Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory576.2 KiB
Average record size in memory59.0 B

Variable types

Categorical3
Numeric3

Dataset

Description전라남도 나주시 16개 저수지의 수심을 격자(5m x 5m) 단위로 제공합니다. X좌표와 Y좌표는 EPSG:5186(중부원점(GRS80) )의 좌표입니다. *2022년 공공데이터 기업매칭 지원사업 결과물
Author전라남도 나주시
URLhttps://www.data.go.kr/data/15110608/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
저수지 is highly overall correlated with 좌표(X) and 2 other fieldsHigh correlation
소재지 is highly overall correlated with 좌표(X) and 2 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)High correlation
저수지 is highly imbalanced (90.0%)Imbalance
소재지 is highly imbalanced (90.0%)Imbalance

Reproduction

Analysis started2023-12-12 17:11:58.296177
Analysis finished2023-12-12 17:12:00.103332
Duration1.81 second
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
9870 
금계
 
130

Length

Max length3
Median length3
Mean length2.987
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
나주호 9870
98.7%
금계 130
 
1.3%

Length

2023-12-13T02:12:00.201269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:12:00.321834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
나주호 9870
98.7%
금계 130
 
1.3%

좌표(X)
Real number (ℝ)

HIGH CORRELATION 

Distinct769
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean185708.32
Minimum163760.43
Maximum187904.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:12:00.456767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum163760.43
5-th percentile184534.5
Q1185214.5
median186084.5
Q3186649.5
95-th percentile187424.5
Maximum187904.5
Range24144.069
Interquartile range (IQR)1435

Descriptive statistics

Standard deviation2653.9134
Coefficient of variation (CV)0.014290762
Kurtosis56.6275
Mean185708.32
Median Absolute Deviation (MAD)710
Skewness-7.2056642
Sum1.8570832 × 109
Variance7043256.5
MonotonicityNot monotonic
2023-12-13T02:12:00.626818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186344.5 37
 
0.4%
186374.5 34
 
0.3%
186264.5 34
 
0.3%
186304.5 31
 
0.3%
185989.5 31
 
0.3%
186549.5 31
 
0.3%
186399.5 30
 
0.3%
186394.5 30
 
0.3%
186279.5 29
 
0.3%
186534.5 29
 
0.3%
Other values (759) 9684
96.8%
ValueCountFrequency (%)
163760.431 1
 
< 0.1%
163765.507 1
 
< 0.1%
163785.81 1
 
< 0.1%
163790.886 1
 
< 0.1%
163795.962 3
< 0.1%
163801.037 3
< 0.1%
163806.113 2
 
< 0.1%
163811.189 4
< 0.1%
163816.264 3
< 0.1%
163821.34 5
0.1%
ValueCountFrequency (%)
187904.5 1
 
< 0.1%
187899.5 1
 
< 0.1%
187894.5 3
< 0.1%
187889.5 1
 
< 0.1%
187884.5 4
< 0.1%
187879.5 6
0.1%
187874.5 1
 
< 0.1%
187869.5 1
 
< 0.1%
187864.5 7
0.1%
187859.5 7
0.1%

좌표(Y)
Real number (ℝ)

HIGH CORRELATION 

Distinct332
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean262831.82
Minimum262108.25
Maximum276530.33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:12:00.787821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum262108.25
5-th percentile262183.26
Q1262388.3
median262653.35
Q3262903.39
95-th percentile263203.44
Maximum276530.33
Range14422.079
Interquartile range (IQR)515.09

Descriptive statistics

Standard deviation1588.9078
Coefficient of variation (CV)0.0060453404
Kurtosis66.393217
Mean262831.82
Median Absolute Deviation (MAD)255.044
Skewness8.1032014
Sum2.6283182 × 109
Variance2524628.1
MonotonicityNot monotonic
2023-12-13T02:12:00.979451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
262803.372 66
 
0.7%
262373.297 63
 
0.6%
262273.279 63
 
0.6%
262688.352 62
 
0.6%
262258.277 62
 
0.6%
262523.323 61
 
0.6%
262488.317 61
 
0.6%
262733.36 60
 
0.6%
262848.38 60
 
0.6%
262853.381 60
 
0.6%
Other values (322) 9382
93.8%
ValueCountFrequency (%)
262108.25 14
 
0.1%
262113.251 41
0.4%
262118.252 32
0.3%
262123.253 21
0.2%
262128.254 37
0.4%
262133.255 35
0.4%
262138.256 47
0.5%
262143.257 41
0.4%
262148.257 35
0.4%
262153.258 30
0.3%
ValueCountFrequency (%)
276530.329 1
 
< 0.1%
276525.276 3
 
< 0.1%
276520.223 2
 
< 0.1%
276515.17 3
 
< 0.1%
276510.117 1
 
< 0.1%
276505.064 2
 
< 0.1%
276500.011 2
 
< 0.1%
276494.958 4
< 0.1%
276489.905 3
 
< 0.1%
276484.852 8
0.1%

수심
Real number (ℝ)

HIGH CORRELATION 

Distinct8134
Distinct (%)81.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-14.647375
Minimum-30.917
Maximum0
Zeros27
Zeros (%)0.3%
Negative9973
Negative (%)99.7%
Memory size166.0 KiB
2023-12-13T02:12:01.169281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-30.917
5-th percentile-26.57525
Q1-19.70075
median-14.355
Q3-8.7345
95-th percentile-5.02855
Maximum0
Range30.917
Interquartile range (IQR)10.96625

Descriptive statistics

Standard deviation6.7820685
Coefficient of variation (CV)-0.46302281
Kurtosis-0.77591726
Mean-14.647375
Median Absolute Deviation (MAD)5.536
Skewness-0.21564209
Sum-146473.75
Variance45.996453
MonotonicityNot monotonic
2023-12-13T02:12:01.351491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 27
 
0.3%
-8.638 6
 
0.1%
-8.209 5
 
0.1%
-11.137 5
 
0.1%
-12.212 4
 
< 0.1%
-8.429 4
 
< 0.1%
-8.38 4
 
< 0.1%
-7.643 4
 
< 0.1%
-16.593 4
 
< 0.1%
-16.979 4
 
< 0.1%
Other values (8124) 9933
99.3%
ValueCountFrequency (%)
-30.917 1
< 0.1%
-30.702 1
< 0.1%
-30.667 1
< 0.1%
-30.663 1
< 0.1%
-30.605 1
< 0.1%
-30.539 1
< 0.1%
-30.492 1
< 0.1%
-30.428 1
< 0.1%
-30.38 1
< 0.1%
-30.368 1
< 0.1%
ValueCountFrequency (%)
0.0 27
0.3%
-0.019 1
 
< 0.1%
-0.023 1
 
< 0.1%
-0.032 1
 
< 0.1%
-0.049 1
 
< 0.1%
-0.061 1
 
< 0.1%
-0.08 1
 
< 0.1%
-0.082 1
 
< 0.1%
-0.089 1
 
< 0.1%
-0.107 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
9870 
전라남도 나주시 문평면 북동리 42
 
130

Length

Max length20
Median length20
Mean length19.987
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 9870
98.7%
전라남도 나주시 문평면 북동리 42 130
 
1.3%

Length

2023-12-13T02:12:01.514065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:12:01.609953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 10000
20.0%
나주시 10000
20.0%
다도면 9870
19.7%
판촌리 9870
19.7%
354 9870
19.7%
문평면 130
 
0.3%
북동리 130
 
0.3%
42 130
 
0.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022-12-16
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-16
2nd row2022-12-16
3rd row2022-12-16
4th row2022-12-16
5th row2022-12-16

Common Values

ValueCountFrequency (%)
2022-12-16 10000
100.0%

Length

2023-12-13T02:12:01.715487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:12:01.817368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-16 10000
100.0%

Interactions

2023-12-13T02:11:59.493798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:11:58.777947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:11:59.103700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:11:59.627334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:11:58.876446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:11:59.219195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:11:59.772619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:11:58.990409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:11:59.358174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:12:01.877817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
저수지좌표(X)좌표(Y)수심소재지
저수지1.0001.0001.0000.4981.000
좌표(X)1.0001.0001.0000.6901.000
좌표(Y)1.0001.0001.0000.4981.000
수심0.4980.6900.4981.0000.498
소재지1.0001.0001.0000.4981.000
2023-12-13T02:12:01.980792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
저수지소재지
저수지1.0000.996
소재지0.9961.000
2023-12-13T02:12:02.066651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
좌표(X)좌표(Y)수심저수지소재지
좌표(X)1.000-0.156-0.7331.0001.000
좌표(Y)-0.1561.000-0.0410.9960.996
수심-0.733-0.0411.0000.3830.383
저수지1.0000.9960.3831.0000.996
소재지1.0000.9960.3830.9961.000

Missing values

2023-12-13T02:11:59.931760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:12:00.044181image/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
34181나주호186454.5262798.371-20.782전라남도 나주시 다도면 판촌리 3542022-12-16
56502나주호185514.5262568.331-11.626전라남도 나주시 다도면 판촌리 3542022-12-16
35352나주호184854.5262783.368-8.638전라남도 나주시 다도면 판촌리 3542022-12-16
46836나주호184774.5262668.348-9.588전라남도 나주시 다도면 판촌리 3542022-12-16
11183나주호185284.5263063.417-9.142전라남도 나주시 다도면 판촌리 3542022-12-16
12701나주호185369.5263038.413-10.578전라남도 나주시 다도면 판촌리 3542022-12-16
12768나주호185804.5263038.413-16.222전라남도 나주시 다도면 판촌리 3542022-12-16
17898나주호186674.5262973.402-21.265전라남도 나주시 다도면 판촌리 3542022-12-16
87095나주호186734.5262228.271-16.424전라남도 나주시 다도면 판촌리 3542022-12-16
88995나주호184534.5262203.267-6.157전라남도 나주시 다도면 판촌리 3542022-12-16
저수지좌표(X)좌표(Y)수심소재지데이터기준일자
18801나주호184674.5262958.399-2.889전라남도 나주시 다도면 판촌리 3542022-12-16
76133나주호186959.5262343.292-21.542전라남도 나주시 다도면 판촌리 3542022-12-16
40581나주호185814.5262733.36-15.634전라남도 나주시 다도면 판촌리 3542022-12-16
7680나주호185274.5263133.43-7.882전라남도 나주시 다도면 판촌리 3542022-12-16
88878나주호187534.5262208.268-28.586전라남도 나주시 다도면 판촌리 3542022-12-16
82373나주호186874.5262278.28-19.952전라남도 나주시 다도면 판촌리 3542022-12-16
73697나주호185004.5262368.296-8.21전라남도 나주시 다도면 판촌리 3542022-12-16
68132나주호185134.5262438.308-8.771전라남도 나주시 다도면 판촌리 3542022-12-16
43281나주호186629.5262708.355-20.991전라남도 나주시 다도면 판촌리 3542022-12-16
34532나주호185729.5262793.37-16.483전라남도 나주시 다도면 판촌리 3542022-12-16