Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory419.9 KiB
Average record size in memory43.0 B

Variable types

Categorical1
Numeric3

Dataset

Description2022년도 새만금호 수심좌표 데이터 입니다. 원통도법인 횡축메르카토르(TM)투영법으로 측정하여 x축과 y축의 좌표정보를 제공합니다.
URLhttps://www.data.go.kr/data/15120059/fileData.do

Alerts

기준일 has constant value ""Constant

Reproduction

Analysis started2023-12-12 08:43:32.974404
Analysis finished2023-12-12 08:43:34.712492
Duration1.74 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022-06-01
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-06-01
2nd row2022-06-01
3rd row2022-06-01
4th row2022-06-01
5th row2022-06-01

Common Values

ValueCountFrequency (%)
2022-06-01 10000
100.0%

Length

2023-12-12T17:43:34.772969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:43:34.857480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-06-01 10000
100.0%

X축
Real number (ℝ)

Distinct632
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean162304.78
Minimum153050
Maximum185200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:43:34.954766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum153050
5-th percentile155500
Q1158050
median160450
Q3164100
95-th percentile177650
Maximum185200
Range32150
Interquartile range (IQR)6050

Descriptive statistics

Standard deviation6437.135
Coefficient of variation (CV)0.039660785
Kurtosis1.7118965
Mean162304.78
Median Absolute Deviation (MAD)2650
Skewness1.4827034
Sum1.6230478 × 109
Variance41436707
MonotonicityNot monotonic
2023-12-12T17:43:35.102508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
158100 69
 
0.7%
157750 69
 
0.7%
158350 67
 
0.7%
157500 64
 
0.6%
159100 63
 
0.6%
159250 63
 
0.6%
158500 63
 
0.6%
160300 63
 
0.6%
157950 63
 
0.6%
157850 60
 
0.6%
Other values (622) 9356
93.6%
ValueCountFrequency (%)
153050 1
 
< 0.1%
153150 1
 
< 0.1%
153200 1
 
< 0.1%
153250 4
< 0.1%
153300 3
< 0.1%
153350 2
 
< 0.1%
153400 3
< 0.1%
153450 1
 
< 0.1%
153500 5
0.1%
153550 5
0.1%
ValueCountFrequency (%)
185200 1
 
< 0.1%
185000 1
 
< 0.1%
184950 1
 
< 0.1%
184900 3
< 0.1%
184850 5
0.1%
184800 1
 
< 0.1%
184750 1
 
< 0.1%
184700 1
 
< 0.1%
184650 1
 
< 0.1%
184600 1
 
< 0.1%

Y축
Real number (ℝ)

Distinct500
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean358504.08
Minimum345000
Maximum370700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:43:35.253868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum345000
5-th percentile348400
Q1354900
median359000
Q3362700
95-th percentile366950
Maximum370700
Range25700
Interquartile range (IQR)7800

Descriptive statistics

Standard deviation5590.4595
Coefficient of variation (CV)0.015593852
Kurtosis-0.69349177
Mean358504.08
Median Absolute Deviation (MAD)3850
Skewness-0.31080253
Sum3.5850408 × 109
Variance31253237
MonotonicityNot monotonic
2023-12-12T17:43:35.421412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
357650 56
 
0.6%
362750 51
 
0.5%
362850 50
 
0.5%
362650 48
 
0.5%
357800 47
 
0.5%
360900 47
 
0.5%
362300 47
 
0.5%
358200 46
 
0.5%
362600 45
 
0.4%
358600 44
 
0.4%
Other values (490) 9519
95.2%
ValueCountFrequency (%)
345000 2
< 0.1%
345200 1
 
< 0.1%
345300 1
 
< 0.1%
345400 2
< 0.1%
345600 4
< 0.1%
345650 1
 
< 0.1%
345700 1
 
< 0.1%
345750 3
< 0.1%
345800 2
< 0.1%
345850 4
< 0.1%
ValueCountFrequency (%)
370700 2
< 0.1%
370650 1
 
< 0.1%
370600 4
< 0.1%
370550 2
< 0.1%
370500 1
 
< 0.1%
370450 1
 
< 0.1%
370400 2
< 0.1%
370350 1
 
< 0.1%
370200 2
< 0.1%
370150 2
< 0.1%

지반높이제곱킬로미터
Real number (ℝ)

Distinct2077
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-5.410987
Minimum-44.57
Maximum20.9
Zeros25
Zeros (%)0.2%
Negative8938
Negative (%)89.4%
Memory size166.0 KiB
2023-12-12T17:43:35.602779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-44.57
5-th percentile-14.71
Q1-7.75
median-4.17
Q3-1.88
95-th percentile0.9
Maximum20.9
Range65.47
Interquartile range (IQR)5.87

Descriptive statistics

Standard deviation5.6664683
Coefficient of variation (CV)-1.0472153
Kurtosis9.4881185
Mean-5.410987
Median Absolute Deviation (MAD)2.625
Skewness-2.217346
Sum-54109.87
Variance32.108863
MonotonicityNot monotonic
2023-12-12T17:43:35.785987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6 43
 
0.4%
0.5 40
 
0.4%
0.7 34
 
0.3%
0.4 33
 
0.3%
0.9 30
 
0.3%
-1.8 29
 
0.3%
0.1 28
 
0.3%
-1.4 28
 
0.3%
0.3 27
 
0.3%
-1.7 26
 
0.3%
Other values (2067) 9682
96.8%
ValueCountFrequency (%)
-44.57 1
< 0.1%
-44.29 1
< 0.1%
-44.18 1
< 0.1%
-44.11 1
< 0.1%
-44.05 1
< 0.1%
-43.99 1
< 0.1%
-43.96 1
< 0.1%
-43.94 2
< 0.1%
-43.87 1
< 0.1%
-43.61 1
< 0.1%
ValueCountFrequency (%)
20.9 1
< 0.1%
15.8 1
< 0.1%
13.1 1
< 0.1%
11.6 1
< 0.1%
10.7 1
< 0.1%
10.0 1
< 0.1%
8.6 1
< 0.1%
8.4 1
< 0.1%
8.0 1
< 0.1%
7.3 1
< 0.1%

Interactions

2023-12-12T17:43:34.223147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:43:33.290363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:43:33.904870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:43:34.329026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:43:33.388856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:43:34.030720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:43:34.447317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:43:33.802922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:43:34.130142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:43:35.916650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
X축Y축지반높이제곱킬로미터
X축1.0000.6850.573
Y축0.6851.0000.458
지반높이제곱킬로미터0.5730.4581.000
2023-12-12T17:43:36.026495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
X축Y축지반높이제곱킬로미터
X축1.0000.1420.499
Y축0.1421.000-0.009
지반높이제곱킬로미터0.499-0.0091.000

Missing values

2023-12-12T17:43:34.584810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:43:34.673691image/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

기준일X축Y축지반높이제곱킬로미터
422852022-06-01155250359050-12.5
481232022-06-01156000358050-17.09
658562022-06-01178900354350-1.74
672072022-06-01158650353750-10.83
59852022-06-01158400366400-11.17
245992022-06-01157600362300-4.29
334372022-06-01158300360750-6.04
297732022-06-01157150361400-6.11
711882022-06-01157750352300-11.32
18482022-06-01159600367750-5.5
기준일X축Y축지반높이제곱킬로미터
186232022-06-01160700363150-6.16
450282022-06-011620503586001.1
478422022-06-01154450358100-32.65
678262022-06-01160350353450-10.69
274422022-06-01165750361850-0.8
678902022-06-01161300353450-7.75
309072022-06-01167000361200-3.89
152892022-06-01158800363900-3.15
851122022-06-01159950346300-0.6
831902022-06-01161600347600-0.57