Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells17000
Missing cells (%)15.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory976.6 KiB
Average record size in memory100.0 B

Variable types

Numeric4
Text5
Categorical2

Dataset

Description재난위치 대상물 데이터는 소방차량이 119신고자 위치를 정확하게 찾기위한 재난위치로, 도로명주소, 지번주소 외에 동의어, 축약어, 관용어 등을 포함하는 주소를 말함
Author광주광역시
URLhttps://www.data.go.kr/data/15111359/fileData.do

Alerts

시 has constant value ""Constant
필지고유번호코드 is highly overall correlated with 구High correlation
구 is highly overall correlated with 필지고유번호코드High correlation
지점명 has 8263 (82.6%) missing valuesMissing
동의어 has 8709 (87.1%) missing valuesMissing
관리번호 has unique valuesUnique
상세주소2 has 7642 (76.4%) zerosZeros

Reproduction

Analysis started2023-12-12 03:37:28.113522
Analysis finished2023-12-12 03:37:33.245826
Duration5.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46279.651
Minimum5
Maximum96014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:37:33.354773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile4499.5
Q121688.25
median43486.5
Q374232
95-th percentile91689.1
Maximum96014
Range96009
Interquartile range (IQR)52543.75

Descriptive statistics

Standard deviation28558.664
Coefficient of variation (CV)0.61708901
Kurtosis-1.2414087
Mean46279.651
Median Absolute Deviation (MAD)26140
Skewness0.16288817
Sum4.6279651 × 108
Variance8.1559728 × 108
MonotonicityNot monotonic
2023-12-12T12:37:33.522578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48894 1
 
< 0.1%
36125 1
 
< 0.1%
94458 1
 
< 0.1%
6228 1
 
< 0.1%
32570 1
 
< 0.1%
53328 1
 
< 0.1%
13826 1
 
< 0.1%
44639 1
 
< 0.1%
9963 1
 
< 0.1%
94516 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
5 1
< 0.1%
13 1
< 0.1%
15 1
< 0.1%
23 1
< 0.1%
27 1
< 0.1%
30 1
< 0.1%
40 1
< 0.1%
49 1
< 0.1%
65 1
< 0.1%
80 1
< 0.1%
ValueCountFrequency (%)
96014 1
< 0.1%
96002 1
< 0.1%
95999 1
< 0.1%
95996 1
< 0.1%
95992 1
< 0.1%
95989 1
< 0.1%
95988 1
< 0.1%
95986 1
< 0.1%
95978 1
< 0.1%
95960 1
< 0.1%

주소
Text

Distinct7571
Distinct (%)75.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:37:34.011073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length15.315
Min length11

Characters and Unicode

Total characters153150
Distinct characters238
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

Unique6107 ?
Unique (%)61.1%

Sample

1st row광주 동구 의재로 20
2nd row광주 광산구 목련로 372-24
3rd row광주 북구 안산로 27
4th row광주 북구 문산로 43-2
5th row광주 서구 계수로51번길 6-1
ValueCountFrequency (%)
광주 9993
25.0%
북구 2851
 
7.1%
광산구 2427
 
6.1%
서구 2279
 
5.7%
동구 1230
 
3.1%
남구 1206
 
3.0%
10 146
 
0.4%
7 136
 
0.3%
상무대로 135
 
0.3%
12 132
 
0.3%
Other values (3705) 19466
48.7%
2023-12-12T12:37:34.675235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30001
19.6%
광 12511
 
8.2%
주 10081
 
6.6%
구 10061
 
6.6%
로 9549
 
6.2%
1 7468
 
4.9%
2 5122
 
3.3%
길 4264
 
2.8%
번 3917
 
2.6%
3 3872
 
2.5%
Other values (228) 56304
36.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 85950
56.1%
Decimal Number 34862
22.8%
Space Separator 30001
 
19.6%
Dash Punctuation 2337
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 12511
14.6%
주 10081
11.7%
구 10061
11.7%
로 9549
 
11.1%
길 4264
 
5.0%
번 3917
 
4.6%
산 3147
 
3.7%
서 3012
 
3.5%
북 2977
 
3.5%
남 1798
 
2.1%
Other values (216) 24633
28.7%
Decimal Number
ValueCountFrequency (%)
1 7468
21.4%
2 5122
14.7%
3 3872
11.1%
5 2991
8.6%
4 2842
 
8.2%
7 2674
 
7.7%
6 2654
 
7.6%
0 2567
 
7.4%
8 2411
 
6.9%
9 2261
 
6.5%
Space Separator
ValueCountFrequency (%)
30001
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2337
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 85950
56.1%
Common 67200
43.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 12511
14.6%
주 10081
11.7%
구 10061
11.7%
로 9549
 
11.1%
길 4264
 
5.0%
번 3917
 
4.6%
산 3147
 
3.7%
서 3012
 
3.5%
북 2977
 
3.5%
남 1798
 
2.1%
Other values (216) 24633
28.7%
Common
ValueCountFrequency (%)
30001
44.6%
1 7468
 
11.1%
2 5122
 
7.6%
3 3872
 
5.8%
5 2991
 
4.5%
4 2842
 
4.2%
7 2674
 
4.0%
6 2654
 
3.9%
0 2567
 
3.8%
8 2411
 
3.6%
Other values (2) 4598
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 85950
56.1%
ASCII 67200
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30001
44.6%
1 7468
 
11.1%
2 5122
 
7.6%
3 3872
 
5.8%
5 2991
 
4.5%
4 2842
 
4.2%
7 2674
 
4.0%
6 2654
 
3.9%
0 2567
 
3.8%
8 2411
 
3.6%
Other values (2) 4598
 
6.8%
Hangul
ValueCountFrequency (%)
광 12511
14.6%
주 10081
11.7%
구 10061
11.7%
로 9549
 
11.1%
길 4264
 
5.0%
번 3917
 
4.6%
산 3147
 
3.7%
서 3012
 
3.5%
북 2977
 
3.5%
남 1798
 
2.1%
Other values (216) 24633
28.7%

시
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
광주
10000 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광주 10000
100.0%

Length

2023-12-12T12:37:34.900043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:37:35.046869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광주 10000
100.0%

구
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
북구
2855 
광산구
2430 
서구
2280 
동구
1232 
남구
1203 

Length

Max length3
Median length2
Mean length2.243
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동구
2nd row광산구
3rd row북구
4th row북구
5th row서구

Common Values

ValueCountFrequency (%)
북구 2855
28.5%
광산구 2430
24.3%
서구 2280
22.8%
동구 1232
12.3%
남구 1203
12.0%

Length

2023-12-12T12:37:35.192907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:37:35.370429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
북구 2855
28.5%
광산구 2430
24.3%
서구 2280
22.8%
동구 1232
12.3%
남구 1203
12.0%

도로명
Text

Distinct1738
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:37:35.791505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.3536
Min length3

Characters and Unicode

Total characters53536
Distinct characters225
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique615 ?
Unique (%)6.2%

Sample

1st row의재로
2nd row목련로
3rd row안산로
4th row문산로
5th row계수로51번길
ValueCountFrequency (%)
상무대로 136
 
1.4%
설죽로 99
 
1.0%
하남대로 96
 
1.0%
사암로 92
 
0.9%
동문대로 91
 
0.9%
대남대로 86
 
0.9%
무등로 84
 
0.8%
운천로 82
 
0.8%
금남로 82
 
0.8%
독립로 79
 
0.8%
Other values (1728) 9073
90.7%
2023-12-12T12:37:36.450743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 9552
 
17.8%
길 4256
 
7.9%
번 3912
 
7.3%
1 1867
 
3.5%
대 1736
 
3.2%
2 1535
 
2.9%
3 1164
 
2.2%
5 877
 
1.6%
0 864
 
1.6%
4 804
 
1.5%
Other values (215) 26969
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43490
81.2%
Decimal Number 10046
 
18.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 9552
22.0%
길 4256
 
9.8%
번 3912
 
9.0%
대 1736
 
4.0%
무 779
 
1.8%
서 728
 
1.7%
산 718
 
1.7%
문 697
 
1.6%
중 617
 
1.4%
상 615
 
1.4%
Other values (205) 19880
45.7%
Decimal Number
ValueCountFrequency (%)
1 1867
18.6%
2 1535
15.3%
3 1164
11.6%
5 877
8.7%
0 864
8.6%
4 804
8.0%
6 774
7.7%
8 769
7.7%
7 704
 
7.0%
9 688
 
6.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43490
81.2%
Common 10046
 
18.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 9552
22.0%
길 4256
 
9.8%
번 3912
 
9.0%
대 1736
 
4.0%
무 779
 
1.8%
서 728
 
1.7%
산 718
 
1.7%
문 697
 
1.6%
중 617
 
1.4%
상 615
 
1.4%
Other values (205) 19880
45.7%
Common
ValueCountFrequency (%)
1 1867
18.6%
2 1535
15.3%
3 1164
11.6%
5 877
8.7%
0 864
8.6%
4 804
8.0%
6 774
7.7%
8 769
7.7%
7 704
 
7.0%
9 688
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43490
81.2%
ASCII 10046
 
18.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 9552
22.0%
길 4256
 
9.8%
번 3912
 
9.0%
대 1736
 
4.0%
무 779
 
1.8%
서 728
 
1.7%
산 718
 
1.7%
문 697
 
1.6%
중 617
 
1.4%
상 615
 
1.4%
Other values (205) 19880
45.7%
ASCII
ValueCountFrequency (%)
1 1867
18.6%
2 1535
15.3%
3 1164
11.6%
5 877
8.7%
0 864
8.6%
4 804
8.0%
6 774
7.7%
8 769
7.7%
7 704
 
7.0%
9 688
 
6.8%

상세주소1
Real number (ℝ)

Distinct755
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean121.5422
Minimum1
Maximum2474
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:37:36.652908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q116
median46
Q3142
95-th percentile517
Maximum2474
Range2473
Interquartile range (IQR)126

Descriptive statistics

Standard deviation186.69552
Coefficient of variation (CV)1.5360551
Kurtosis12.832541
Mean121.5422
Median Absolute Deviation (MAD)37
Skewness3.0192401
Sum1215422
Variance34855.218
MonotonicityNot monotonic
2023-12-12T12:37:36.869492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 210
 
2.1%
7 201
 
2.0%
12 197
 
2.0%
8 181
 
1.8%
5 176
 
1.8%
6 174
 
1.7%
3 173
 
1.7%
15 165
 
1.7%
9 163
 
1.6%
16 155
 
1.6%
Other values (745) 8205
82.0%
ValueCountFrequency (%)
1 150
1.5%
2 147
1.5%
3 173
1.7%
4 128
1.3%
5 176
1.8%
6 174
1.7%
7 201
2.0%
8 181
1.8%
9 163
1.6%
10 210
2.1%
ValueCountFrequency (%)
2474 1
< 0.1%
2348 1
< 0.1%
1824 1
< 0.1%
1514 1
< 0.1%
1323 1
< 0.1%
1255 1
< 0.1%
1244 1
< 0.1%
1227 1
< 0.1%
1224 1
< 0.1%
1216 1
< 0.1%

상세주소2
Real number (ℝ)

ZEROS 

Distinct67
Distinct (%)0.7%
Missing13
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean1.9275058
Minimum0
Maximum146
Zeros7642
Zeros (%)76.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:37:37.090137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile12
Maximum146
Range146
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.4009931
Coefficient of variation (CV)3.3208685
Kurtosis90.226709
Mean1.9275058
Median Absolute Deviation (MAD)0
Skewness7.2235314
Sum19250
Variance40.972713
MonotonicityNot monotonic
2023-12-12T12:37:37.322817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7642
76.4%
1 754
 
7.5%
2 195
 
1.9%
6 135
 
1.4%
3 124
 
1.2%
5 98
 
1.0%
4 96
 
1.0%
7 90
 
0.9%
8 87
 
0.9%
10 83
 
0.8%
Other values (57) 683
 
6.8%
ValueCountFrequency (%)
0 7642
76.4%
1 754
 
7.5%
2 195
 
1.9%
3 124
 
1.2%
4 96
 
1.0%
5 98
 
1.0%
6 135
 
1.4%
7 90
 
0.9%
8 87
 
0.9%
9 65
 
0.7%
ValueCountFrequency (%)
146 1
< 0.1%
139 1
< 0.1%
100 1
< 0.1%
99 1
< 0.1%
98 1
< 0.1%
90 1
< 0.1%
87 1
< 0.1%
85 1
< 0.1%
77 1
< 0.1%
69 1
< 0.1%

필지고유번호코드
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing14
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean2.9161391 × 1018
Minimum2.91101 × 1018
Maximum2.92002 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:37:37.499484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.91101 × 1018
5-th percentile2.91101 × 1018
Q12.91401 × 1018
median2.91701 × 1018
Q32.91701 × 1018
95-th percentile2.92001 × 1018
Maximum2.92002 × 1018
Range9.01 × 1015
Interquartile range (IQR)3 × 1015

Descriptive statistics

Standard deviation2.8567075 × 1015
Coefficient of variation (CV)0.00097961977
Kurtosis-0.83507139
Mean2.9161391 × 1018
Median Absolute Deviation (MAD)3 × 1015
Skewness-0.19134084
Sum-6.8442924 × 1018
Variance8.1607776 × 1030
MonotonicityNot monotonic
2023-12-12T12:37:37.641455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2917010000000000000 2855
28.5%
2920010000000000000 2302
23.0%
2914010000000000000 2280
22.8%
2911010000000000000 1222
12.2%
2915510000000000000 1203
12.0%
2920020000000000000 124
 
1.2%
(Missing) 14
 
0.1%
ValueCountFrequency (%)
2911010000000000000 1222
12.2%
2914010000000000000 2280
22.8%
2915510000000000000 1203
12.0%
2917010000000000000 2855
28.5%
2920010000000000000 2302
23.0%
2920020000000000000 124
 
1.2%
ValueCountFrequency (%)
2920020000000000000 124
 
1.2%
2920010000000000000 2302
23.0%
2917010000000000000 2855
28.5%
2915510000000000000 1203
12.0%
2914010000000000000 2280
22.8%
2911010000000000000 1222
12.2%

대상물명
Text

Distinct9464
Distinct (%)94.6%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-12T12:37:38.172780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length7.640364
Min length1

Characters and Unicode

Total characters76396
Distinct characters1034
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9188 ?
Unique (%)91.9%

Sample

1st row김형제 고기의 철학
2nd row정원 가설 산업
3rd row팩토리 아울렛
4th row유매쓰 수학 학원
5th row메가 리치 상명
ValueCountFrequency (%)
광주 430
 
1.8%
사무소 274
 
1.1%
센터 213
 
0.9%
학원 177
 
0.7%
아파트 175
 
0.7%
헤어 153
 
0.6%
공인중개사 153
 
0.6%
교회 138
 
0.6%
의원 127
 
0.5%
산업 95
 
0.4%
Other values (8900) 22086
91.9%
2023-12-12T12:37:39.014518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14308
 
18.7%
이 1302
 
1.7%
스 1278
 
1.7%
사 1071
 
1.4%
원 932
 
1.2%
주 911
 
1.2%
아 870
 
1.1%
리 828
 
1.1%
광 805
 
1.1%
소 742
 
1.0%
Other values (1024) 53349
69.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59365
77.7%
Space Separator 14308
 
18.7%
Uppercase Letter 1288
 
1.7%
Decimal Number 1019
 
1.3%
Lowercase Letter 193
 
0.3%
Other Punctuation 95
 
0.1%
Close Punctuation 56
 
0.1%
Open Punctuation 56
 
0.1%
Other Symbol 13
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 1302
 
2.2%
스 1278
 
2.2%
사 1071
 
1.8%
원 932
 
1.6%
주 911
 
1.5%
아 870
 
1.5%
리 828
 
1.4%
광 805
 
1.4%
소 742
 
1.2%
인 677
 
1.1%
Other values (956) 49949
84.1%
Uppercase Letter
ValueCountFrequency (%)
C 143
 
11.1%
S 116
 
9.0%
K 101
 
7.8%
T 99
 
7.7%
M 96
 
7.5%
A 93
 
7.2%
G 85
 
6.6%
B 74
 
5.7%
U 59
 
4.6%
L 47
 
3.6%
Other values (16) 375
29.1%
Lowercase Letter
ValueCountFrequency (%)
e 29
15.0%
a 20
10.4%
o 19
9.8%
d 14
 
7.3%
r 14
 
7.3%
c 13
 
6.7%
w 11
 
5.7%
l 11
 
5.7%
t 10
 
5.2%
f 9
 
4.7%
Other values (11) 43
22.3%
Decimal Number
ValueCountFrequency (%)
1 208
20.4%
2 183
18.0%
5 131
12.9%
3 117
11.5%
0 92
9.0%
9 81
 
7.9%
6 66
 
6.5%
4 64
 
6.3%
8 46
 
4.5%
7 31
 
3.0%
Other Punctuation
ValueCountFrequency (%)
& 75
78.9%
. 15
 
15.8%
/ 3
 
3.2%
' 1
 
1.1%
% 1
 
1.1%
Space Separator
ValueCountFrequency (%)
14308
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59378
77.7%
Common 15537
 
20.3%
Latin 1481
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1302
 
2.2%
스 1278
 
2.2%
사 1071
 
1.8%
원 932
 
1.6%
주 911
 
1.5%
아 870
 
1.5%
리 828
 
1.4%
광 805
 
1.4%
소 742
 
1.2%
인 677
 
1.1%
Other values (957) 49962
84.1%
Latin
ValueCountFrequency (%)
C 143
 
9.7%
S 116
 
7.8%
K 101
 
6.8%
T 99
 
6.7%
M 96
 
6.5%
A 93
 
6.3%
G 85
 
5.7%
B 74
 
5.0%
U 59
 
4.0%
L 47
 
3.2%
Other values (37) 568
38.4%
Common
ValueCountFrequency (%)
14308
92.1%
1 208
 
1.3%
2 183
 
1.2%
5 131
 
0.8%
3 117
 
0.8%
0 92
 
0.6%
9 81
 
0.5%
& 75
 
0.5%
6 66
 
0.4%
4 64
 
0.4%
Other values (10) 212
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 59365
77.7%
ASCII 17018
 
22.3%
None 13
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14308
84.1%
1 208
 
1.2%
2 183
 
1.1%
C 143
 
0.8%
5 131
 
0.8%
3 117
 
0.7%
S 116
 
0.7%
K 101
 
0.6%
T 99
 
0.6%
M 96
 
0.6%
Other values (57) 1516
 
8.9%
Hangul
ValueCountFrequency (%)
이 1302
 
2.2%
스 1278
 
2.2%
사 1071
 
1.8%
원 932
 
1.6%
주 911
 
1.5%
아 870
 
1.5%
리 828
 
1.4%
광 805
 
1.4%
소 742
 
1.2%
인 677
 
1.1%
Other values (956) 49949
84.1%
None
ValueCountFrequency (%)
㈜ 13
100.0%

지점명
Text

MISSING 

Distinct840
Distinct (%)48.4%
Missing8263
Missing (%)82.6%
Memory size156.2 KiB
2023-12-12T12:37:39.429986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length13
Mean length4.6850892
Min length1

Characters and Unicode

Total characters8138
Distinct characters327
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique645 ?
Unique (%)37.1%

Sample

1st row학동본점
2nd row전남광주쌍촌점
3rd row광산점
4th row본점
5th row광천점
ValueCountFrequency (%)
광주점 48
 
2.6%
본점 37
 
2.0%
광주 35
 
1.9%
첨단점 35
 
1.9%
광주지점 34
 
1.9%
상무점 34
 
1.9%
수완점 30
 
1.7%
광주수완점 24
 
1.3%
봉선점 20
 
1.1%
광주첨단점 20
 
1.1%
Other values (860) 1500
82.6%
2023-12-12T12:37:39.919237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 1589
 
19.5%
광 739
 
9.1%
주 727
 
8.9%
지 223
 
2.7%
대 153
 
1.9%
남 146
 
1.8%
암 124
 
1.5%
단 117
 
1.4%
동 117
 
1.4%
산 117
 
1.4%
Other values (317) 4086
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7872
96.7%
Decimal Number 100
 
1.2%
Space Separator 90
 
1.1%
Uppercase Letter 67
 
0.8%
Other Punctuation 4
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1589
20.2%
광 739
 
9.4%
주 727
 
9.2%
지 223
 
2.8%
대 153
 
1.9%
남 146
 
1.9%
암 124
 
1.6%
단 117
 
1.5%
동 117
 
1.5%
산 117
 
1.5%
Other values (285) 3820
48.5%
Uppercase Letter
ValueCountFrequency (%)
C 16
23.9%
T 7
10.4%
D 6
 
9.0%
S 6
 
9.0%
N 6
 
9.0%
P 4
 
6.0%
B 3
 
4.5%
G 3
 
4.5%
A 2
 
3.0%
L 2
 
3.0%
Other values (8) 12
17.9%
Decimal Number
ValueCountFrequency (%)
2 38
38.0%
1 28
28.0%
5 10
 
10.0%
3 10
 
10.0%
6 5
 
5.0%
4 4
 
4.0%
8 3
 
3.0%
7 1
 
1.0%
9 1
 
1.0%
Space Separator
ValueCountFrequency (%)
90
100.0%
Other Punctuation
ValueCountFrequency (%)
& 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7871
96.7%
Common 199
 
2.4%
Latin 67
 
0.8%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1589
20.2%
광 739
 
9.4%
주 727
 
9.2%
지 223
 
2.8%
대 153
 
1.9%
남 146
 
1.9%
암 124
 
1.6%
단 117
 
1.5%
동 117
 
1.5%
산 117
 
1.5%
Other values (284) 3819
48.5%
Latin
ValueCountFrequency (%)
C 16
23.9%
T 7
10.4%
D 6
 
9.0%
S 6
 
9.0%
N 6
 
9.0%
P 4
 
6.0%
B 3
 
4.5%
G 3
 
4.5%
A 2
 
3.0%
L 2
 
3.0%
Other values (8) 12
17.9%
Common
ValueCountFrequency (%)
90
45.2%
2 38
19.1%
1 28
 
14.1%
5 10
 
5.0%
3 10
 
5.0%
6 5
 
2.5%
4 4
 
2.0%
& 4
 
2.0%
8 3
 
1.5%
) 2
 
1.0%
Other values (4) 5
 
2.5%
Han
ValueCountFrequency (%)
前 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7871
96.7%
ASCII 266
 
3.3%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 1589
20.2%
광 739
 
9.4%
주 727
 
9.2%
지 223
 
2.8%
대 153
 
1.9%
남 146
 
1.9%
암 124
 
1.6%
단 117
 
1.5%
동 117
 
1.5%
산 117
 
1.5%
Other values (284) 3819
48.5%
ASCII
ValueCountFrequency (%)
90
33.8%
2 38
14.3%
1 28
 
10.5%
C 16
 
6.0%
5 10
 
3.8%
3 10
 
3.8%
T 7
 
2.6%
D 6
 
2.3%
S 6
 
2.3%
N 6
 
2.3%
Other values (22) 49
18.4%
CJK
ValueCountFrequency (%)
前 1
100.0%

동의어
Text

MISSING 

Distinct1178
Distinct (%)91.2%
Missing8709
Missing (%)87.1%
Memory size156.2 KiB
2023-12-12T12:37:40.335681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length105
Median length45
Mean length13.041828
Min length1

Characters and Unicode

Total characters16837
Distinct characters624
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

Unique1137 ?
Unique (%)88.1%

Sample

1st row용두초
2nd row대한 수산
3rd rowSK 에너지 일곡제일 주유소, 에스케이 에너지 일곡 제일 주유소
4th rowOK텔레콤, 오케이 텔레콤
5th rowIYF광주문화체육센터, 아이와이에프 광주 문화 체육 센터
ValueCountFrequency (%)
광주 73
 
1.7%
cu 47
 
1.1%
공인중개사 43
 
1.0%
42
 
1.0%
아파트 41
 
0.9%
부동산 40
 
0.9%
에이티엠 37
 
0.9%
씨유 37
 
0.9%
앤 35
 
0.8%
노래방 33
 
0.8%
Other values (2002) 3911
90.1%
2023-12-12T12:37:41.032624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3292
 
19.6%
이 513
 
3.0%
, 469
 
2.8%
스 324
 
1.9%
에 217
 
1.3%
주 190
 
1.1%
사 180
 
1.1%
일 174
 
1.0%
지 171
 
1.0%
오 169
 
1.0%
Other values (614) 11138
66.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11884
70.6%
Space Separator 3292
 
19.6%
Uppercase Letter 906
 
5.4%
Other Punctuation 483
 
2.9%
Decimal Number 172
 
1.0%
Lowercase Letter 74
 
0.4%
Open Punctuation 12
 
0.1%
Close Punctuation 12
 
0.1%
Other Symbol 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 513
 
4.3%
스 324
 
2.7%
에 217
 
1.8%
주 190
 
1.6%
사 180
 
1.5%
일 174
 
1.5%
지 171
 
1.4%
오 169
 
1.4%
아 165
 
1.4%
동 162
 
1.4%
Other values (556) 9619
80.9%
Uppercase Letter
ValueCountFrequency (%)
C 96
10.6%
S 87
 
9.6%
K 81
 
8.9%
G 72
 
7.9%
T 71
 
7.8%
M 63
 
7.0%
B 61
 
6.7%
A 57
 
6.3%
U 53
 
5.8%
L 35
 
3.9%
Other values (16) 230
25.4%
Lowercase Letter
ValueCountFrequency (%)
o 10
13.5%
l 10
13.5%
d 10
13.5%
w 10
13.5%
r 10
13.5%
e 6
8.1%
n 4
 
5.4%
i 3
 
4.1%
a 3
 
4.1%
t 2
 
2.7%
Other values (4) 6
8.1%
Decimal Number
ValueCountFrequency (%)
5 51
29.7%
2 43
25.0%
3 28
16.3%
6 23
13.4%
1 19
 
11.0%
9 5
 
2.9%
8 1
 
0.6%
4 1
 
0.6%
0 1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
, 469
97.1%
& 10
 
2.1%
. 3
 
0.6%
\ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
3292
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11885
70.6%
Common 3972
 
23.6%
Latin 980
 
5.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 513
 
4.3%
스 324
 
2.7%
에 217
 
1.8%
주 190
 
1.6%
사 180
 
1.5%
일 174
 
1.5%
지 171
 
1.4%
오 169
 
1.4%
아 165
 
1.4%
동 162
 
1.4%
Other values (557) 9620
80.9%
Latin
ValueCountFrequency (%)
C 96
 
9.8%
S 87
 
8.9%
K 81
 
8.3%
G 72
 
7.3%
T 71
 
7.2%
M 63
 
6.4%
B 61
 
6.2%
A 57
 
5.8%
U 53
 
5.4%
L 35
 
3.6%
Other values (30) 304
31.0%
Common
ValueCountFrequency (%)
3292
82.9%
, 469
 
11.8%
5 51
 
1.3%
2 43
 
1.1%
3 28
 
0.7%
6 23
 
0.6%
1 19
 
0.5%
( 12
 
0.3%
) 12
 
0.3%
& 10
 
0.3%
Other values (7) 13
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11884
70.6%
ASCII 4952
29.4%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3292
66.5%
, 469
 
9.5%
C 96
 
1.9%
S 87
 
1.8%
K 81
 
1.6%
G 72
 
1.5%
T 71
 
1.4%
M 63
 
1.3%
B 61
 
1.2%
A 57
 
1.2%
Other values (47) 603
 
12.2%
Hangul
ValueCountFrequency (%)
이 513
 
4.3%
스 324
 
2.7%
에 217
 
1.8%
주 190
 
1.6%
사 180
 
1.5%
일 174
 
1.5%
지 171
 
1.4%
오 169
 
1.4%
아 165
 
1.4%
동 162
 
1.4%
Other values (556) 9619
80.9%
None
ValueCountFrequency (%)
㈜ 1
100.0%

Interactions

2023-12-12T12:37:31.966762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:37:30.328349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:37:30.877655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:37:31.439816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:37:32.093744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:37:30.446593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:37:31.013009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:37:31.576961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:37:32.203100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:37:30.602104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:37:31.145169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:37:31.709270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:37:32.350896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:37:30.742341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:37:31.294582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:37:31.849782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:37:41.217422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호구상세주소1상세주소2필지고유번호코드
관리번호1.0000.1410.0930.0310.116
구0.1411.0000.1290.1401.000
상세주소10.0930.1291.0000.0820.108
상세주소20.0310.1400.0821.0000.234
필지고유번호코드0.1161.0000.1080.2341.000
2023-12-12T12:37:41.378804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호상세주소1상세주소2필지고유번호코드구
관리번호1.000-0.0150.0330.0130.059
상세주소1-0.0151.000-0.0970.0830.074
상세주소20.033-0.0971.0000.0290.086
필지고유번호코드0.0130.0830.0291.0001.000
구0.0590.0740.0861.0001.000

Missing values

2023-12-12T12:37:32.825778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:37:33.012353image/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.
2023-12-12T12:37:33.162675image/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

관리번호주소시구도로명상세주소1상세주소2필지고유번호코드대상물명지점명동의어
4508748894광주 동구 의재로 20광주동구의재로2002911010000000000000김형제 고기의 철학학동본점<NA>
75868245광주 광산구 목련로 372-24광주광산구목련로372242920010000000000000정원 가설 산업<NA><NA>
16191744광주 북구 안산로 27광주북구안산로2702917010000000000000팩토리 아울렛<NA><NA>
1994021569광주 북구 문산로 43-2광주북구문산로4322917010000000000000유매쓰 수학 학원<NA><NA>
3823841281광주 서구 계수로51번길 6-1광주서구계수로51번길612914010000000000000메가 리치 상명<NA><NA>
3735240326광주 남구 천변좌로552번길 24광주남구천변좌로552번길2402915510000000000000바로크 피아노 교습소<NA><NA>
6038274979광주 서구 화운로 304-1광주서구화운로30412914010000000000000엠제이 글로벌<NA><NA>
7926995250광주 북구 임방울대로1041번길 25광주북구임방울대로1041번길2502917010000000000000용두 초등학교<NA>용두초
5541969643광주 서구 상무대로868번길 3광주서구상무대로868번길302914010000000000000또봉이 통닭전남광주쌍촌점<NA>
5897673480광주 광산구 연산로 291광주광산구연산로29102920010000000000000(주) 대한 수산<NA>대한 수산
관리번호주소시구도로명상세주소1상세주소2필지고유번호코드대상물명지점명동의어
7514490796광주 북구 양산제로 109광주북구양산제로10902917010000000000000환희 음악 학원<NA><NA>
6353378402광주 북구 서강로66번길 9광주북구서강로66번길902917010000000000000노랑 통닭광주운암점<NA>
7681392583광주 남구 대남대로 277-2광주남구대남대로27722915510000000000000의신 산업 개발<NA><NA>
4198145412광주 남구 대남대로 366광주남구대남대로36602915510000000000000전일 씨네빌<NA><NA>
5678271120광주 남구 봉선로 90광주남구봉선로9002915510000000000000YJ 폴댄스 아카데미남구봉선점YJ폴댄스아카데미, 와이제이 폴댄스 아카데미
1931020889광주 동구 천변우로 487광주동구천변우로48702911010000000000000산토스<NA><NA>
4624650154광주 북구 삼정로 6광주북구삼정로602917010000000000000명품 광주김치<NA><NA>
2091522588광주 광산구 장신로20번안길 44-5광주광산구장신로20번안길4452920010000000000000보니타<NA><NA>
1902620582광주 북구 첨단과기로176번길 27광주북구첨단과기로176번길2702917010000000000000사단법인 광주 전남 디자인 협회<NA>광주 전남 디자인 협회
2200423760광주 광산구 장신로 52광주광산구장신로5202920010000000000000코웨이수완점<NA>