Overview

Dataset statistics

Number of variables9
Number of observations621
Missing cells10
Missing cells (%)0.2%
Duplicate rows112
Duplicate rows (%)18.0%
Total size in memory45.0 KiB
Average record size in memory74.2 B

Variable types

Categorical1
Text5
Numeric2
DateTime1

Dataset

Description안양시 내 사업장 폐기물이 발생한 업체들의 배출 신고 현황(시군명, 상호명, 소재지도로명주소, 소재지지번주소, 위도, 경도, 인허가관리번호, 인허가등록일자, 배출폐기물종류)입니다. 폐기물관리법 제 17조에 근거한 사업장 폐기물 배출자 신고 현황 및 내용입니다.
URLhttps://www.data.go.kr/data/15114685/fileData.do

Alerts

시군명 has constant value ""Constant
Dataset has 112 (18.0%) duplicate rowsDuplicates
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
소재지도로명주소 has 7 (1.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 13:34:29.684404
Analysis finished2023-12-12 13:34:30.893146
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
안양시
621 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안양시 621
100.0%

Length

2023-12-12T22:34:30.975962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:34:31.085462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안양시 621
100.0%

상호명
Text

Distinct149
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T22:34:31.277504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length9.178744
Min length4

Characters and Unicode

Total characters5700
Distinct characters247
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

Unique53 ?
Unique (%)8.5%

Sample

1st row삼영운수(주)충훈부영업소
2nd row주식회사 엘지유플러스
3rd row주식회사 샘빌
4th row농업회사법인(주)금천축산유통
5th row주식회사 파인엠텍
ValueCountFrequency (%)
주)노루페인트 61
 
8.5%
주)오뚜기 26
 
3.6%
공공하수처리시설(안양 25
 
3.5%
주식회사 19
 
2.6%
공공하수처리시설(석수 17
 
2.4%
엘에스엠트론(주 16
 
2.2%
홈플러스(주 16
 
2.2%
안양공장 16
 
2.2%
주)정선골재 15
 
2.1%
주)효성 15
 
2.1%
Other values (153) 492
68.5%
2023-12-12T22:34:31.717698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 423
 
7.4%
) 423
 
7.4%
주 401
 
7.0%
양 209
 
3.7%
안 197
 
3.5%
시 116
 
2.0%
공 114
 
2.0%
97
 
1.7%
트 95
 
1.7%
원 91
 
1.6%
Other values (237) 3534
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4684
82.2%
Open Punctuation 423
 
7.4%
Close Punctuation 423
 
7.4%
Space Separator 97
 
1.7%
Uppercase Letter 47
 
0.8%
Decimal Number 22
 
0.4%
Other Punctuation 3
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 401
 
8.6%
양 209
 
4.5%
안 197
 
4.2%
시 116
 
2.5%
공 114
 
2.4%
트 95
 
2.0%
원 91
 
1.9%
수 87
 
1.9%
인 86
 
1.8%
리 81
 
1.7%
Other values (219) 3207
68.5%
Uppercase Letter
ValueCountFrequency (%)
G 15
31.9%
S 11
23.4%
K 5
 
10.6%
V 5
 
10.6%
C 5
 
10.6%
P 2
 
4.3%
L 2
 
4.3%
R 1
 
2.1%
D 1
 
2.1%
Decimal Number
ValueCountFrequency (%)
3 10
45.5%
2 5
22.7%
6 5
22.7%
5 2
 
9.1%
Open Punctuation
ValueCountFrequency (%)
( 423
100.0%
Close Punctuation
ValueCountFrequency (%)
) 423
100.0%
Space Separator
ValueCountFrequency (%)
97
100.0%
Other Punctuation
ValueCountFrequency (%)
& 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4684
82.2%
Common 969
 
17.0%
Latin 47
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 401
 
8.6%
양 209
 
4.5%
안 197
 
4.2%
시 116
 
2.5%
공 114
 
2.4%
트 95
 
2.0%
원 91
 
1.9%
수 87
 
1.9%
인 86
 
1.8%
리 81
 
1.7%
Other values (219) 3207
68.5%
Common
ValueCountFrequency (%)
( 423
43.7%
) 423
43.7%
97
 
10.0%
3 10
 
1.0%
2 5
 
0.5%
6 5
 
0.5%
& 3
 
0.3%
5 2
 
0.2%
- 1
 
0.1%
Latin
ValueCountFrequency (%)
G 15
31.9%
S 11
23.4%
K 5
 
10.6%
V 5
 
10.6%
C 5
 
10.6%
P 2
 
4.3%
L 2
 
4.3%
R 1
 
2.1%
D 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4684
82.2%
ASCII 1016
 
17.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 423
41.6%
) 423
41.6%
97
 
9.5%
G 15
 
1.5%
S 11
 
1.1%
3 10
 
1.0%
K 5
 
0.5%
V 5
 
0.5%
C 5
 
0.5%
2 5
 
0.5%
Other values (8) 17
 
1.7%
Hangul
ValueCountFrequency (%)
주 401
 
8.6%
양 209
 
4.5%
안 197
 
4.2%
시 116
 
2.5%
공 114
 
2.4%
트 95
 
2.0%
원 91
 
1.9%
수 87
 
1.9%
인 86
 
1.8%
리 81
 
1.7%
Other values (219) 3207
68.5%

소재지도로명주소
Text

MISSING 

Distinct124
Distinct (%)20.2%
Missing7
Missing (%)1.1%
Memory size5.0 KiB
2023-12-12T22:34:32.030113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length27
Mean length20.288274
Min length16

Characters and Unicode

Total characters12457
Distinct characters86
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

Unique39 ?
Unique (%)6.4%

Sample

1st row경기도 안양시 만안구 석수로 220
2nd row경기도 안양시 만안구 덕천로48번길 37
3rd row경기도 안양시 동안구 벌말로 123
4th row경기도 안양시 만안구 오리로 15
5th row경기도 안양시 만안구 전파로24번길 93
ValueCountFrequency (%)
경기도 614
19.9%
안양시 611
19.8%
만안구 370
12.0%
동안구 241
 
7.8%
박달로 136
 
4.4%
351 61
 
2.0%
시민대로 47
 
1.5%
232 40
 
1.3%
흥안대로 36
 
1.2%
석천로 28
 
0.9%
Other values (167) 899
29.2%
2023-12-12T22:34:32.486715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2469
19.8%
안 1327
 
10.7%
시 684
 
5.5%
양 672
 
5.4%
경 635
 
5.1%
로 614
 
4.9%
도 614
 
4.9%
기 614
 
4.9%
구 611
 
4.9%
만 372
 
3.0%
Other values (76) 3845
30.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8028
64.4%
Space Separator 2469
 
19.8%
Decimal Number 1916
 
15.4%
Dash Punctuation 20
 
0.2%
Close Punctuation 8
 
0.1%
Open Punctuation 8
 
0.1%
Connector Punctuation 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 1327
16.5%
시 684
8.5%
양 672
8.4%
경 635
 
7.9%
로 614
 
7.6%
도 614
 
7.6%
기 614
 
7.6%
구 611
 
7.6%
만 372
 
4.6%
동 268
 
3.3%
Other values (61) 1617
20.1%
Decimal Number
ValueCountFrequency (%)
1 350
18.3%
3 312
16.3%
2 310
16.2%
9 178
9.3%
5 167
8.7%
0 159
8.3%
4 128
 
6.7%
8 125
 
6.5%
6 101
 
5.3%
7 86
 
4.5%
Space Separator
ValueCountFrequency (%)
2469
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8028
64.4%
Common 4429
35.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 1327
16.5%
시 684
8.5%
양 672
8.4%
경 635
 
7.9%
로 614
 
7.6%
도 614
 
7.6%
기 614
 
7.6%
구 611
 
7.6%
만 372
 
4.6%
동 268
 
3.3%
Other values (61) 1617
20.1%
Common
ValueCountFrequency (%)
2469
55.7%
1 350
 
7.9%
3 312
 
7.0%
2 310
 
7.0%
9 178
 
4.0%
5 167
 
3.8%
0 159
 
3.6%
4 128
 
2.9%
8 125
 
2.8%
6 101
 
2.3%
Other values (5) 130
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8028
64.4%
ASCII 4429
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2469
55.7%
1 350
 
7.9%
3 312
 
7.0%
2 310
 
7.0%
9 178
 
4.0%
5 167
 
3.8%
0 159
 
3.6%
4 128
 
2.9%
8 125
 
2.8%
6 101
 
2.3%
Other values (5) 130
 
2.9%
Hangul
ValueCountFrequency (%)
안 1327
16.5%
시 684
8.5%
양 672
8.4%
경 635
 
7.9%
로 614
 
7.6%
도 614
 
7.6%
기 614
 
7.6%
구 611
 
7.6%
만 372
 
4.6%
동 268
 
3.3%
Other values (61) 1617
20.1%

소재지지번주소
Text

Distinct130
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T22:34:32.746540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length22.876006
Min length19

Characters and Unicode

Total characters14206
Distinct characters49
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

Unique44 ?
Unique (%)7.1%

Sample

1st row경기도 안양시 만안구 석수동 747번지
2nd row경기도 안양시 만안구 안양동 200-12번지
3rd row경기도 안양시 동안구 관양동 792-2번지
4th row경기도 안양시 만안구 박달동 683-2번지
5th row경기도 안양시 만안구 안양동 200-7번지
ValueCountFrequency (%)
경기도 621
19.9%
안양시 618
19.8%
만안구 373
12.0%
동안구 245
 
7.9%
박달동 171
 
5.5%
안양동 157
 
5.0%
호계동 115
 
3.7%
평촌동 71
 
2.3%
615번지 61
 
2.0%
석수동 45
 
1.4%
Other values (136) 639
20.5%
2023-12-12T22:34:33.141328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2495
17.6%
안 1393
 
9.8%
동 870
 
6.1%
양 809
 
5.7%
시 622
 
4.4%
경 621
 
4.4%
기 621
 
4.4%
도 621
 
4.4%
지 618
 
4.4%
구 618
 
4.4%
Other values (39) 4918
34.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8759
61.7%
Space Separator 2495
 
17.6%
Decimal Number 2489
 
17.5%
Dash Punctuation 463
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 1393
15.9%
동 870
9.9%
양 809
9.2%
시 622
7.1%
경 621
7.1%
기 621
7.1%
도 621
7.1%
지 618
7.1%
구 618
7.1%
번 610
7.0%
Other values (27) 1356
15.5%
Decimal Number
ValueCountFrequency (%)
1 544
21.9%
5 354
14.2%
6 290
11.7%
7 245
9.8%
2 218
8.8%
0 205
 
8.2%
9 202
 
8.1%
8 163
 
6.5%
4 138
 
5.5%
3 130
 
5.2%
Space Separator
ValueCountFrequency (%)
2495
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 463
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8759
61.7%
Common 5447
38.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 1393
15.9%
동 870
9.9%
양 809
9.2%
시 622
7.1%
경 621
7.1%
기 621
7.1%
도 621
7.1%
지 618
7.1%
구 618
7.1%
번 610
7.0%
Other values (27) 1356
15.5%
Common
ValueCountFrequency (%)
2495
45.8%
1 544
 
10.0%
- 463
 
8.5%
5 354
 
6.5%
6 290
 
5.3%
7 245
 
4.5%
2 218
 
4.0%
0 205
 
3.8%
9 202
 
3.7%
8 163
 
3.0%
Other values (2) 268
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8759
61.7%
ASCII 5447
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2495
45.8%
1 544
 
10.0%
- 463
 
8.5%
5 354
 
6.5%
6 290
 
5.3%
7 245
 
4.5%
2 218
 
4.0%
0 205
 
3.8%
9 202
 
3.7%
8 163
 
3.0%
Other values (2) 268
 
4.9%
Hangul
ValueCountFrequency (%)
안 1393
15.9%
동 870
9.9%
양 809
9.2%
시 622
7.1%
경 621
7.1%
기 621
7.1%
도 621
7.1%
지 618
7.1%
구 618
7.1%
번 610
7.0%
Other values (27) 1356
15.5%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct131
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.396335
Minimum37.367646
Maximum37.434448
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T22:34:33.285388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.367646
5-th percentile37.371613
Q137.387641
median37.395312
Q337.404604
95-th percentile37.421713
Maximum37.434448
Range0.066802
Interquartile range (IQR)0.016963

Descriptive statistics

Standard deviation0.013979759
Coefficient of variation (CV)0.00037382699
Kurtosis-0.21260818
Mean37.396335
Median Absolute Deviation (MAD)0.009292
Skewness0.21489546
Sum23223.124
Variance0.00019543367
MonotonicityNot monotonic
2023-12-12T22:34:33.433476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.407501 61
 
9.8%
37.403026 28
 
4.5%
37.416997 28
 
4.5%
37.390626 20
 
3.2%
37.373805 19
 
3.1%
37.421713 17
 
2.7%
37.371613 17
 
2.7%
37.404604 16
 
2.6%
37.395312 15
 
2.4%
37.404191 15
 
2.4%
Other values (121) 385
62.0%
ValueCountFrequency (%)
37.367646 1
 
0.2%
37.368182 1
 
0.2%
37.369056 1
 
0.2%
37.369816 2
 
0.3%
37.369864 3
 
0.5%
37.369891 7
 
1.1%
37.370011 1
 
0.2%
37.370582 4
 
0.6%
37.371613 17
2.7%
37.373805 19
3.1%
ValueCountFrequency (%)
37.434448 1
 
0.2%
37.431649 3
 
0.5%
37.427879 12
1.9%
37.426171 9
 
1.4%
37.421713 17
2.7%
37.421023 1
 
0.2%
37.420369 1
 
0.2%
37.416997 28
4.5%
37.413471 1
 
0.2%
37.410937 2
 
0.3%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct131
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.92609
Minimum126.88198
Maximum126.97301
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T22:34:33.621432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.88198
5-th percentile126.88198
Q1126.8916
median126.93252
Q3126.95043
95-th percentile126.97047
Maximum126.97301
Range0.091035
Interquartile range (IQR)0.058825

Descriptive statistics

Standard deviation0.030104069
Coefficient of variation (CV)0.00023717794
Kurtosis-1.4339509
Mean126.92609
Median Absolute Deviation (MAD)0.030096
Skewness-0.044306831
Sum78821.103
Variance0.00090625497
MonotonicityNot monotonic
2023-12-12T22:34:33.799850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.891601 61
 
9.8%
126.881976 28
 
4.5%
126.890699 28
 
4.5%
126.969855 20
 
3.2%
126.949824 19
 
3.1%
126.898396 17
 
2.7%
126.951433 17
 
2.7%
126.887364 16
 
2.6%
126.965777 15
 
2.4%
126.885775 15
 
2.4%
Other values (121) 385
62.0%
ValueCountFrequency (%)
126.881976 28
4.5%
126.8819764 12
 
1.9%
126.8855802 1
 
0.2%
126.885775 15
 
2.4%
126.886843 5
 
0.8%
126.887364 16
 
2.6%
126.888397 3
 
0.5%
126.890184 1
 
0.2%
126.890699 28
4.5%
126.891601 61
9.8%
ValueCountFrequency (%)
126.973011 2
 
0.3%
126.971705 3
 
0.5%
126.971703 6
 
1.0%
126.971464 2
 
0.3%
126.971209 8
 
1.3%
126.970856 1
 
0.2%
126.970718 2
 
0.3%
126.970473 13
2.1%
126.969855 20
3.2%
126.969301 1
 
0.2%

인허가관리번호
Text

Distinct156
Distinct (%)25.1%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T22:34:34.091277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length21
Mean length21
Min length21

Characters and Unicode

Total characters13041
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

Unique59 ?
Unique (%)9.5%

Sample

1st row3830000-31-2023-00002
2nd row3830000-31-2023-00001
3rd row3830000-31-2022-00008
4th row3830000-31-2022-00007
5th row3830000-31-2022-00006
ValueCountFrequency (%)
3830000-31-2007-00019 36
 
5.8%
3830000-31-1997-00074 25
 
4.0%
3830000-31-1992-00007 24
 
3.9%
3830000-31-2007-00023 20
 
3.2%
3830000-31-2008-00024 17
 
2.7%
3830000-31-2008-00033 16
 
2.6%
3830000-31-2000-00068 15
 
2.4%
3830000-31-1997-00031 15
 
2.4%
3830000-31-1992-00009 14
 
2.3%
3830000-31-2022-00004 12
 
1.9%
Other values (146) 427
68.8%
2023-12-12T22:34:34.504040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5356
41.1%
3 2071
 
15.9%
- 1863
 
14.3%
1 1160
 
8.9%
2 809
 
6.2%
8 773
 
5.9%
9 382
 
2.9%
7 290
 
2.2%
4 177
 
1.4%
6 115
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11178
85.7%
Dash Punctuation 1863
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5356
47.9%
3 2071
 
18.5%
1 1160
 
10.4%
2 809
 
7.2%
8 773
 
6.9%
9 382
 
3.4%
7 290
 
2.6%
4 177
 
1.6%
6 115
 
1.0%
5 45
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 1863
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13041
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5356
41.1%
3 2071
 
15.9%
- 1863
 
14.3%
1 1160
 
8.9%
2 809
 
6.2%
8 773
 
5.9%
9 382
 
2.9%
7 290
 
2.2%
4 177
 
1.4%
6 115
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13041
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5356
41.1%
3 2071
 
15.9%
- 1863
 
14.3%
1 1160
 
8.9%
2 809
 
6.2%
8 773
 
5.9%
9 382
 
2.9%
7 290
 
2.2%
4 177
 
1.4%
6 115
 
0.9%

인허가등록일자
Date

Distinct145
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Minimum1997-03-06 00:00:00
Maximum2023-02-16 00:00:00
2023-12-12T22:34:34.680769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:34.803833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

배출폐기물종류
Text

Distinct91
Distinct (%)14.7%
Missing3
Missing (%)0.5%
Memory size5.0 KiB
2023-12-12T22:34:35.067916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length57
Mean length15.226537
Min length2

Characters and Unicode

Total characters9410
Distinct characters168
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)6.1%

Sample

1st row폐수처리오니
2nd row산업용폐전기전자제품
3rd row폐합성수지류(폐염화비닐수지류는 제외한다)
4th row동물성유지류
5th row폐합성수지류(폐염화비닐수지류는 제외한다)
ValueCountFrequency (%)
제외한다 220
 
15.3%
폐합성수지류(폐염화비닐수지류는 216
 
15.0%
그 115
 
8.0%
밖의 115
 
8.0%
폐수처리오니 35
 
2.4%
음식물류폐기물 32
 
2.2%
하수처리오니 32
 
2.2%
폐기물 31
 
2.1%
폐목재류 26
 
1.8%
말한다 23
 
1.6%
Other values (140) 597
41.4%
2023-12-12T22:34:35.432232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
824
 
8.8%
폐 780
 
8.3%
류 563
 
6.0%
수 537
 
5.7%
지 468
 
5.0%
성 296
 
3.1%
한 282
 
3.0%
제 260
 
2.8%
) 259
 
2.8%
( 259
 
2.8%
Other values (158) 4882
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8011
85.1%
Space Separator 824
 
8.8%
Close Punctuation 259
 
2.8%
Open Punctuation 259
 
2.8%
Connector Punctuation 43
 
0.5%
Lowercase Letter 12
 
0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 780
 
9.7%
류 563
 
7.0%
수 537
 
6.7%
지 468
 
5.8%
성 296
 
3.7%
한 282
 
3.5%
제 260
 
3.2%
는 258
 
3.2%
다 255
 
3.2%
합 247
 
3.1%
Other values (148) 4065
50.7%
Lowercase Letter
ValueCountFrequency (%)
e 4
33.3%
t 2
16.7%
a 2
16.7%
h 2
16.7%
l 2
16.7%
Space Separator
ValueCountFrequency (%)
824
100.0%
Close Punctuation
ValueCountFrequency (%)
) 259
100.0%
Open Punctuation
ValueCountFrequency (%)
( 259
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 43
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8011
85.1%
Common 1385
 
14.7%
Latin 14
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폐 780
 
9.7%
류 563
 
7.0%
수 537
 
6.7%
지 468
 
5.8%
성 296
 
3.7%
한 282
 
3.5%
제 260
 
3.2%
는 258
 
3.2%
다 255
 
3.2%
합 247
 
3.1%
Other values (148) 4065
50.7%
Latin
ValueCountFrequency (%)
e 4
28.6%
t 2
14.3%
a 2
14.3%
h 2
14.3%
C 2
14.3%
l 2
14.3%
Common
ValueCountFrequency (%)
824
59.5%
) 259
 
18.7%
( 259
 
18.7%
_ 43
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7964
84.6%
ASCII 1399
 
14.9%
Compat Jamo 47
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
824
58.9%
) 259
 
18.5%
( 259
 
18.5%
_ 43
 
3.1%
e 4
 
0.3%
t 2
 
0.1%
a 2
 
0.1%
h 2
 
0.1%
C 2
 
0.1%
l 2
 
0.1%
Hangul
ValueCountFrequency (%)
폐 780
 
9.8%
류 563
 
7.1%
수 537
 
6.7%
지 468
 
5.9%
성 296
 
3.7%
한 282
 
3.5%
제 260
 
3.3%
는 258
 
3.2%
다 255
 
3.2%
합 247
 
3.1%
Other values (147) 4018
50.5%
Compat Jamo
ValueCountFrequency (%)
ㆍ 47
100.0%

Interactions

2023-12-12T22:34:30.326797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:30.138786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:30.419317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:30.237333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:34:35.515134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도배출폐기물종류
위도1.0000.8940.748
경도0.8941.0000.635
배출폐기물종류0.7480.6351.000
2023-12-12T22:34:35.606333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.651
경도-0.6511.000

Missing values

2023-12-12T22:34:30.555518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:34:30.716920image/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.
2023-12-12T22:34:30.827312image/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

시군명상호명소재지도로명주소소재지지번주소위도경도인허가관리번호인허가등록일자배출폐기물종류
0안양시삼영운수(주)충훈부영업소경기도 안양시 만안구 석수로 220경기도 안양시 만안구 석수동 747번지37.409821126.8941023830000-31-2023-000022023-02-16폐수처리오니
1안양시주식회사 엘지유플러스경기도 안양시 만안구 덕천로48번길 37경기도 안양시 만안구 안양동 200-12번지37.386413126.9379283830000-31-2023-000012023-02-16산업용폐전기전자제품
2안양시주식회사 샘빌경기도 안양시 동안구 벌말로 123경기도 안양시 동안구 관양동 792-2번지37.39947126.9683243830000-31-2022-000082022-11-07폐합성수지류(폐염화비닐수지류는 제외한다)
3안양시농업회사법인(주)금천축산유통경기도 안양시 만안구 오리로 15경기도 안양시 만안구 박달동 683-2번지37.405857126.885583830000-31-2022-000072022-10-11동물성유지류
4안양시주식회사 파인엠텍경기도 안양시 만안구 전파로24번길 93경기도 안양시 만안구 안양동 200-7번지37.386425126.936733830000-31-2022-000062022-10-11폐합성수지류(폐염화비닐수지류는 제외한다)
5안양시(주)동아엘텍경기도 안양시 동안구 시민대로327번길 12-24경기도 안양시 동안구 관양동 1739-3번지37.398663126.96723830000-31-2022-000052022-07-28폐합성수지류(폐염화비닐수지류는 제외한다)
6안양시(주)천일에너지(안양지점)경기도 안양시 만안구 박달로 232경기도 안양시 만안구 박달동 751-7번지37.403025126.8819763830000-31-2022-000042022-07-19폐석고
7안양시(주)천일에너지(안양지점)경기도 안양시 만안구 박달로 232경기도 안양시 만안구 박달동 751-7번지37.403025126.8819763830000-31-2022-000042022-07-20폐합성수지류(폐염화비닐수지류는 제외한다)
8안양시(주)천일에너지(안양지점)경기도 안양시 만안구 박달로 232경기도 안양시 만안구 박달동 751-7번지37.403025126.8819763830000-31-2022-000042022-07-21그 밖의 폐목재류
9안양시(주)천일에너지(안양지점)경기도 안양시 만안구 박달로 232경기도 안양시 만안구 박달동 751-7번지37.403025126.8819763830000-31-2022-000042022-07-22폐콘크리트
시군명상호명소재지도로명주소소재지지번주소위도경도인허가관리번호인허가등록일자배출폐기물종류
611안양시(주)노루페인트경기도 안양시 만안구 박달로 351경기도 안양시 만안구 박달동 615번지37.407501126.8916013830000-31-1992-000072006-06-30폐합성수지류
612안양시(주)노루페인트경기도 안양시 만안구 박달로 351경기도 안양시 만안구 박달동 615번지37.407501126.8916013830000-31-1992-000072006-06-30폐목재류
613안양시(주)노루페인트경기도 안양시 만안구 박달로 351경기도 안양시 만안구 박달동 615번지37.407501126.8916013830000-31-1992-000072006-06-30지정외폐기물
614안양시(주)노루페인트경기도 안양시 만안구 박달로 351경기도 안양시 만안구 박달동 615번지37.407501126.8916013830000-31-1992-000072006-06-30폐페인트 및 폐락카
615안양시(주)노루페인트경기도 안양시 만안구 박달로 351경기도 안양시 만안구 박달동 615번지37.407501126.8916013830000-31-1992-000072006-06-30폐페인트 및 폐락카
616안양시(주)노루페인트경기도 안양시 만안구 박달로 351경기도 안양시 만안구 박달동 615번지37.407501126.8916013830000-31-1992-000072006-06-30폐유
617안양시(주)노루페인트경기도 안양시 만안구 박달로 351경기도 안양시 만안구 박달동 615번지37.407501126.8916013830000-31-1992-000072006-06-30폐페인트 및 폐락카
618안양시(주)수석경기도 안양시 만안구 박달로 313경기도 안양시 만안구 박달동 620-5번지37.406845126.8883973830000-31-1992-000062003-04-02광재
619안양시(주)수석경기도 안양시 만안구 박달로 313경기도 안양시 만안구 박달동 620-5번지37.406845126.8883973830000-31-1992-000062003-04-02폐합성수지류
620안양시(주)수석경기도 안양시 만안구 박달로 313경기도 안양시 만안구 박달동 620-5번지37.406845126.8883973830000-31-1992-000062003-04-02폐내화물및도자기편류

Duplicate rows

Most frequently occurring

시군명상호명소재지도로명주소소재지지번주소위도경도인허가관리번호인허가등록일자배출폐기물종류# duplicates
49안양시공공하수처리시설(안양)경기도 안양시 만안구 석천로 1경기도 안양시 만안구 박달동 655번지37.416997126.8906993830000-31-1997-000742007-04-26하수처리오니18
46안양시공공하수처리시설(석수)경기도 안양시 만안구 화창로 19경기도 안양시 만안구 석수동 561-2번지37.421713126.8983963830000-31-2008-000242008-05-19하수처리오니14
8안양시(주)노루페인트경기도 안양시 만안구 박달로 351경기도 안양시 만안구 박달동 615번지37.407501126.8916013830000-31-2007-000192007-09-13폐수처리오니12
3안양시(주)노루페인트경기도 안양시 만안구 박달로 351경기도 안양시 만안구 박달동 615번지37.407501126.8916013830000-31-1992-000072006-06-30폐페인트 및 폐락카8
27안양시(주)정선골재경기도 안양시 만안구 박달로 280경기도 안양시 만안구 박달동 702-7번지37.404191126.8857753830000-31-2000-000682005-10-13석재ㆍ골재폐수처리오니(석재ㆍ골재 생산 시 발생한 폐수를 처리하는 과정에서 발생한 오니로 한정한다)7
93안양시엘에스엠트론(주)경기도 안양시 동안구 엘에스로116번길 39경기도 안양시 동안구 호계동 555-16번지37.373805126.9498243830000-31-2008-000332008-07-22폐합성수지류(폐염화비닐수지류는 제외한다)7
5안양시(주)노루페인트경기도 안양시 만안구 박달로 351경기도 안양시 만안구 박달동 615번지37.407501126.8916013830000-31-2007-000192007-09-13그 밖의 무기성오니6
9안양시(주)노루페인트경기도 안양시 만안구 박달로 351경기도 안양시 만안구 박달동 615번지37.407501126.8916013830000-31-2007-000192007-09-13폐합성수지류(폐염화비닐수지류는 제외한다)6
31안양시(주)청목자원경기도 안양시 만안구 박달로 232경기도 안양시 만안구 박달동 751-7번지37.403026126.8819763830000-31-2016-000042016-08-31폐합성수지류(폐염화비닐수지류는 제외한다)6
39안양시(주)협신식품경기도 안양시 만안구 박달로 298경기도 안양시 만안구 박달동 691-3번지37.404604126.8873643830000-31-1997-000381997-04-03그 밖의 동물성잔재물6