Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory576.2 KiB
Average record size in memory59.0 B

Variable types

Categorical2
Numeric3
DateTime1

Dataset

Description전라남도 나주시 소재 16개 저수지의 항적수심을 제공합니다. X좌표와 Y좌표는 5186 좌표계(GRS80)의 좌표를 의미합니다. *2022년 공공데이터 기업매칭 지원사업 결과
Author전라남도 나주시
URLhttps://www.data.go.kr/data/15110609/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 1 (< 0.1%) duplicate rowsDuplicates
저수지 is highly overall correlated with 좌표(X) and 3 other fieldsHigh correlation
소재지 is highly overall correlated with 좌표(X) and 3 other fieldsHigh correlation
좌표(X) is highly overall correlated with 수심 and 2 other fieldsHigh correlation
좌표(Y) is highly overall correlated with 저수지 and 1 other fieldsHigh correlation
수심 is highly overall correlated with 좌표(X) and 2 other fieldsHigh correlation
저수지 is highly imbalanced (63.7%)Imbalance
소재지 is highly imbalanced (63.7%)Imbalance

Reproduction

Analysis started2023-12-12 01:54:56.383568
Analysis finished2023-12-12 01:54:58.477822
Duration2.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

저수지
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
나주호
9307 
금계
 
693

Length

Max length3
Median length3
Mean length2.9307
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
나주호 9307
93.1%
금계 693
 
6.9%

Length

2023-12-12T10:54:58.565913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:54:58.698269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
나주호 9307
93.1%
금계 693
 
6.9%

좌표(X)
Real number (ℝ)

HIGH CORRELATION 

Distinct9939
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean185046.56
Minimum163770.11
Maximum188429.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T10:54:58.841316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum163770.11
5-th percentile163909.61
Q1186198.83
median186475.57
Q3186748.1
95-th percentile188016.65
Maximum188429.23
Range24659.115
Interquartile range (IQR)549.26475

Descriptive statistics

Standard deviation5802.4498
Coefficient of variation (CV)0.031356703
Kurtosis9.299969
Mean185046.56
Median Absolute Deviation (MAD)275.0125
Skewness-3.3400728
Sum1.8504656 × 109
Variance33668424
MonotonicityNot monotonic
2023-12-12T10:54:59.029404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186481.083 6
 
0.1%
186460.186 5
 
0.1%
185844.425 4
 
< 0.1%
186458.793 4
 
< 0.1%
185869.501 3
 
< 0.1%
186659.402 3
 
< 0.1%
186748.562 3
 
< 0.1%
163921.063 3
 
< 0.1%
186711.042 3
 
< 0.1%
187883.458 2
 
< 0.1%
Other values (9929) 9964
99.6%
ValueCountFrequency (%)
163770.111 1
< 0.1%
163773.021 1
< 0.1%
163778.282 1
< 0.1%
163778.308 1
< 0.1%
163778.412 1
< 0.1%
163778.672 1
< 0.1%
163779.218 1
< 0.1%
163779.452 1
< 0.1%
163779.794 1
< 0.1%
163779.862 1
< 0.1%
ValueCountFrequency (%)
188429.226 1
< 0.1%
188420.977 1
< 0.1%
188411.425 1
< 0.1%
188409.254 1
< 0.1%
188408.214 1
< 0.1%
188406.477 1
< 0.1%
188403.438 1
< 0.1%
188402.569 1
< 0.1%
188402.307 1
< 0.1%
188394.491 1
< 0.1%

좌표(Y)
Real number (ℝ)

HIGH CORRELATION 

Distinct9919
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean260726.41
Minimum258125.11
Maximum276529.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T10:54:59.177713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum258125.11
5-th percentile258391.9
Q1259060.47
median259635.27
Q3260209.83
95-th percentile276368.95
Maximum276529.72
Range18404.612
Interquartile range (IQR)1149.3607

Descriptive statistics

Standard deviation4334.6139
Coefficient of variation (CV)0.016625143
Kurtosis8.9275374
Mean260726.41
Median Absolute Deviation (MAD)574.639
Skewness3.2513734
Sum2.6072641 × 109
Variance18788878
MonotonicityNot monotonic
2023-12-12T10:54:59.366198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
258959.587 29
 
0.3%
258960.98 27
 
0.3%
258791.019 8
 
0.1%
258875.999 3
 
< 0.1%
258664.244 3
 
< 0.1%
258958.194 2
 
< 0.1%
258955.407 2
 
< 0.1%
259575.642 2
 
< 0.1%
258948.443 2
 
< 0.1%
276513.287 2
 
< 0.1%
Other values (9909) 9920
99.2%
ValueCountFrequency (%)
258125.105 1
< 0.1%
258127.891 2
< 0.1%
258129.947 1
< 0.1%
258131.397 1
< 0.1%
258131.882 1
< 0.1%
258132.071 1
< 0.1%
258132.17 1
< 0.1%
258133.065 1
< 0.1%
258134.854 1
< 0.1%
258137.068 1
< 0.1%
ValueCountFrequency (%)
276529.717 1
< 0.1%
276528.875 1
< 0.1%
276528.518 1
< 0.1%
276527.81 1
< 0.1%
276527.457 1
< 0.1%
276526.297 1
< 0.1%
276524.685 1
< 0.1%
276522.751 1
< 0.1%
276522.311 1
< 0.1%
276522.24 1
< 0.1%

수심
Real number (ℝ)

HIGH CORRELATION 

Distinct7124
Distinct (%)71.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-13.852783
Minimum-22.141
Maximum0
Zeros1
Zeros (%)< 0.1%
Negative9999
Negative (%)> 99.9%
Memory size166.0 KiB
2023-12-12T10:54:59.555740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-22.141
5-th percentile-19.6851
Q1-17.095
median-14.546
Q3-11.516
95-th percentile-5.1074
Maximum0
Range22.141
Interquartile range (IQR)5.579

Descriptive statistics

Standard deviation4.2899606
Coefficient of variation (CV)-0.30968222
Kurtosis0.32062818
Mean-13.852783
Median Absolute Deviation (MAD)2.75
Skewness0.77381365
Sum-138527.83
Variance18.403762
MonotonicityNot monotonic
2023-12-12T10:55:00.056709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-15.099 6
 
0.1%
-17.269 6
 
0.1%
-8.977 5
 
0.1%
-13.791 5
 
0.1%
-15.979 5
 
0.1%
-17.415 5
 
0.1%
-17.697 5
 
0.1%
-12.799 5
 
0.1%
-17.641 5
 
0.1%
-17.252 5
 
0.1%
Other values (7114) 9948
99.5%
ValueCountFrequency (%)
-22.141 1
< 0.1%
-21.974 1
< 0.1%
-21.703 1
< 0.1%
-21.679 1
< 0.1%
-21.589 1
< 0.1%
-21.538 1
< 0.1%
-21.511 1
< 0.1%
-21.504 1
< 0.1%
-21.497 1
< 0.1%
-21.494 1
< 0.1%
ValueCountFrequency (%)
0.0 1
< 0.1%
-0.003890861 1
< 0.1%
-0.571 1
< 0.1%
-0.582 1
< 0.1%
-0.658 2
< 0.1%
-0.703 1
< 0.1%
-0.706 1
< 0.1%
-0.708 1
< 0.1%
-0.736 1
< 0.1%
-0.753 1
< 0.1%

소재지
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
전라남도 나주시 다도면 판촌리 354
9307 
전라남도 나주시 문평면 북동리 42
 
693

Length

Max length20
Median length20
Mean length19.9307
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전라남도 나주시 다도면 판촌리 354
2nd row전라남도 나주시 다도면 판촌리 354
3rd row전라남도 나주시 다도면 판촌리 354
4th row전라남도 나주시 다도면 판촌리 354
5th row전라남도 나주시 다도면 판촌리 354

Common Values

ValueCountFrequency (%)
전라남도 나주시 다도면 판촌리 354 9307
93.1%
전라남도 나주시 문평면 북동리 42 693
 
6.9%

Length

2023-12-12T10:55:00.219649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:55:00.338761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 10000
20.0%
나주시 10000
20.0%
다도면 9307
18.6%
판촌리 9307
18.6%
354 9307
18.6%
문평면 693
 
1.4%
북동리 693
 
1.4%
42 693
 
1.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-12-16 00:00:00
Maximum2022-12-16 00:00:00
2023-12-12T10:55:00.455926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:55:00.606137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T10:54:57.901567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:54:57.040742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:54:57.479829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:54:58.016189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:54:57.174642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:54:57.609475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:54:58.146838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:54:57.347851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:54:57.769592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:55:00.707080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
저수지좌표(X)좌표(Y)수심소재지
저수지1.0001.0001.0000.9831.000
좌표(X)1.0001.0000.9460.7691.000
좌표(Y)1.0000.9461.0000.8611.000
수심0.9830.7690.8611.0000.983
소재지1.0001.0001.0000.9831.000
2023-12-12T10:55:00.824564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
저수지소재지
저수지1.0000.999
소재지0.9991.000
2023-12-12T10:55:00.917835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
좌표(X)좌표(Y)수심저수지소재지
좌표(X)1.0000.278-0.5131.0001.000
좌표(Y)0.2781.000-0.4321.0001.000
수심-0.513-0.4321.0000.8850.885
저수지1.0001.0000.8851.0000.999
소재지1.0001.0000.8850.9991.000

Missing values

2023-12-12T10:54:58.271064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:54:58.408775image/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

저수지좌표(X)좌표(Y)수심소재지데이터기준일자
70364나주호186751.266259752.749-17.087전라남도 나주시 다도면 판촌리 3542022-12-16
65073나주호186591.321259602.151-16.772전라남도 나주시 다도면 판촌리 3542022-12-16
74664나주호186351.529259008.29-12.201전라남도 나주시 다도면 판촌리 3542022-12-16
38334나주호186672.655260319.185-18.58전라남도 나주시 다도면 판촌리 3542022-12-16
61183나주호186338.121259257.206-14.432전라남도 나주시 다도면 판촌리 3542022-12-16
25199나주호186550.829258701.244-12.282전라남도 나주시 다도면 판촌리 3542022-12-16
49029나주호186676.41260092.918-18.289전라남도 나주시 다도면 판촌리 3542022-12-16
55878나주호186838.795260208.83-19.338전라남도 나주시 다도면 판촌리 3542022-12-16
59914나주호186604.594259740.563-17.321전라남도 나주시 다도면 판촌리 3542022-12-16
65451나주호186785.646259926.376-18.377전라남도 나주시 다도면 판촌리 3542022-12-16
저수지좌표(X)좌표(Y)수심소재지데이터기준일자
8832나주호186468.629258264.549-8.896전라남도 나주시 다도면 판촌리 3542022-12-16
34869나주호186520.022260180.786-18.197전라남도 나주시 다도면 판촌리 3542022-12-16
21174나주호186619.524258602.274-10.652전라남도 나주시 다도면 판촌리 3542022-12-16
24674나주호186846.081258393.243-10.273전라남도 나주시 다도면 판촌리 3542022-12-16
78854나주호186977.443259936.342-17.394전라남도 나주시 다도면 판촌리 3542022-12-16
19655나주호186538.628258648.159-11.987전라남도 나주시 다도면 판촌리 3542022-12-16
35055나주호186650.84260360.297-19.14전라남도 나주시 다도면 판촌리 3542022-12-16
85128나주호187063.842259991.083-7.355전라남도 나주시 다도면 판촌리 3542022-12-16
78322나주호186558.976259238.142-13.463전라남도 나주시 다도면 판촌리 3542022-12-16
33971나주호186058.371259410.536-14.67전라남도 나주시 다도면 판촌리 3542022-12-16

Duplicate rows

Most frequently occurring

저수지좌표(X)좌표(Y)수심소재지데이터기준일자# duplicates
0금계163874.665276334.601-1.309전라남도 나주시 문평면 북동리 422022-12-162