Overview

Dataset statistics

Number of variables9
Number of observations48
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory77.7 B

Variable types

Categorical4
Text2
Numeric3

Dataset

Description광주광역시 남구 급경사지 현황에 대한 데이터로 급경사지 명칭, 주소, 연장, 높이, 경사도, 등급현황을 제공합니다
Author공공데이터포털
URLhttps://www.data.go.kr/data/15122141/fileData.do

Alerts

구분 has constant value ""Constant
데이터기준일자 has constant value ""Constant
높이 is highly overall correlated with 경사도High correlation
경사도 is highly overall correlated with 높이High correlation
명칭 has unique valuesUnique

Reproduction

Analysis started2024-04-20 12:37:54.162939
Analysis finished2024-04-20 12:37:57.600122
Duration3.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size512.0 B
급경사지
48 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
급경사지 48
100.0%

Length

2024-04-20T21:37:57.801069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T21:37:58.089395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
급경사지 48
100.0%

명칭
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size512.0 B
2024-04-20T21:37:59.001114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length17
Mean length8.0208333
Min length4

Characters and Unicode

Total characters385
Distinct characters126
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)100.0%

Sample

1st rowMBC방송국 도로옹벽
2nd rowMBC주차장
3rd row경남아너스빌
4th row광명아파트 도로
5th row광주 남 송하 N1 지구 남문장례식장
ValueCountFrequency (%)
후면 5
 
5.9%
지구 3
 
3.5%
옆 3
 
3.5%
도로 3
 
3.5%
광주 3
 
3.5%
남 3
 
3.5%
진월 2
 
2.4%
모아2차아파트 2
 
2.4%
n1 2
 
2.4%
정우아파트 1
 
1.2%
Other values (58) 58
68.2%
2024-04-20T21:38:00.326862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37
 
9.6%
아 17
 
4.4%
파 12
 
3.1%
트 12
 
3.1%
남 11
 
2.9%
차 9
 
2.3%
월 9
 
2.3%
지 8
 
2.1%
호 8
 
2.1%
주 8
 
2.1%
Other values (116) 254
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 305
79.2%
Space Separator 37
 
9.6%
Decimal Number 23
 
6.0%
Uppercase Letter 14
 
3.6%
Open Punctuation 3
 
0.8%
Close Punctuation 3
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 17
 
5.6%
파 12
 
3.9%
트 12
 
3.9%
남 11
 
3.6%
차 9
 
3.0%
월 9
 
3.0%
지 8
 
2.6%
호 8
 
2.6%
주 8
 
2.6%
선 7
 
2.3%
Other values (98) 204
66.9%
Uppercase Letter
ValueCountFrequency (%)
C 3
21.4%
N 3
21.4%
B 2
14.3%
M 2
14.3%
I 1
 
7.1%
A 1
 
7.1%
P 1
 
7.1%
T 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
2 8
34.8%
1 5
21.7%
6 4
17.4%
0 2
 
8.7%
3 2
 
8.7%
9 1
 
4.3%
5 1
 
4.3%
Space Separator
ValueCountFrequency (%)
37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 305
79.2%
Common 66
 
17.1%
Latin 14
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 17
 
5.6%
파 12
 
3.9%
트 12
 
3.9%
남 11
 
3.6%
차 9
 
3.0%
월 9
 
3.0%
지 8
 
2.6%
호 8
 
2.6%
주 8
 
2.6%
선 7
 
2.3%
Other values (98) 204
66.9%
Common
ValueCountFrequency (%)
37
56.1%
2 8
 
12.1%
1 5
 
7.6%
6 4
 
6.1%
( 3
 
4.5%
) 3
 
4.5%
0 2
 
3.0%
3 2
 
3.0%
9 1
 
1.5%
5 1
 
1.5%
Latin
ValueCountFrequency (%)
C 3
21.4%
N 3
21.4%
B 2
14.3%
M 2
14.3%
I 1
 
7.1%
A 1
 
7.1%
P 1
 
7.1%
T 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 305
79.2%
ASCII 80
 
20.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37
46.2%
2 8
 
10.0%
1 5
 
6.2%
6 4
 
5.0%
( 3
 
3.8%
C 3
 
3.8%
) 3
 
3.8%
N 3
 
3.8%
0 2
 
2.5%
B 2
 
2.5%
Other values (8) 10
 
12.5%
Hangul
ValueCountFrequency (%)
아 17
 
5.6%
파 12
 
3.9%
트 12
 
3.9%
남 11
 
3.6%
차 9
 
3.0%
월 9
 
3.0%
지 8
 
2.6%
호 8
 
2.6%
주 8
 
2.6%
선 7
 
2.3%
Other values (98) 204
66.9%

위치
Text

Distinct46
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size512.0 B
2024-04-20T21:38:01.103640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length17.395833
Min length14

Characters and Unicode

Total characters835
Distinct characters34
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 (%)91.7%

Sample

1st row광주광역시 남구 월산동 303
2nd row광주광역시 남구 월산동 269-79
3rd row광주광역시 남구 주월동 1134
4th row광주광역시 남구 방림동 54-1
5th row광주광역시 남구 송하동 218-59
ValueCountFrequency (%)
광주광역시 48
25.0%
남구 48
25.0%
진월동 9
 
4.7%
월산동 7
 
3.6%
송하동 7
 
3.6%
방림동 7
 
3.6%
주월동 5
 
2.6%
봉선동 4
 
2.1%
양과동 3
 
1.6%
백운동 3
 
1.6%
Other values (49) 51
26.6%
2024-04-20T21:38:02.128298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
144
17.2%
광 96
11.5%
주 53
 
6.3%
구 49
 
5.9%
시 48
 
5.7%
역 48
 
5.7%
남 48
 
5.7%
동 48
 
5.7%
1 40
 
4.8%
- 31
 
3.7%
Other values (24) 230
27.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 487
58.3%
Decimal Number 173
 
20.7%
Space Separator 144
 
17.2%
Dash Punctuation 31
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 96
19.7%
주 53
10.9%
구 49
10.1%
시 48
9.9%
역 48
9.9%
남 48
9.9%
동 48
9.9%
월 21
 
4.3%
산 17
 
3.5%
진 9
 
1.8%
Other values (12) 50
10.3%
Decimal Number
ValueCountFrequency (%)
1 40
23.1%
3 23
13.3%
5 20
11.6%
2 17
9.8%
7 15
 
8.7%
9 14
 
8.1%
6 14
 
8.1%
4 13
 
7.5%
8 12
 
6.9%
0 5
 
2.9%
Space Separator
ValueCountFrequency (%)
144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 487
58.3%
Common 348
41.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 96
19.7%
주 53
10.9%
구 49
10.1%
시 48
9.9%
역 48
9.9%
남 48
9.9%
동 48
9.9%
월 21
 
4.3%
산 17
 
3.5%
진 9
 
1.8%
Other values (12) 50
10.3%
Common
ValueCountFrequency (%)
144
41.4%
1 40
 
11.5%
- 31
 
8.9%
3 23
 
6.6%
5 20
 
5.7%
2 17
 
4.9%
7 15
 
4.3%
9 14
 
4.0%
6 14
 
4.0%
4 13
 
3.7%
Other values (2) 17
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 487
58.3%
ASCII 348
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
144
41.4%
1 40
 
11.5%
- 31
 
8.9%
3 23
 
6.6%
5 20
 
5.7%
2 17
 
4.9%
7 15
 
4.3%
9 14
 
4.0%
6 14
 
4.0%
4 13
 
3.7%
Other values (2) 17
 
4.9%
Hangul
ValueCountFrequency (%)
광 96
19.7%
주 53
10.9%
구 49
10.1%
시 48
9.9%
역 48
9.9%
남 48
9.9%
동 48
9.9%
월 21
 
4.3%
산 17
 
3.5%
진 9
 
1.8%
Other values (12) 50
10.3%

높이
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)60.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.4854167
Minimum5
Maximum18.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-04-20T21:38:02.550822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5
Q15.95
median8.55
Q310
95-th percentile13.65
Maximum18.6
Range13.6
Interquartile range (IQR)4.05

Descriptive statistics

Standard deviation3.0551658
Coefficient of variation (CV)0.360049
Kurtosis1.3535601
Mean8.4854167
Median Absolute Deviation (MAD)2.3
Skewness1.0782756
Sum407.3
Variance9.3340381
MonotonicityNot monotonic
2024-04-20T21:38:02.971408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
9.0 6
 
12.5%
10.0 5
 
10.4%
5.0 4
 
8.3%
5.5 3
 
6.2%
6.0 3
 
6.2%
5.3 2
 
4.2%
7.0 2
 
4.2%
12.0 2
 
4.2%
11.0 1
 
2.1%
14.0 1
 
2.1%
Other values (19) 19
39.6%
ValueCountFrequency (%)
5.0 4
8.3%
5.2 1
 
2.1%
5.3 2
4.2%
5.5 3
6.2%
5.6 1
 
2.1%
5.8 1
 
2.1%
6.0 3
6.2%
6.4 1
 
2.1%
6.5 1
 
2.1%
6.6 1
 
2.1%
ValueCountFrequency (%)
18.6 1
 
2.1%
15.5 1
 
2.1%
14.0 1
 
2.1%
13.0 1
 
2.1%
12.5 1
 
2.1%
12.0 2
 
4.2%
11.5 1
 
2.1%
11.0 1
 
2.1%
10.5 1
 
2.1%
10.0 5
10.4%

연장
Real number (ℝ)

Distinct37
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean118.27083
Minimum22
Maximum750
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-04-20T21:38:03.353546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile27.4
Q154.25
median96.5
Q3139.75
95-th percentile242.5
Maximum750
Range728
Interquartile range (IQR)85.5

Descriptive statistics

Standard deviation115.09177
Coefficient of variation (CV)0.97312052
Kurtosis19.463653
Mean118.27083
Median Absolute Deviation (MAD)43
Skewness3.867658
Sum5677
Variance13246.117
MonotonicityNot monotonic
2024-04-20T21:38:03.772201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
110 4
 
8.3%
40 3
 
6.2%
200 2
 
4.2%
55 2
 
4.2%
26 2
 
4.2%
70 2
 
4.2%
30 2
 
4.2%
50 2
 
4.2%
86 1
 
2.1%
72 1
 
2.1%
Other values (27) 27
56.2%
ValueCountFrequency (%)
22 1
 
2.1%
26 2
4.2%
30 2
4.2%
40 3
6.2%
46 1
 
2.1%
50 2
4.2%
52 1
 
2.1%
55 2
4.2%
65 1
 
2.1%
70 2
4.2%
ValueCountFrequency (%)
750 1
2.1%
370 1
2.1%
260 1
2.1%
210 1
2.1%
200 2
4.2%
180 1
2.1%
170 1
2.1%
167 1
2.1%
165 1
2.1%
150 1
2.1%

경사도
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70.291667
Minimum34
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-04-20T21:38:04.138976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile40
Q150.75
median78.5
Q386
95-th percentile90
Maximum90
Range56
Interquartile range (IQR)35.25

Descriptive statistics

Standard deviation19.109938
Coefficient of variation (CV)0.27186633
Kurtosis-1.2906897
Mean70.291667
Median Absolute Deviation (MAD)11.5
Skewness-0.55324355
Sum3374
Variance365.18972
MonotonicityNot monotonic
2024-04-20T21:38:04.459395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
90 8
16.7%
86 5
 
10.4%
40 4
 
8.3%
85 3
 
6.2%
84 3
 
6.2%
88 2
 
4.2%
62 2
 
4.2%
50 2
 
4.2%
44 2
 
4.2%
80 2
 
4.2%
Other values (15) 15
31.2%
ValueCountFrequency (%)
34 1
 
2.1%
37 1
 
2.1%
40 4
8.3%
44 2
4.2%
45 1
 
2.1%
49 1
 
2.1%
50 2
4.2%
51 1
 
2.1%
55 1
 
2.1%
56 1
 
2.1%
ValueCountFrequency (%)
90 8
16.7%
88 2
 
4.2%
87 1
 
2.1%
86 5
10.4%
85 3
 
6.2%
84 3
 
6.2%
80 2
 
4.2%
77 1
 
2.1%
76 1
 
2.1%
75 1
 
2.1%

유형
Categorical

Distinct3
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size512.0 B
옹벽 및 축대
30 
인공
14 
자연
4 

Length

Max length7
Median length7
Mean length5.125
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row옹벽 및 축대
2nd row옹벽 및 축대
3rd row옹벽 및 축대
4th row옹벽 및 축대
5th row인공

Common Values

ValueCountFrequency (%)
옹벽 및 축대 30
62.5%
인공 14
29.2%
자연 4
 
8.3%

Length

2024-04-20T21:38:04.702236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T21:38:04.914871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
옹벽 30
27.8%
및 30
27.8%
축대 30
27.8%
인공 14
13.0%
자연 4
 
3.7%

등급
Categorical

Distinct3
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size512.0 B
C
30 
B
16 
D
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowC
2nd rowC
3rd rowB
4th rowB
5th rowC

Common Values

ValueCountFrequency (%)
C 30
62.5%
B 16
33.3%
D 2
 
4.2%

Length

2024-04-20T21:38:05.358535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T21:38:05.538401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
c 30
62.5%
b 16
33.3%
d 2
 
4.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size512.0 B
2023-09-01
48 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-01
2nd row2023-09-01
3rd row2023-09-01
4th row2023-09-01
5th row2023-09-01

Common Values

ValueCountFrequency (%)
2023-09-01 48
100.0%

Length

2024-04-20T21:38:05.807605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T21:38:06.058141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-01 48
100.0%

Interactions

2024-04-20T21:37:56.172712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T21:37:54.627245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T21:37:55.383368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T21:37:56.417745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T21:37:54.884123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T21:37:55.687517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T21:37:56.666874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T21:37:55.140650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T21:37:55.930223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-20T21:38:06.235630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
명칭위치높이연장경사도유형등급
명칭1.0001.0001.0001.0001.0001.0001.000
위치1.0001.0000.0000.0000.4821.0001.000
높이1.0000.0001.0000.6100.6850.5860.000
연장1.0000.0000.6101.0000.0000.0000.060
경사도1.0000.4820.6850.0001.0000.6490.000
유형1.0001.0000.5860.0000.6491.0000.445
등급1.0001.0000.0000.0600.0000.4451.000
2024-04-20T21:38:06.506734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등급유형
등급1.0000.168
유형0.1681.000
2024-04-20T21:38:06.854186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
높이연장경사도유형등급
높이1.0000.350-0.5580.2870.000
연장0.3501.000-0.1760.0000.000
경사도-0.558-0.1761.0000.4530.000
유형0.2870.0000.4531.0000.168
등급0.0000.0000.0000.1681.000

Missing values

2024-04-20T21:37:56.999519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-20T21:37:57.437899image/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

구분명칭위치높이연장경사도유형등급데이터기준일자
0급경사지MBC방송국 도로옹벽광주광역시 남구 월산동 3035.38686옹벽 및 축대C2023-09-01
1급경사지MBC주차장광주광역시 남구 월산동 269-796.05565옹벽 및 축대C2023-09-01
2급경사지경남아너스빌광주광역시 남구 주월동 11345.517085옹벽 및 축대B2023-09-01
3급경사지광명아파트 도로광주광역시 남구 방림동 54-18.59388옹벽 및 축대B2023-09-01
4급경사지광주 남 송하 N1 지구 남문장례식장광주광역시 남구 송하동 218-5911.513862인공C2023-09-01
5급경사지광주 남 진월 N1 지구 진월대주1차 후면광주광역시 남구 진월동 산17-1012.516749인공C2023-09-01
6급경사지광주 남 진월 N2 지구 진아하이빌 2차 후면광주광역시 남구 진월동 산77-110.521075인공C2023-09-01
7급경사지구동절개지광주광역시 남구 구동 339.04044자연D2023-09-01
8급경사지금호아파트광주광역시 남구 송하동 43-288.610290옹벽 및 축대B2023-09-01
9급경사지남부경찰서광주광역시 남구 봉선동 26-145.87086옹벽 및 축대C2023-09-01
구분명칭위치높이연장경사도유형등급데이터기준일자
38급경사지하늘연가(정문)광주광역시 남구 진월동 3926.64670옹벽 및 축대B2023-09-01
39급경사지형제사 뒤광주광역시 남구 봉선동 11-19.03086인공C2023-09-01
40급경사지호남경전선59광주광역시 남구 양과동 793-110.020040인공B2023-09-01
41급경사지호남경전선60광주광역시 남구 양과동 산213-39.05050인공B2023-09-01
42급경사지호남경전선61광주광역시 남구 양과동 396-16.075040인공B2023-09-01
43급경사지호남경전선62광주광역시 남구 송하동 417-1310.018040인공B2023-09-01
44급경사지호남경전선63광주광역시 남구 송하동 425-5910.012050인공B2023-09-01
45급경사지호반리젠시빌 전면광주광역시 남구 진월동 3886.55290옹벽 및 축대B2023-09-01
46급경사지호반스위트 후면광주광역시 남구 진월동 산294-186.09580옹벽 및 축대C2023-09-01
47급경사지효덕IC 본선(하행) 우측광주광역시 남구 송하동 산5218.626051인공C2023-09-01