Overview

Dataset statistics

Number of variables4
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory37.3 B

Variable types

Categorical2
Numeric2

Dataset

DescriptionSample
Author㈜지오시스템리서치
URLhttps://www.bigdata-coast.kr/gdsInfo/gdsInfoDetail.do?gdsCd=CT09GSR011

Alerts

VR_SCNRO_ACCTO_STRM_SRG_NM has constant value ""Constant
STRM_SRG_MXM_HGH_LA is highly overall correlated with STRM_SRG_MXM_HGH_LO and 1 other fieldsHigh correlation
STRM_SRG_MXM_HGH_LO is highly overall correlated with STRM_SRG_MXM_HGH_LA and 1 other fieldsHigh correlation
VR_SCNRO_ACCTO_MXM_SRG_HGH is highly overall correlated with STRM_SRG_MXM_HGH_LA and 1 other fieldsHigh correlation
STRM_SRG_MXM_HGH_LA has unique valuesUnique
STRM_SRG_MXM_HGH_LO has unique valuesUnique

Reproduction

Analysis started2024-03-13 12:27:29.885198
Analysis finished2024-03-13 12:27:32.707755
Duration2.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

VR_SCNRO_ACCTO_STRM_SRG_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
100 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 100
100.0%

Length

2024-03-13T21:27:32.853508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:27:33.069478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 100
100.0%

STRM_SRG_MXM_HGH_LA
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.677351
Minimum34.663896
Maximum34.714294
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-13T21:27:33.281550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.663896
5-th percentile34.665946
Q134.668129
median34.670612
Q334.67903
95-th percentile34.712455
Maximum34.714294
Range0.050398088
Interquartile range (IQR)0.010900994

Descriptive statistics

Standard deviation0.015305206
Coefficient of variation (CV)0.00044136031
Kurtosis1.0502009
Mean34.677351
Median Absolute Deviation (MAD)0.0032293257
Skewness1.6028616
Sum3467.7351
Variance0.00023424933
MonotonicityNot monotonic
2024-03-13T21:27:33.515416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.6638963624 1
 
1.0%
34.6792927914 1
 
1.0%
34.6724037968 1
 
1.0%
34.6731641268 1
 
1.0%
34.6713716213 1
 
1.0%
34.6700794249 1
 
1.0%
34.6703807815 1
 
1.0%
34.670599305 1
 
1.0%
34.6707483858 1
 
1.0%
34.6706586822 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
34.6638963624 1
1.0%
34.6643533431 1
1.0%
34.6655549834 1
1.0%
34.6656412052 1
1.0%
34.6657341383 1
1.0%
34.6659575886 1
1.0%
34.6660048653 1
1.0%
34.6660663362 1
1.0%
34.6662577502 1
1.0%
34.6665580971 1
1.0%
ValueCountFrequency (%)
34.7142944501 1
1.0%
34.7142726722 1
1.0%
34.7139623003 1
1.0%
34.713130612 1
1.0%
34.7126407489 1
1.0%
34.7124451174 1
1.0%
34.7122526821 1
1.0%
34.7113819424 1
1.0%
34.7109076946 1
1.0%
34.7105234639 1
1.0%

STRM_SRG_MXM_HGH_LO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.30931
Minimum127.2802
Maximum127.3437
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-13T21:27:33.828385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.2802
5-th percentile127.28521
Q1127.29411
median127.30946
Q3127.31941
95-th percentile127.34114
Maximum127.3437
Range0.063503931
Interquartile range (IQR)0.025300556

Descriptive statistics

Standard deviation0.017678701
Coefficient of variation (CV)0.00013886416
Kurtosis-0.80074833
Mean127.30931
Median Absolute Deviation (MAD)0.011361213
Skewness0.31303063
Sum12730.931
Variance0.00031253646
MonotonicityNot monotonic
2024-03-13T21:27:34.161186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.285219942 1
 
1.0%
127.3195201098 1
 
1.0%
127.3151568311 1
 
1.0%
127.3174617195 1
 
1.0%
127.2877620736 1
 
1.0%
127.2889047968 1
 
1.0%
127.2910096119 1
 
1.0%
127.2933735168 1
 
1.0%
127.2857812616 1
 
1.0%
127.2958019832 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
127.2801969777 1
1.0%
127.2819733176 1
1.0%
127.2837038718 1
1.0%
127.2842390829 1
1.0%
127.2849271492 1
1.0%
127.285219942 1
1.0%
127.2853996649 1
1.0%
127.2854262237 1
1.0%
127.2857812616 1
1.0%
127.2863218057 1
1.0%
ValueCountFrequency (%)
127.3437009083 1
1.0%
127.3433582518 1
1.0%
127.3428011065 1
1.0%
127.3418122671 1
1.0%
127.3414162076 1
1.0%
127.3411288269 1
1.0%
127.3409048434 1
1.0%
127.3396415179 1
1.0%
127.3392302268 1
1.0%
127.3389437153 1
1.0%

VR_SCNRO_ACCTO_MXM_SRG_HGH
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.175
68 
0.171
15 
0.174
10 
0.172
 
4
0.173
 
3

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.175
2nd row0.175
3rd row0.175
4th row0.175
5th row0.175

Common Values

ValueCountFrequency (%)
0.175 68
68.0%
0.171 15
 
15.0%
0.174 10
 
10.0%
0.172 4
 
4.0%
0.173 3
 
3.0%

Length

2024-03-13T21:27:34.536446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:27:34.801975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.175 68
68.0%
0.171 15
 
15.0%
0.174 10
 
10.0%
0.172 4
 
4.0%
0.173 3
 
3.0%

Interactions

2024-03-13T21:27:32.015032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:31.567237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:32.217070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:31.820065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:27:34.962692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
STRM_SRG_MXM_HGH_LASTRM_SRG_MXM_HGH_LOVR_SCNRO_ACCTO_MXM_SRG_HGH
STRM_SRG_MXM_HGH_LA1.0000.7630.900
STRM_SRG_MXM_HGH_LO0.7631.0000.942
VR_SCNRO_ACCTO_MXM_SRG_HGH0.9000.9421.000
2024-03-13T21:27:35.131513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
STRM_SRG_MXM_HGH_LASTRM_SRG_MXM_HGH_LOVR_SCNRO_ACCTO_MXM_SRG_HGH
STRM_SRG_MXM_HGH_LA1.0000.6750.814
STRM_SRG_MXM_HGH_LO0.6751.0000.656
VR_SCNRO_ACCTO_MXM_SRG_HGH0.8140.6561.000

Missing values

2024-03-13T21:27:32.470313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:27:32.658618image/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

VR_SCNRO_ACCTO_STRM_SRG_NMSTRM_SRG_MXM_HGH_LASTRM_SRG_MXM_HGH_LOVR_SCNRO_ACCTO_MXM_SRG_HGH
0134.663896127.285220.175
1134.664353127.2867440.175
2134.665641127.28540.175
3134.665958127.2876340.175
4134.666819127.2870150.175
5134.668748127.3179330.175
6134.667294127.3166470.175
7134.666066127.3150760.175
8134.665555127.3130050.175
9134.665734127.3108340.175
VR_SCNRO_ACCTO_STRM_SRG_NMSTRM_SRG_MXM_HGH_LASTRM_SRG_MXM_HGH_LOVR_SCNRO_ACCTO_MXM_SRG_HGH
90134.672185127.2842390.175
91134.689617127.3264220.172
92134.688266127.324980.172
93134.687235127.3231920.172
94134.68592127.3217010.172
95134.684383127.3205610.173
96134.682822127.3194790.173
97134.680866127.3174370.174
98134.682796127.3176830.173
99134.67238127.2975060.175