Overview

Dataset statistics

Number of variables15
Number of observations50
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.4 KiB
Average record size in memory131.6 B

Variable types

Numeric5
Categorical10

Dataset

DescriptionSample
Author엔에스원소프트㈜
URLhttps://www.bigdata-coast.kr/gdsInfo/gdsInfoDetail.do?gdsCd=CT10NS1013

Alerts

gtr_ym has constant value ""Constant
shp_cog has constant value ""Constant
shp_no has constant value ""Constant
shp_nm has constant value ""Constant
shp_knd_nm has constant value ""Constant
shp_qtmt_nm has constant value ""Constant
rgshb_nm has constant value ""Constant
shp_gtnn has constant value ""Constant
shp_lt has constant value ""Constant
shp_prpos_nm has constant value ""Constant
data_sn is highly overall correlated with gtr_ymdhms and 1 other fieldsHigh correlation
gtr_ymdhms is highly overall correlated with data_sn and 1 other fieldsHigh correlation
shp_lo is highly overall correlated with data_sn and 1 other fieldsHigh correlation
data_sn has unique valuesUnique
gtr_ymdhms has unique valuesUnique
shp_sog has 3 (6.0%) zerosZeros

Reproduction

Analysis started2024-03-13 12:41:34.862468
Analysis finished2024-03-13 12:41:39.111999
Duration4.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

data_sn
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.5
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-13T21:41:39.211143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.45
Q113.25
median25.5
Q337.75
95-th percentile47.55
Maximum50
Range49
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation14.57738
Coefficient of variation (CV)0.57166195
Kurtosis-1.2
Mean25.5
Median Absolute Deviation (MAD)12.5
Skewness0
Sum1275
Variance212.5
MonotonicityStrictly increasing
2024-03-13T21:41:39.426249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
39 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%
41 1
2.0%

gtr_ym
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
202312
50 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row202312
2nd row202312
3rd row202312
4th row202312
5th row202312

Common Values

ValueCountFrequency (%)
202312 50
100.0%

Length

2024-03-13T21:41:39.601558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:41:39.731733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202312 50
100.0%

gtr_ymdhms
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0231204 × 1013
Minimum2.0231204 × 1013
Maximum2.0231204 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-13T21:41:40.420596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0231204 × 1013
5-th percentile2.0231204 × 1013
Q12.0231204 × 1013
median2.0231204 × 1013
Q32.0231204 × 1013
95-th percentile2.0231204 × 1013
Maximum2.0231204 × 1013
Range1180
Interquartile range (IQR)1059.75

Descriptive statistics

Standard deviation514.73813
Coefficient of variation (CV)2.5442783 × 10-11
Kurtosis-1.4789375
Mean2.0231204 × 1013
Median Absolute Deviation (MAD)18
Skewness0.72983173
Sum1.0115602 × 1015
Variance264955.35
MonotonicityStrictly increasing
2024-03-13T21:41:40.606229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20231204112256 1
 
2.0%
20231204113425 1
 
2.0%
20231204112325 1
 
2.0%
20231204112326 1
 
2.0%
20231204112327 1
 
2.0%
20231204112328 1
 
2.0%
20231204112329 1
 
2.0%
20231204113200 1
 
2.0%
20231204113201 1
 
2.0%
20231204113203 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
20231204112256 1
2.0%
20231204112257 1
2.0%
20231204112258 1
2.0%
20231204112259 1
2.0%
20231204112300 1
2.0%
20231204112301 1
2.0%
20231204112302 1
2.0%
20231204112303 1
2.0%
20231204112304 1
2.0%
20231204112305 1
2.0%
ValueCountFrequency (%)
20231204113436 1
2.0%
20231204113435 1
2.0%
20231204113434 1
2.0%
20231204113433 1
2.0%
20231204113432 1
2.0%
20231204113431 1
2.0%
20231204113430 1
2.0%
20231204113429 1
2.0%
20231204113428 1
2.0%
20231204113427 1
2.0%

shp_la
Real number (ℝ)

Distinct34
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.381504
Minimum36.381491
Maximum36.381517
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-13T21:41:40.771955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.381491
5-th percentile36.381491
Q136.381495
median36.381506
Q336.38151
95-th percentile36.381515
Maximum36.381517
Range2.6 × 10-5
Interquartile range (IQR)1.4833275 × 10-5

Descriptive statistics

Standard deviation8.3812525 × 10-6
Coefficient of variation (CV)2.3037125 × 10-7
Kurtosis-0.93847743
Mean36.381504
Median Absolute Deviation (MAD)4.16665 × 10-6
Skewness-0.59063782
Sum1819.0752
Variance7.0245393 × 10-11
MonotonicityNot monotonic
2024-03-13T21:41:40.960141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
36.381506 5
 
10.0%
36.3814908333 3
 
6.0%
36.3814915 3
 
6.0%
36.3815058333 3
 
6.0%
36.3815061667 3
 
6.0%
36.381491 2
 
4.0%
36.3814916667 2
 
4.0%
36.3815043333 2
 
4.0%
36.3815041667 2
 
4.0%
36.3814906667 1
 
2.0%
Other values (24) 24
48.0%
ValueCountFrequency (%)
36.3814906667 1
 
2.0%
36.3814908333 3
6.0%
36.381491 2
4.0%
36.3814911667 1
 
2.0%
36.3814913333 1
 
2.0%
36.3814915 3
6.0%
36.3814916667 2
4.0%
36.3815041667 2
4.0%
36.3815043333 2
4.0%
36.3815056667 1
 
2.0%
ValueCountFrequency (%)
36.3815166667 1
2.0%
36.381516 1
2.0%
36.3815153333 1
2.0%
36.3815145 1
2.0%
36.381514 1
2.0%
36.3815136667 1
2.0%
36.3815133333 1
2.0%
36.381513 1
2.0%
36.3815125 1
2.0%
36.3815116667 1
2.0%

shp_lo
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.39836
Minimum126.39835
Maximum126.39838
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-13T21:41:41.140669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.39835
5-th percentile126.39835
Q1126.39836
median126.39836
Q3126.39836
95-th percentile126.39838
Maximum126.39838
Range2.7 × 10-5
Interquartile range (IQR)4.208325 × 10-6

Descriptive statistics

Standard deviation6.8860088 × 10-6
Coefficient of variation (CV)5.4478625 × 10-8
Kurtosis6.3027042
Mean126.39836
Median Absolute Deviation (MAD)2 × 10-6
Skewness2.6431045
Sum6319.918
Variance4.7417117 × 10-11
MonotonicityNot monotonic
2024-03-13T21:41:41.305801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
126.3983558333 5
 
10.0%
126.3983543333 4
 
8.0%
126.398356 4
 
8.0%
126.3983573333 3
 
6.0%
126.3983808333 2
 
4.0%
126.3983611667 2
 
4.0%
126.3983575 2
 
4.0%
126.3983596667 2
 
4.0%
126.3983556667 2
 
4.0%
126.398355 2
 
4.0%
Other values (20) 22
44.0%
ValueCountFrequency (%)
126.3983541667 1
 
2.0%
126.3983543333 4
8.0%
126.3983545 2
 
4.0%
126.3983546667 1
 
2.0%
126.398355 2
 
4.0%
126.3983553333 1
 
2.0%
126.3983556667 2
 
4.0%
126.3983558333 5
10.0%
126.398356 4
8.0%
126.3983561667 1
 
2.0%
ValueCountFrequency (%)
126.3983811667 1
2.0%
126.398381 1
2.0%
126.3983808333 2
4.0%
126.3983613333 1
2.0%
126.3983611667 2
4.0%
126.398361 2
4.0%
126.3983608333 1
2.0%
126.3983606667 1
2.0%
126.3983603333 1
2.0%
126.39836 1
2.0%

shp_cog
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
0
50 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 50
100.0%

Length

2024-03-13T21:41:41.482295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:41:41.610772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 50
100.0%

shp_sog
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0238
Minimum0
Maximum0.11
Zeros3
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-13T21:41:41.734717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0045
Q10.01
median0.02
Q30.03
95-th percentile0.05
Maximum0.11
Range0.11
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.017830265
Coefficient of variation (CV)0.74917082
Kurtosis10.386112
Mean0.0238
Median Absolute Deviation (MAD)0.01
Skewness2.5001631
Sum1.19
Variance0.00031791837
MonotonicityNot monotonic
2024-03-13T21:41:41.896378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.02 16
32.0%
0.03 12
24.0%
0.01 12
24.0%
0.04 3
 
6.0%
0.0 3
 
6.0%
0.05 2
 
4.0%
0.06 1
 
2.0%
0.11 1
 
2.0%
ValueCountFrequency (%)
0.0 3
 
6.0%
0.01 12
24.0%
0.02 16
32.0%
0.03 12
24.0%
0.04 3
 
6.0%
0.05 2
 
4.0%
0.06 1
 
2.0%
0.11 1
 
2.0%
ValueCountFrequency (%)
0.11 1
 
2.0%
0.06 1
 
2.0%
0.05 2
 
4.0%
0.04 3
 
6.0%
0.03 12
24.0%
0.02 16
32.0%
0.01 12
24.0%
0.0 3
 
6.0%

shp_no
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
95080*********
50 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row95080*********
2nd row95080*********
3rd row95080*********
4th row95080*********
5th row95080*********

Common Values

ValueCountFrequency (%)
95080********* 50
100.0%

Length

2024-03-13T21:41:42.069950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:41:42.234479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
95080 50
100.0%

shp_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
제****호
50 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제****호
2nd row제****호
3rd row제****호
4th row제****호
5th row제****호

Common Values

ValueCountFrequency (%)
제****호 50
100.0%

Length

2024-03-13T21:41:42.437068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:41:42.563668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제****호 50
100.0%

shp_knd_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
기선
50 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기선 50
100.0%

Length

2024-03-13T21:41:42.701821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:41:42.811669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기선 50
100.0%

shp_qtmt_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
FRP
50 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
FRP 50
100.0%

Length

2024-03-13T21:41:42.955578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:41:43.085045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
frp 50
100.0%

rgshb_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
충남 보령시 오천면
50 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충남 보령시 오천면
2nd row충남 보령시 오천면
3rd row충남 보령시 오천면
4th row충남 보령시 오천면
5th row충남 보령시 오천면

Common Values

ValueCountFrequency (%)
충남 보령시 오천면 50
100.0%

Length

2024-03-13T21:41:43.242716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:41:43.411640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충남 50
33.3%
보령시 50
33.3%
오천면 50
33.3%

shp_gtnn
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
7.93
50 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7.93
2nd row7.93
3rd row7.93
4th row7.93
5th row7.93

Common Values

ValueCountFrequency (%)
7.93 50
100.0%

Length

2024-03-13T21:41:43.555270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:41:43.690722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7.93 50
100.0%

shp_lt
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
13
50 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row13
2nd row13
3rd row13
4th row13
5th row13

Common Values

ValueCountFrequency (%)
13 50
100.0%

Length

2024-03-13T21:41:43.811072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:41:43.948254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 50
100.0%

shp_prpos_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
장망류어업
50 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
장망류어업 50
100.0%

Length

2024-03-13T21:41:44.083650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:41:44.227344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장망류어업 50
100.0%

Interactions

2024-03-13T21:41:38.093276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:35.176731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:35.966484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:36.657023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:37.313917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:38.188960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:35.317093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:36.110011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:36.789119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:37.425017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:38.304794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:35.517715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:36.251765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:36.924593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:37.579494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:38.425447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:35.668624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:36.412840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:37.063599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:37.776204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:38.540906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:35.826163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:36.533848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:37.193422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:41:37.942307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:41:44.357235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
data_sngtr_ymdhmsshp_lashp_loshp_sog
data_sn1.0000.7750.8840.8850.299
gtr_ymdhms0.7751.0000.7330.9700.168
shp_la0.8840.7331.0000.8390.000
shp_lo0.8850.9700.8391.0000.157
shp_sog0.2990.1680.0000.1571.000
2024-03-13T21:41:44.522085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
data_sngtr_ymdhmsshp_lashp_loshp_sog
data_sn1.0001.000-0.4450.9220.276
gtr_ymdhms1.0001.000-0.4450.9220.276
shp_la-0.445-0.4451.000-0.375-0.150
shp_lo0.9220.922-0.3751.0000.310
shp_sog0.2760.276-0.1500.3101.000

Missing values

2024-03-13T21:41:38.749501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:41:39.018618image/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

data_sngtr_ymgtr_ymdhmsshp_lashp_loshp_cogshp_sogshp_noshp_nmshp_knd_nmshp_qtmt_nmrgshb_nmshp_gtnnshp_ltshp_prpos_nm
012023122023120411225636.381506126.39835400.0295080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
122023122023120411225736.381506126.39835400.0695080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
232023122023120411225836.381506126.39835400.0295080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
342023122023120411225936.381506126.39835400.0395080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
452023122023120411230036.381506126.39835400.0195080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
562023122023120411230136.381506126.39835400.0295080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
672023122023120411230236.381506126.39835400.0495080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
782023122023120411230336.381506126.39835500.0195080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
892023122023120411230436.381506126.39835500.0195080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
9102023122023120411230536.381506126.39835500.0195080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
data_sngtr_ymgtr_ymdhmsshp_lashp_loshp_cogshp_sogshp_noshp_nmshp_knd_nmshp_qtmt_nmrgshb_nmshp_gtnnshp_ltshp_prpos_nm
40412023122023120411342736.381492126.39836100.0395080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
41422023122023120411342836.381492126.39836100.0595080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
42432023122023120411342936.381491126.39836100.0295080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
43442023122023120411343036.381491126.39836100.0295080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
44452023122023120411343136.381491126.3983600.0295080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
45462023122023120411343236.381491126.3983600.0295080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
46472023122023120411343336.381491126.3983600.0195080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
47482023122023120411343436.381491126.3983600.0295080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
48492023122023120411343536.381491126.39835900.0395080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업
49502023122023120411343636.381491126.39835900.0595080*********제****호기선FRP충남 보령시 오천면7.9313장망류어업