Overview

Dataset statistics

Number of variables7
Number of observations1868
Missing cells1824
Missing cells (%)13.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory109.6 KiB
Average record size in memory60.1 B

Variable types

Numeric4
Text1
Boolean1
DateTime1

Dataset

Description대구광역시_도로 표준노드 현황_20191127
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15049953&dataSetDetailId=150499531ee6340c39e1a&provdMethod=FILE

Alerts

표준노드ID is highly overall correlated with X좌표 and 1 other fieldsHigh correlation
X좌표 is highly overall correlated with 표준노드IDHigh correlation
Y좌표 is highly overall correlated with 표준노드IDHigh correlation
노드유형코드 has 456 (24.4%) missing valuesMissing
회전제한여부 has 456 (24.4%) missing valuesMissing
X좌표 has 456 (24.4%) missing valuesMissing
Y좌표 has 456 (24.4%) missing valuesMissing
표준노드ID has unique valuesUnique

Reproduction

Analysis started2023-12-10 19:46:17.943130
Analysis finished2023-12-10 19:46:21.789369
Duration3.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

표준노드ID
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1868
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6254043 × 109
Minimum1.5000001 × 109
Maximum3.9101367 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2023-12-11T04:46:21.903244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.5000001 × 109
5-th percentile1.5000094 × 109
Q11.5300021 × 109
median1.5500026 × 109
Q31.5600277 × 109
95-th percentile1.5702029 × 109
Maximum3.9101367 × 109
Range2.4101366 × 109
Interquartile range (IQR)30025650

Descriptive statistics

Standard deviation4.1051259 × 108
Coefficient of variation (CV)0.2525603
Kurtosis20.826399
Mean1.6254043 × 109
Median Absolute Deviation (MAD)19995350
Skewness4.7562724
Sum3.0362553 × 1012
Variance1.6852059 × 1017
MonotonicityNot monotonic
2023-12-11T04:46:22.128921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1510000100 1
 
0.1%
1540031800 1
 
0.1%
1550017900 1
 
0.1%
1520008100 1
 
0.1%
1560028500 1
 
0.1%
1540033500 1
 
0.1%
1550020500 1
 
0.1%
1520008700 1
 
0.1%
1510017800 1
 
0.1%
1510016400 1
 
0.1%
Other values (1858) 1858
99.5%
ValueCountFrequency (%)
1500000100 1
0.1%
1500000200 1
0.1%
1500000300 1
0.1%
1500000400 1
0.1%
1500000500 1
0.1%
1500000600 1
0.1%
1500000700 1
0.1%
1500000800 1
0.1%
1500000900 1
0.1%
1500001000 1
0.1%
ValueCountFrequency (%)
3910136700 1
0.1%
3910071500 1
0.1%
3910071200 1
0.1%
3910071100 1
0.1%
3910020300 1
0.1%
3910020100 1
0.1%
3910019000 1
0.1%
3910015900 1
0.1%
3690163300 1
0.1%
3690163200 1
0.1%

노드명
Text

Distinct1022
Distinct (%)54.7%
Missing0
Missing (%)0.0%
Memory size14.7 KiB
2023-12-11T04:46:22.526497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length4.4791221
Min length1

Characters and Unicode

Total characters8367
Distinct characters377
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique927 ?
Unique (%)49.6%

Sample

1st row반야월네거리
2nd row남평리네거리
3rd row-
4th row-
5th row만촌네거리
ValueCountFrequency (%)
736
35.4%
구지면 61
 
2.9%
응암리 22
 
1.1%
창리 18
 
0.9%
봉무동 16
 
0.8%
화산리 11
 
0.5%
대천동 9
 
0.4%
다사읍 8
 
0.4%
경계 7
 
0.3%
화원읍 6
 
0.3%
Other values (1046) 1185
57.0%
2023-12-11T04:46:23.116120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 832
 
9.9%
리 375
 
4.5%
거 253
 
3.0%
교 239
 
2.9%
구 235
 
2.8%
211
 
2.5%
동 205
 
2.5%
대 180
 
2.2%
1 176
 
2.1%
네 164
 
2.0%
Other values (367) 5497
65.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6196
74.1%
Dash Punctuation 832
 
9.9%
Decimal Number 703
 
8.4%
Uppercase Letter 261
 
3.1%
Space Separator 211
 
2.5%
Open Punctuation 82
 
1.0%
Close Punctuation 82
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 375
 
6.1%
거 253
 
4.1%
교 239
 
3.9%
구 235
 
3.8%
동 205
 
3.3%
대 180
 
2.9%
네 164
 
2.6%
지 148
 
2.4%
앞 143
 
2.3%
산 130
 
2.1%
Other values (335) 4124
66.6%
Uppercase Letter
ValueCountFrequency (%)
C 106
40.6%
I 80
30.7%
J 23
 
8.8%
G 9
 
3.4%
T 7
 
2.7%
B 6
 
2.3%
S 5
 
1.9%
K 5
 
1.9%
E 5
 
1.9%
D 5
 
1.9%
Other values (8) 10
 
3.8%
Decimal Number
ValueCountFrequency (%)
1 176
25.0%
2 105
14.9%
0 70
 
10.0%
5 68
 
9.7%
3 55
 
7.8%
4 52
 
7.4%
6 51
 
7.3%
7 51
 
7.3%
9 42
 
6.0%
8 33
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 832
100.0%
Space Separator
ValueCountFrequency (%)
211
100.0%
Open Punctuation
ValueCountFrequency (%)
( 82
100.0%
Close Punctuation
ValueCountFrequency (%)
) 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6196
74.1%
Common 1910
 
22.8%
Latin 261
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 375
 
6.1%
거 253
 
4.1%
교 239
 
3.9%
구 235
 
3.8%
동 205
 
3.3%
대 180
 
2.9%
네 164
 
2.6%
지 148
 
2.4%
앞 143
 
2.3%
산 130
 
2.1%
Other values (335) 4124
66.6%
Latin
ValueCountFrequency (%)
C 106
40.6%
I 80
30.7%
J 23
 
8.8%
G 9
 
3.4%
T 7
 
2.7%
B 6
 
2.3%
S 5
 
1.9%
K 5
 
1.9%
E 5
 
1.9%
D 5
 
1.9%
Other values (8) 10
 
3.8%
Common
ValueCountFrequency (%)
- 832
43.6%
211
 
11.0%
1 176
 
9.2%
2 105
 
5.5%
( 82
 
4.3%
) 82
 
4.3%
0 70
 
3.7%
5 68
 
3.6%
3 55
 
2.9%
4 52
 
2.7%
Other values (4) 177
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6196
74.1%
ASCII 2171
 
25.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 832
38.3%
211
 
9.7%
1 176
 
8.1%
C 106
 
4.9%
2 105
 
4.8%
( 82
 
3.8%
) 82
 
3.8%
I 80
 
3.7%
0 70
 
3.2%
5 68
 
3.1%
Other values (22) 359
16.5%
Hangul
ValueCountFrequency (%)
리 375
 
6.1%
거 253
 
4.1%
교 239
 
3.9%
구 235
 
3.8%
동 205
 
3.3%
대 180
 
2.9%
네 164
 
2.6%
지 148
 
2.4%
앞 143
 
2.3%
산 130
 
2.1%
Other values (335) 4124
66.6%

노드유형코드
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)0.4%
Missing456
Missing (%)24.4%
Infinite0
Infinite (%)0.0%
Mean101.69901
Minimum101
Maximum108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2023-12-11T04:46:23.307387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1101
median101
Q3101
95-th percentile104
Maximum108
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.6121172
Coefficient of variation (CV)0.015851847
Kurtosis6.5646954
Mean101.69901
Median Absolute Deviation (MAD)0
Skewness2.6084657
Sum143599
Variance2.5989218
MonotonicityNot monotonic
2023-12-11T04:46:23.485017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
101 1119
59.9%
104 157
 
8.4%
108 54
 
2.9%
102 42
 
2.2%
103 32
 
1.7%
105 8
 
0.4%
(Missing) 456
24.4%
ValueCountFrequency (%)
101 1119
59.9%
102 42
 
2.2%
103 32
 
1.7%
104 157
 
8.4%
105 8
 
0.4%
108 54
 
2.9%
ValueCountFrequency (%)
108 54
 
2.9%
105 8
 
0.4%
104 157
 
8.4%
103 32
 
1.7%
102 42
 
2.2%
101 1119
59.9%

회전제한여부
Boolean

MISSING 

Distinct2
Distinct (%)0.1%
Missing456
Missing (%)24.4%
Memory size3.8 KiB
True
1072 
False
340 
(Missing)
456 
ValueCountFrequency (%)
True 1072
57.4%
False 340
 
18.2%
(Missing) 456
24.4%
2023-12-11T04:46:23.656597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

X좌표
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1400
Distinct (%)99.2%
Missing456
Missing (%)24.4%
Infinite0
Infinite (%)0.0%
Mean128.58143
Minimum128.38877
Maximum128.76073
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2023-12-11T04:46:23.842194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.38877
5-th percentile128.47807
Q1128.53887
median128.58517
Q3128.61846
95-th percentile128.7018
Maximum128.76073
Range0.371964
Interquartile range (IQR)0.07959325

Descriptive statistics

Standard deviation0.064385195
Coefficient of variation (CV)0.00050073479
Kurtosis-0.060367821
Mean128.58143
Median Absolute Deviation (MAD)0.0399345
Skewness0.072452915
Sum181556.98
Variance0.0041454533
MonotonicityNot monotonic
2023-12-11T04:46:24.073532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.530613 4
 
0.2%
128.512522 2
 
0.1%
128.474866 2
 
0.1%
128.530592 2
 
0.1%
128.606972 2
 
0.1%
128.721226 2
 
0.1%
128.616752 2
 
0.1%
128.52845 2
 
0.1%
128.61676 2
 
0.1%
128.490378 2
 
0.1%
Other values (1390) 1390
74.4%
(Missing) 456
 
24.4%
ValueCountFrequency (%)
128.388766 1
0.1%
128.397453 1
0.1%
128.39892 1
0.1%
128.41084 1
0.1%
128.416336 1
0.1%
128.420894 1
0.1%
128.422182 1
0.1%
128.432262 1
0.1%
128.434512 1
0.1%
128.434561 1
0.1%
ValueCountFrequency (%)
128.76073 1
0.1%
128.75733 1
0.1%
128.747759 1
0.1%
128.74179 1
0.1%
128.741706 1
0.1%
128.740277 1
0.1%
128.740238 1
0.1%
128.736329 1
0.1%
128.733451 1
0.1%
128.733447 1
0.1%

Y좌표
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1401
Distinct (%)99.2%
Missing456
Missing (%)24.4%
Infinite0
Infinite (%)0.0%
Mean35.863019
Minimum35.646396
Maximum35.99661
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2023-12-11T04:46:24.316572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.646396
5-th percentile35.799718
Q135.839689
median35.86454
Q335.889702
95-th percentile35.938104
Maximum35.99661
Range0.350214
Interquartile range (IQR)0.050014

Descriptive statistics

Standard deviation0.048327041
Coefficient of variation (CV)0.0013475453
Kurtosis3.6212635
Mean35.863019
Median Absolute Deviation (MAD)0.024867
Skewness-0.99291812
Sum50638.582
Variance0.0023355029
MonotonicityNot monotonic
2023-12-11T04:46:24.557799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.842028 2
 
0.1%
35.839666 2
 
0.1%
35.840859 2
 
0.1%
35.865132 2
 
0.1%
35.867344 2
 
0.1%
35.858842 2
 
0.1%
35.844511 2
 
0.1%
35.88872 2
 
0.1%
35.886328 2
 
0.1%
35.859288 2
 
0.1%
Other values (1391) 1392
74.5%
(Missing) 456
 
24.4%
ValueCountFrequency (%)
35.646396 1
0.1%
35.647636 1
0.1%
35.663952 1
0.1%
35.667529 1
0.1%
35.667853 1
0.1%
35.667985 1
0.1%
35.668065 1
0.1%
35.669008 1
0.1%
35.669343 1
0.1%
35.669569 1
0.1%
ValueCountFrequency (%)
35.99661 1
0.1%
35.994876 1
0.1%
35.992718 1
0.1%
35.989907 1
0.1%
35.989682 1
0.1%
35.989467 1
0.1%
35.989213 1
0.1%
35.988396 1
0.1%
35.985502 1
0.1%
35.982062 1
0.1%

적용시작일자
Date

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.7 KiB
Minimum2011-03-24 00:00:00
Maximum2018-10-29 00:00:00
2023-12-11T04:46:24.761408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:46:24.917387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

Interactions

2023-12-11T04:46:20.640153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:46:18.624614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:46:19.300423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:46:19.966285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:46:20.797527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:46:18.769084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:46:19.450144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:46:20.133601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:46:20.983093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:46:18.944996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:46:19.607631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:46:20.294941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:46:21.166631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:46:19.129205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:46:19.765332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:46:20.465525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T04:46:25.038728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표준노드ID노드유형코드회전제한여부X좌표Y좌표적용시작일자
표준노드ID1.0000.7130.0000.2540.1250.270
노드유형코드0.7131.0000.3920.3120.356NaN
회전제한여부0.0000.3921.0000.2030.219NaN
X좌표0.2540.3120.2031.0000.793NaN
Y좌표0.1250.3560.2190.7931.000NaN
적용시작일자0.270NaNNaNNaNNaN1.000
2023-12-11T04:46:25.194894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표준노드ID노드유형코드X좌표Y좌표회전제한여부
표준노드ID1.000-0.007-0.540-0.5450.000
노드유형코드-0.0071.0000.0340.0690.282
X좌표-0.5400.0341.0000.2640.156
Y좌표-0.5450.0690.2641.0000.167
회전제한여부0.0000.2820.1560.1671.000

Missing values

2023-12-11T04:46:21.359351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T04:46:21.520103image/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.
2023-12-11T04:46:21.679042image/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

표준노드ID노드명노드유형코드회전제한여부X좌표Y좌표적용시작일자
01510000100반야월네거리101N128.71354135.865992011-03-24
11520000600남평리네거리101N128.55616735.8635482011-03-24
21550004700-101Y128.64776835.8613692011-03-24
31570008800-101Y128.46267635.8603912011-03-24
41550003900만촌네거리101N128.64602335.8589222011-03-24
51520000200두류네거리101N128.55745135.8579022011-03-24
61570008700-103Y128.43503835.8581912011-03-24
71550003600-101Y128.65063235.856592011-03-24
81550003400-101N128.65339635.8550852011-03-24
91550003300-101Y128.65452835.8545612011-03-24
표준노드ID노드명노드유형코드회전제한여부X좌표Y좌표적용시작일자
18581540008200칠성교서편104Y128.60635235.8761562011-03-24
18591510010000칠성교동편104Y128.60660235.8767682011-03-24
18601500006300신천교서편104Y128.6111535.8735682011-03-24
18611510008900신천교동편104Y128.61211735.8737932011-03-24
18621500003800동신교서편104Y128.61361435.8682792011-03-24
18631510007000동신교동편104Y128.61454735.86822011-03-24
18641500000900대봉교서편104Y128.60746335.8549622011-03-24
18651550014300대봉교동편104Y128.60865835.8548812011-03-24
18661530005800희망교서편104Y128.60601535.8474662011-03-24
18671550011900희망교동편104Y128.60754135.8473672011-03-24