%
( 1
 
< 0.1%
) 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20146
82.3%
ASCII 4328
 
17.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
류 3857
19.1%
로 3845
19.1%
소 3303
16.4%
시 809
 
4.0%
원 792
 
3.9%
설 760
 
3.8%
기 669
 
3.3%
타 654
 
3.2%
공 497
 
2.5%
중 495
 
2.5%
Other values (73) 4465
22.2%
ASCII
ValueCountFrequency (%)
3 2161
49.9%
2 1107
25.6%
1 494
 
11.4%
482
 
11.1%
4 82
 
1.9%
( 1
 
< 0.1%
) 1
 
< 0.1%

지역명
Text

Distinct934
Distinct (%)17.3%
Missing0
Missing (%)0.0%
Memory size42.2 KiB
2023-12-12T09:46:03.438955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length8.2308264
Min length4

Characters and Unicode

Total characters44323
Distinct characters238
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique335 ?
Unique (%)6.2%

Sample

1st row소로2-21
2nd row소로2-22
3rd row소로2-23
4th row소로2-24
5th row소로2-25
ValueCountFrequency (%)
기타 466
 
7.7%
수양개 65
 
1.1%
소로3-2 64
 
1.1%
소로3-3 64
 
1.1%
소로3-4 61
 
1.0%
소로3-1 60
 
1.0%
소로2-1 60
 
1.0%
소로3-6 59
 
1.0%
소로2-2 56
 
0.9%
소로3-5 56
 
0.9%
Other values (952) 5021
83.2%
2023-12-12T09:46:03.942464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 4064
 
9.2%
로 3889
 
8.8%
소 3392
 
7.7%
3 3144
 
7.1%
1 2638
 
6.0%
2 2479
 
5.6%
/ 1538
 
3.5%
) 1353
 
3.1%
( 1353
 
3.1%
시 1242
 
2.8%
Other values (228) 19231
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23204
52.4%
Decimal Number 11815
26.7%
Dash Punctuation 4064
 
9.2%
Other Punctuation 1865
 
4.2%
Close Punctuation 1353
 
3.1%
Open Punctuation 1353
 
3.1%
Space Separator 647
 
1.5%
Uppercase Letter 21
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 3889
16.8%
소 3392
 
14.6%
시 1242
 
5.4%
설 1188
 
5.1%
원 1103
 
4.8%
공 787
 
3.4%
기 664
 
2.9%
장 643
 
2.8%
타 639
 
2.8%
지 596
 
2.6%
Other values (201) 9061
39.0%
Decimal Number
ValueCountFrequency (%)
3 3144
26.6%
1 2638
22.3%
2 2479
21.0%
4 850
 
7.2%
5 627
 
5.3%
6 525
 
4.4%
7 504
 
4.3%
8 413
 
3.5%
9 328
 
2.8%
0 307
 
2.6%
Other Punctuation
ValueCountFrequency (%)
/ 1538
82.5%
: 322
 
17.3%
· 2
 
0.1%
& 1
 
0.1%
. 1
 
0.1%
, 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
A 11
52.4%
B 4
 
19.0%
C 2
 
9.5%
K 2
 
9.5%
D 1
 
4.8%
V 1
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 4064
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1353
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1353
100.0%
Space Separator
ValueCountFrequency (%)
647
100.0%
Lowercase Letter
ValueCountFrequency (%)
v 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23204
52.4%
Common 21097
47.6%
Latin 22
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 3889
16.8%
소 3392
 
14.6%
시 1242
 
5.4%
설 1188
 
5.1%
원 1103
 
4.8%
공 787
 
3.4%
기 664
 
2.9%
장 643
 
2.8%
타 639
 
2.8%
지 596
 
2.6%
Other values (201) 9061
39.0%
Common
ValueCountFrequency (%)
- 4064
19.3%
3 3144
14.9%
1 2638
12.5%
2 2479
11.8%
/ 1538
 
7.3%
) 1353
 
6.4%
( 1353
 
6.4%
4 850
 
4.0%
647
 
3.1%
5 627
 
3.0%
Other values (10) 2404
11.4%
Latin
ValueCountFrequency (%)
A 11
50.0%
B 4
 
18.2%
C 2
 
9.1%
K 2
 
9.1%
D 1
 
4.5%
v 1
 
4.5%
V 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23204
52.4%
ASCII 21117
47.6%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 4064
19.2%
3 3144
14.9%
1 2638
12.5%
2 2479
11.7%
/ 1538
 
7.3%
) 1353
 
6.4%
( 1353
 
6.4%
4 850
 
4.0%
647
 
3.1%
5 627
 
3.0%
Other values (16) 2424
11.5%
Hangul
ValueCountFrequency (%)
로 3889
16.8%
소 3392
 
14.6%
시 1242
 
5.4%
설 1188
 
5.1%
원 1103
 
4.8%
공 787
 
3.4%
기 664
 
2.9%
장 643
 
2.8%
타 639
 
2.8%
지 596
 
2.6%
Other values (201) 9061
39.0%
None
ValueCountFrequency (%)
· 2
100.0%

규모_등급
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.2 KiB
소로
3317 
<NA>
1525 
중로
463 
대로
 
79
31836.8
 
1

Length

Max length7
Median length2
Mean length2.5673166
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
소로 3317
61.6%
<NA> 1525
28.3%
중로 463
 
8.6%
대로 79
 
1.5%
31836.8 1
 
< 0.1%

Length

2023-12-12T09:46:04.104813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:46:04.248875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소로 3317
61.6%
na 1525
28.3%
중로 463
 
8.6%
대로 79
 
1.5%
31836.8 1
 
< 0.1%

폭
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct34
Distinct (%)0.8%
Missing852
Missing (%)15.8%
Infinite0
Infinite (%)0.0%
Mean7.0842268
Minimum0
Maximum50
Zeros673
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size47.5 KiB
2023-12-12T09:46:04.427168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median6
Q38
95-th percentile15
Maximum50
Range50
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.0488443
Coefficient of variation (CV)0.71268813
Kurtosis10.187453
Mean7.0842268
Median Absolute Deviation (MAD)2
Skewness2.0910178
Sum32112.8
Variance25.490829
MonotonicityNot monotonic
2023-12-12T09:46:04.617770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
6.0 1700
31.6%
8.0 973
18.1%
0.0 673
 
12.5%
10.0 388
 
7.2%
12.0 223
 
4.1%
4.0 157
 
2.9%
15.0 113
 
2.1%
20.0 85
 
1.6%
25.0 49
 
0.9%
35.0 27
 
0.5%
Other values (24) 145
 
2.7%
(Missing) 852
15.8%
ValueCountFrequency (%)
0.0 673
 
12.5%
1.5 2
 
< 0.1%
2.0 19
 
0.4%
3.0 9
 
0.2%
3.9 2
 
< 0.1%
4.0 157
 
2.9%
5.0 15
 
0.3%
5.5 1
 
< 0.1%
6.0 1700
31.6%
7.0 24
 
0.4%
ValueCountFrequency (%)
50.0 3
 
0.1%
44.5 1
 
< 0.1%
35.0 27
 
0.5%
30.0 1
 
< 0.1%
25.0 49
0.9%
23.0 2
 
< 0.1%
20.0 85
1.6%
18.0 1
 
< 0.1%
17.0 1
 
< 0.1%
16.0 4
 
0.1%

선형_연장_기정
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct410
Distinct (%)10.8%
Missing1599
Missing (%)29.7%
Infinite0
Infinite (%)0.0%
Mean298.50053
Minimum0
Maximum42865
Zeros2429
Zeros (%)45.1%
Negative0
Negative (%)0.0%
Memory size47.5 KiB
2023-12-12T09:46:04.813473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3100
95-th percentile574.5
Maximum42865
Range42865
Interquartile range (IQR)100

Descriptive statistics

Standard deviation1916.5477
Coefficient of variation (CV)6.420584
Kurtosis157.24793
Mean298.50053
Median Absolute Deviation (MAD)0
Skewness11.46667
Sum1130123
Variance3673155.1
MonotonicityNot monotonic
2023-12-12T09:46:04.968539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2429
45.1%
73 21
 
0.4%
185 17
 
0.3%
71 14
 
0.3%
124 14
 
0.3%
102 13
 
0.2%
32 12
 
0.2%
260 12
 
0.2%
262 12
 
0.2%
186 12
 
0.2%
Other values (400) 1230
22.8%
(Missing) 1599
29.7%
ValueCountFrequency (%)
0 2429
45.1%
3 1
 
< 0.1%
10 1
 
< 0.1%
13 2
 
< 0.1%
14 3
 
0.1%
15 1
 
< 0.1%
18 1
 
< 0.1%
22 2
 
< 0.1%
25 1
 
< 0.1%
26 2
 
< 0.1%
ValueCountFrequency (%)
42865 1
 
< 0.1%
28794 2
< 0.1%
25179 2
< 0.1%
21848 2
< 0.1%
20730 2
< 0.1%
20720 1
 
< 0.1%
20715 2
< 0.1%
20658 3
0.1%
19228 4
0.1%
18229 1
 
< 0.1%

선형_연장_변경후
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct632
Distinct (%)14.0%
Missing868
Missing (%)16.1%
Infinite0
Infinite (%)0.0%
Mean574.10275
Minimum0
Maximum42865
Zeros907
Zeros (%)16.8%
Negative0
Negative (%)0.0%
Memory size47.5 KiB
2023-12-12T09:46:05.167391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q147
median122
Q3268
95-th percentile1600
Maximum42865
Range42865
Interquartile range (IQR)221

Descriptive statistics

Standard deviation2384.8807
Coefficient of variation (CV)4.1541009
Kurtosis111.34375
Mean574.10275
Median Absolute Deviation (MAD)111
Skewness9.3449558
Sum2593222.1
Variance5687656.1
MonotonicityNot monotonic
2023-12-12T09:46:05.347494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 907
 
16.8%
146.0 45
 
0.8%
73.0 39
 
0.7%
122.0 37
 
0.7%
110.0 36
 
0.7%
50.0 33
 
0.6%
70.0 32
 
0.6%
100.0 32
 
0.6%
185.0 31
 
0.6%
71.0 30
 
0.6%
Other values (622) 3295
61.2%
(Missing) 868
 
16.1%
ValueCountFrequency (%)
0.0 907
16.8%
3.0 2
 
< 0.1%
11.0 3
 
0.1%
13.0 1
 
< 0.1%
14.0 6
 
0.1%
15.0 2
 
< 0.1%
17.0 1
 
< 0.1%
18.0 3
 
0.1%
20.0 1
 
< 0.1%
22.0 1
 
< 0.1%
ValueCountFrequency (%)
42865.0 3
0.1%
28794.0 3
0.1%
25179.0 3
0.1%
21848.0 3
0.1%
20730.0 3
0.1%
20720.0 1
 
< 0.1%
20715.0 2
< 0.1%
20659.0 1
 
< 0.1%
20658.0 3
0.1%
20459.0 1
 
< 0.1%

선형_면적_기정
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct741
Distinct (%)18.3%
Missing1338
Missing (%)24.8%
Infinite0
Infinite (%)0.0%
Mean15808.343
Minimum0
Maximum7048140
Zeros1426
Zeros (%)26.5%
Negative0
Negative (%)0.0%
Memory size47.5 KiB
2023-12-12T09:46:05.528304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median560
Q31698
95-th percentile17400
Maximum7048140
Range7048140
Interquartile range (IQR)1698

Descriptive statistics

Standard deviation224239.11
Coefficient of variation (CV)14.184858
Kurtosis769.19575
Mean15808.343
Median Absolute Deviation (MAD)560
Skewness26.642794
Sum63976364
Variance5.0283177 × 1010
MonotonicityNot monotonic
2023-12-12T09:46:05.703671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1426
26.5%
876.0 29
 
0.5%
660.0 22
 
0.4%
732.0 22
 
0.4%
408.0 22
 
0.4%
1850.0 20
 
0.4%
480.0 19
 
0.4%
840.0 18
 
0.3%
420.0 16
 
0.3%
384.0 16
 
0.3%
Other values (731) 2437
45.3%
(Missing) 1338
24.8%
ValueCountFrequency (%)
0.0 1426
26.5%
15.0 1
 
< 0.1%
21.0 1
 
< 0.1%
27.0 1
 
< 0.1%
29.0 1
 
< 0.1%
42.0 1
 
< 0.1%
44.0 2
 
< 0.1%
48.0 1
 
< 0.1%
55.0 1
 
< 0.1%
56.0 4
 
0.1%
ValueCountFrequency (%)
7048140.0 2
< 0.1%
6172557.0 2
< 0.1%
2722500.0 2
< 0.1%
1439700.0 2
< 0.1%
1302023.0 1
< 0.1%
1100300.0 2
< 0.1%
1089919.0 1
< 0.1%
414600.0 2
< 0.1%
414400.0 2
< 0.1%
414300.0 2
< 0.1%

선형_면적_변경후
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct841
Distinct (%)20.9%
Missing1353
Missing (%)25.1%
Infinite0
Infinite (%)0.0%
Mean23386.293
Minimum0
Maximum7048140
Zeros774
Zeros (%)14.4%
Negative0
Negative (%)0.0%
Memory size47.5 KiB
2023-12-12T09:46:05.906105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1300
median876
Q32109.5
95-th percentile24667.5
Maximum7048140
Range7048140
Interquartile range (IQR)1809.5

Descriptive statistics

Standard deviation275940.59
Coefficient of variation (CV)11.799245
Kurtosis501.84231
Mean23386.293
Median Absolute Deviation (MAD)876
Skewness21.486484
Sum94293533
Variance7.6143211 × 1010
MonotonicityNot monotonic
2023-12-12T09:46:06.392445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 774
 
14.4%
876.0 34
 
0.6%
732.0 26
 
0.5%
660.0 26
 
0.5%
1850.0 25
 
0.5%
408.0 25
 
0.5%
480.0 23
 
0.4%
192.0 20
 
0.4%
384.0 19
 
0.4%
462.0 18
 
0.3%
Other values (831) 3042
56.5%
(Missing) 1353
25.1%
ValueCountFrequency (%)
0.0 774
14.4%
15.0 2
 
< 0.1%
36.0 2
 
< 0.1%
42.0 1
 
< 0.1%
44.0 2
 
< 0.1%
56.0 5
 
0.1%
75.0 3
 
0.1%
96.0 4
 
0.1%
108.0 1
 
< 0.1%
112.0 1
 
< 0.1%
ValueCountFrequency (%)
7048140.0 3
0.1%
6172557.0 3
0.1%
2722500.0 3
0.1%
1439700.0 3
0.1%
1302023.0 3
0.1%
1100300.0 2
< 0.1%
1089919.0 3
0.1%
414600.0 3
0.1%
414445.0 1
 
< 0.1%
414400.0 1
 
< 0.1%

기점
Text

MISSING 

Distinct1999
Distinct (%)50.7%
Missing1442
Missing (%)26.8%
Memory size42.2 KiB
2023-12-12T09:46:06.729958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length10.78874
Min length2

Characters and Unicode

Total characters42540
Distinct characters141
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

Unique1457 ?
Unique (%)37.0%

Sample

1st row하시리193
2nd row하시리199
3rd row하시리204-2
4th row하시리210-5
5th row하시리147-2
ValueCountFrequency (%)
대로3-1 289
 
4.1%
중로1-1 251
 
3.6%
대로1-1 173
 
2.4%
중로2-2 153
 
2.2%
장림 116
 
1.6%
평동리 104
 
1.5%
중로2-3 101
 
1.4%
중로2-1 98
 
1.4%
소로2-1 89
 
1.3%
중로3-3 84
 
1.2%
Other values (1815) 5606
79.4%
2023-12-12T09:46:07.273343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 4950
 
11.6%
1 4713
 
11.1%
로 3230
 
7.6%
3121
 
7.3%
3 2988
 
7.0%
2 2868
 
6.7%
리 2192
 
5.2%
중 1377
 
3.2%
소 1356
 
3.2%
4 1229
 
2.9%
Other values (131) 14516
34.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16165
38.0%
Other Letter 15645
36.8%
Dash Punctuation 4950
 
11.6%
Space Separator 3121
 
7.3%
Other Punctuation 1054
 
2.5%
Close Punctuation 800
 
1.9%
Open Punctuation 798
 
1.9%
Uppercase Letter 6
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 3230
20.6%
리 2192
14.0%
중 1377
 
8.8%
소 1356
 
8.7%
대 739
 
4.7%
평 586
 
3.7%
동 543
 
3.5%
도 509
 
3.3%
장 347
 
2.2%
담 331
 
2.1%
Other values (112) 4435
28.3%
Decimal Number
ValueCountFrequency (%)
1 4713
29.2%
3 2988
18.5%
2 2868
17.7%
4 1229
 
7.6%
6 939
 
5.8%
5 778
 
4.8%
7 745
 
4.6%
0 658
 
4.1%
9 647
 
4.0%
8 600
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 1053
99.9%
? 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
A 3
50.0%
B 3
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 4950
100.0%
Space Separator
ValueCountFrequency (%)
3121
100.0%
Close Punctuation
ValueCountFrequency (%)
) 800
100.0%
Open Punctuation
ValueCountFrequency (%)
( 798
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26889
63.2%
Hangul 15645
36.8%
Latin 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 3230
20.6%
리 2192
14.0%
중 1377
 
8.8%
소 1356
 
8.7%
대 739
 
4.7%
평 586
 
3.7%
동 543
 
3.5%
도 509
 
3.3%
장 347
 
2.2%
담 331
 
2.1%
Other values (112) 4435
28.3%
Common
ValueCountFrequency (%)
- 4950
18.4%
1 4713
17.5%
3121
11.6%
3 2988
11.1%
2 2868
10.7%
4 1229
 
4.6%
, 1053
 
3.9%
6 939
 
3.5%
) 800
 
3.0%
( 798
 
3.0%
Other values (7) 3430
12.8%
Latin
ValueCountFrequency (%)
A 3
50.0%
B 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26895
63.2%
Hangul 15645
36.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 4950
18.4%
1 4713
17.5%
3121
11.6%
3 2988
11.1%
2 2868
10.7%
4 1229
 
4.6%
, 1053
 
3.9%
6 939
 
3.5%
) 800
 
3.0%
( 798
 
3.0%
Other values (9) 3436
12.8%
Hangul
ValueCountFrequency (%)
로 3230
20.6%
리 2192
14.0%
중 1377
 
8.8%
소 1356
 
8.7%
대 739
 
4.7%
평 586
 
3.7%
동 543
 
3.5%
도 509
 
3.3%
장 347
 
2.2%
담 331
 
2.1%
Other values (112) 4435
28.3%

종점
Text

MISSING 

Distinct2153
Distinct (%)54.7%
Missing1452
Missing (%)27.0%
Memory size42.2 KiB
2023-12-12T09:46:07.642656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length10.848207
Min length2

Characters and Unicode

Total characters42666
Distinct characters173
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

Unique1566 ?
Unique (%)39.8%

Sample

1st row하시리173-5
2nd row하시리202
3rd row하시리204-2
4th row하시리207
5th row하시리 산
ValueCountFrequency (%)
장림 124
 
1.8%
평동리 123
 
1.7%
소로2-1 103
 
1.5%
중로3-2 79
 
1.1%
중로2-1 72
 
1.0%
소로3-1 72
 
1.0%
중로1-1 67
 
0.9%
하리 66
 
0.9%
임현리 59
 
0.8%
상리 59
 
0.8%
Other values (2006) 6255
88.4%
2023-12-12T09:46:08.175661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 4580
 
10.7%
1 3779
 
8.9%
3 3213
 
7.5%
3146
 
7.4%
로 2897
 
6.8%
2 2631
 
6.2%
리 2256
 
5.3%
소 2014
 
4.7%
4 1513
 
3.5%
5 1052
 
2.5%
Other values (163) 15585
36.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16265
38.1%
Decimal Number 16132
37.8%
Dash Punctuation 4580
 
10.7%
Space Separator 3146
 
7.4%
Other Punctuation 934
 
2.2%
Open Punctuation 802
 
1.9%
Close Punctuation 801
 
1.9%
Uppercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 2897
17.8%
리 2256
13.9%
소 2014
 
12.4%
중 883
 
5.4%
동 600
 
3.7%
평 594
 
3.7%
도 546
 
3.4%
담 353
 
2.2%
하 349
 
2.1%
계 330
 
2.0%
Other values (146) 5443
33.5%
Decimal Number
ValueCountFrequency (%)
1 3779
23.4%
3 3213
19.9%
2 2631
16.3%
4 1513
9.4%
5 1052
 
6.5%
7 909
 
5.6%
6 894
 
5.5%
0 723
 
4.5%
9 709
 
4.4%
8 709
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
C 5
83.3%
A 1
 
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 4580
100.0%
Space Separator
ValueCountFrequency (%)
3146
100.0%
Other Punctuation
ValueCountFrequency (%)
, 934
100.0%
Open Punctuation
ValueCountFrequency (%)
( 802
100.0%
Close Punctuation
ValueCountFrequency (%)
) 801
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26395
61.9%
Hangul 16265
38.1%
Latin 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 2897
17.8%
리 2256
13.9%
소 2014
 
12.4%
중 883
 
5.4%
동 600
 
3.7%
평 594
 
3.7%
도 546
 
3.4%
담 353
 
2.2%
하 349
 
2.1%
계 330
 
2.0%
Other values (146) 5443
33.5%
Common
ValueCountFrequency (%)
- 4580
17.4%
1 3779
14.3%
3 3213
12.2%
3146
11.9%
2 2631
10.0%
4 1513
 
5.7%
5 1052
 
4.0%
, 934
 
3.5%
7 909
 
3.4%
6 894
 
3.4%
Other values (5) 3744
14.2%
Latin
ValueCountFrequency (%)
C 5
83.3%
A 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26401
61.9%
Hangul 16265
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 4580
17.3%
1 3779
14.3%
3 3213
12.2%
3146
11.9%
2 2631
10.0%
4 1513
 
5.7%
5 1052
 
4.0%
, 934
 
3.5%
7 909
 
3.4%
6 894
 
3.4%
Other values (7) 3750
14.2%
Hangul
ValueCountFrequency (%)
로 2897
17.8%
리 2256
13.9%
소 2014
 
12.4%
중 883
 
5.4%
동 600
 
3.7%
평 594
 
3.7%
도 546
 
3.4%
담 353
 
2.2%
하 349
 
2.1%
계 330
 
2.0%
Other values (146) 5443
33.5%

시스템 생성일시
Date

Distinct34
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size42.2 KiB
Minimum2016-12-06 00:00:00
Maximum2023-06-22 00:00:00
2023-12-12T09:46:08.355749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:08.500273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

Interactions

2023-12-12T09:46:01.516758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:45:59.135333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:45:59.757539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:00.378816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:00.920309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:01.606196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:45:59.246142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:45:59.883588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:00.477738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:01.044132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:01.717245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:45:59.364306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:45:59.984770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:00.587907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:01.161990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:01.829518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:45:59.483697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:00.118471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:00.683484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:01.284872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:01.952195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:45:59.622975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:00.275268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:00.802468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:46:01.404351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:46:08.580793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소분류 세분명규모_등급폭선형_연장_기정선형_연장_변경후선형_면적_기정선형_면적_변경후시스템 생성일시
소분류 세분명1.0000.9260.9800.6070.7510.6270.7300.854
규모_등급0.9261.0000.9930.3600.4750.0980.1200.254
폭0.9800.9931.0000.6150.7090.6070.7100.410
선형_연장_기정0.6070.3600.6151.0000.9710.8540.7620.663
선형_연장_변경후0.7510.4750.7090.9711.0000.7570.8610.568
선형_면적_기정0.6270.0980.6070.8540.7571.0000.9820.288
선형_면적_변경후0.7300.1200.7100.7620.8610.9821.0000.218
시스템 생성일시0.8540.2540.4100.6630.5680.2880.2181.000
2023-12-12T09:46:08.709043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폭선형_연장_기정선형_연장_변경후선형_면적_기정선형_면적_변경후규모_등급
폭1.0000.3230.5780.5530.7350.988
선형_연장_기정0.3231.0000.1890.5420.3040.260
선형_연장_변경후0.5780.1891.0000.6090.9720.362
선형_면적_기정0.5530.5420.6091.0000.6070.162
선형_면적_변경후0.7350.3040.9720.6071.0000.199
규모_등급0.9880.2600.3620.1620.1991.000

Missing values

2023-12-12T09:46:02.087697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:46:02.279438image/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.
2023-12-12T09:46:02.440256image/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

소분류 세분명지역명규모_등급폭선형_연장_기정선형_연장_변경후선형_면적_기정선형_면적_변경후기점종점시스템 생성일시
0소로2류소로2-21소로8.00904.07232.07232.0하시리193하시리173-52016-12-06
1소로2류소로2-22소로8.0054.0432.0432.0하시리199하시리2022016-12-06
2소로2류소로2-23소로8.0054.0432.0432.0하시리204-2하시리204-22016-12-06
3소로2류소로2-24소로8.0054.0432.0432.0하시리210-5하시리2072016-12-06
4소로2류소로2-25소로8.0054.0432.0432.0하시리147-2하시리 산2016-12-06
5소로2류소로2-26소로8.0054.0432.0432.0하시리154-1하시리 산2016-12-06
6소로2류소로2-27소로8.00621.04968.04968.0하시리157-6하시리371-1112016-12-06
7소로2류소로2-28소로8.0032.0256.0256.0하시리371-111하시리162-22016-12-06
8소로2류소로2-29소로8.00420.03360.03360.0평동221평동705-12016-12-06
9소로2류소로2-30소로8.00115.0920.0920.0평동240-23평동2222016-12-06
소분류 세분명지역명규모_등급폭선형_연장_기정선형_연장_변경후선형_면적_기정선형_면적_변경후기점종점시스템 생성일시
5375소로2류소로2-13소로8.0<NA>720.04480.05760.0중로1-1중로2-22016-12-06
5376소로2류소로2-7소로8.0<NA>352.02848.02816.0대로1-1평동리625답2016-12-06
5377소로2류소로2-8소로8.0<NA>238.01920.01904.0소로2-7중로2-22016-12-06
5378소로2류소로2-9소로8.0<NA>226.01856.01808.0중로1-1소로2-72016-12-06
5379중로3류중로3-4중로12.00560.00.06720.0대로1-1, 하시리하시리구역계2016-12-06
5380중로3류중로3-3중로12.0<NA>510.06120.06120.0대로1-1, 평동리중로3-22016-12-06
5381중로3류중로3-1중로12.0<NA><NA>7320.00.0중로2-3, 하괴리하괴리구역계2016-12-06
5382중로3류중로3-2중로12.0<NA>294.03480.03480.0중로2-2, 평동리소로3-18, 평동리2016-12-06
5383중로2류중로2-3중로15.0<NA>410.023355.06150.0대로3-2도담공원2016-12-06
5384중로2류중로2-4중로15.0<NA>384.05850.05760.0중로1-1대로1-12016-12-06

Duplicate rows

Most frequently occurring

소분류 세분명지역명규모_등급폭선형_연장_기정선형_연장_변경후선형_면적_기정선형_면적_변경후기점종점시스템 생성일시# duplicates
69기타 유원지시설기타 유원지시설/(세부시설:편익및관리시설)<NA>0.000.00.00.0<NA><NA>2016-12-0611
74기타 유원지시설기타 유원지시설/(세부시설:휴양시설)<NA>0.000.00.00.0<NA><NA>2016-12-0611
36기타 교통광장시설기타 교통광장시설/1(광장)<NA>0.000.00.00.0<NA><NA>2016-12-069
200도시자연공원도시자연공원/1(도담공원)<NA>0.000.00.00.0<NA><NA>2016-12-068
473역전광장역전광장/1<NA>0.000.00.00.0<NA><NA>2016-12-068
39기타 교통광장시설기타 교통광장시설/2(광장)<NA>0.000.00.00.0<NA><NA>2016-12-067
77기타 유원지시설기타 유원지시설/1(도담삼봉 유원지)<NA>0.000.00.00.0<NA><NA>2016-12-067
149기타공원시설기타공원시설/1(공원)<NA>0.000.00.00.0<NA><NA>2016-12-067
533초등학교초등학교/1(학교)<NA>0.000.00.00.0<NA><NA>2016-12-067
57기타 시장시설기타 시장시설/1(시장)<NA>0.000.00.00.0<NA><NA>2016-12-066