Overview

Dataset statistics

Number of variables14
Number of observations27
Missing cells142
Missing cells (%)37.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory130.9 B

Variable types

Numeric13
Categorical1

Dataset

Description국방부 간부(군인) 계급별, 호봉별 봉급 정보 데이터 입니다. (2020년 기준) 간부(군인) 봉급 정보 변동 시 업데이트 예정입니다.
Author국방부
URLhttps://www.data.go.kr/data/15046064/fileData.do

Alerts

호봉 is highly overall correlated with 소장 and 12 other fieldsHigh correlation
소장 is highly overall correlated with 호봉 and 12 other fieldsHigh correlation
준장 is highly overall correlated with 호봉 and 12 other fieldsHigh correlation
대령 is highly overall correlated with 호봉 and 12 other fieldsHigh correlation
중령 is highly overall correlated with 호봉 and 12 other fieldsHigh correlation
소령 is highly overall correlated with 호봉 and 12 other fieldsHigh correlation
대위 is highly overall correlated with 호봉 and 12 other fieldsHigh correlation
중위 is highly overall correlated with 호봉 and 12 other fieldsHigh correlation
준위 is highly overall correlated with 호봉 and 12 other fieldsHigh correlation
원사 is highly overall correlated with 호봉 and 12 other fieldsHigh correlation
상사 is highly overall correlated with 호봉 and 12 other fieldsHigh correlation
중사 is highly overall correlated with 호봉 and 12 other fieldsHigh correlation
하사 is highly overall correlated with 호봉 and 12 other fieldsHigh correlation
소위 is highly overall correlated with 호봉 and 12 other fieldsHigh correlation
소위 is highly imbalanced (66.0%)Imbalance
소장 has 14 (51.9%) missing valuesMissing
준장 has 14 (51.9%) missing valuesMissing
대령 has 12 (44.4%) missing valuesMissing
중령 has 12 (44.4%) missing valuesMissing
소령 has 13 (48.1%) missing valuesMissing
대위 has 15 (55.6%) missing valuesMissing
중위 has 20 (74.1%) missing valuesMissing
원사 has 12 (44.4%) missing valuesMissing
상사 has 8 (29.6%) missing valuesMissing
중사 has 5 (18.5%) missing valuesMissing
하사 has 17 (63.0%) missing valuesMissing
호봉 has unique valuesUnique
준위 has unique valuesUnique

Reproduction

Analysis started2023-12-13 00:24:57.566517
Analysis finished2023-12-13 00:25:10.825425
Duration13.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

호봉
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T09:25:10.871917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.3
Q17.5
median14
Q320.5
95-th percentile25.7
Maximum27
Range26
Interquartile range (IQR)13

Descriptive statistics

Standard deviation7.9372539
Coefficient of variation (CV)0.56694671
Kurtosis-1.2
Mean14
Median Absolute Deviation (MAD)7
Skewness0
Sum378
Variance63
MonotonicityStrictly increasing
2023-12-13T09:25:10.960645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1 1
 
3.7%
2 1
 
3.7%
27 1
 
3.7%
26 1
 
3.7%
25 1
 
3.7%
24 1
 
3.7%
23 1
 
3.7%
22 1
 
3.7%
21 1
 
3.7%
20 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1 1
3.7%
2 1
3.7%
3 1
3.7%
4 1
3.7%
5 1
3.7%
6 1
3.7%
7 1
3.7%
8 1
3.7%
9 1
3.7%
10 1
3.7%
ValueCountFrequency (%)
27 1
3.7%
26 1
3.7%
25 1
3.7%
24 1
3.7%
23 1
3.7%
22 1
3.7%
21 1
3.7%
20 1
3.7%
19 1
3.7%
18 1
3.7%

소장
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct13
Distinct (%)100.0%
Missing14
Missing (%)51.9%
Infinite0
Infinite (%)0.0%
Mean6139600
Minimum5346400
Maximum6932800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T09:25:11.046704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5346400
5-th percentile5425720
Q15743000
median6139600
Q36536200
95-th percentile6853480
Maximum6932800
Range1586400
Interquartile range (IQR)793200

Descriptive statistics

Standard deviation514845.03
Coefficient of variation (CV)0.083856445
Kurtosis-1.2
Mean6139600
Median Absolute Deviation (MAD)396600
Skewness0
Sum79814800
Variance2.6506541 × 1011
MonotonicityStrictly increasing
2023-12-13T09:25:11.134481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
5346400 1
 
3.7%
5478600 1
 
3.7%
5610800 1
 
3.7%
5743000 1
 
3.7%
5875200 1
 
3.7%
6007400 1
 
3.7%
6139600 1
 
3.7%
6271800 1
 
3.7%
6404000 1
 
3.7%
6536200 1
 
3.7%
Other values (3) 3
 
11.1%
(Missing) 14
51.9%
ValueCountFrequency (%)
5346400 1
3.7%
5478600 1
3.7%
5610800 1
3.7%
5743000 1
3.7%
5875200 1
3.7%
6007400 1
3.7%
6139600 1
3.7%
6271800 1
3.7%
6404000 1
3.7%
6536200 1
3.7%
ValueCountFrequency (%)
6932800 1
3.7%
6800600 1
3.7%
6668400 1
3.7%
6536200 1
3.7%
6404000 1
3.7%
6271800 1
3.7%
6139600 1
3.7%
6007400 1
3.7%
5875200 1
3.7%
5743000 1
3.7%

준장
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct13
Distinct (%)100.0%
Missing14
Missing (%)51.9%
Infinite0
Infinite (%)0.0%
Mean5829700
Minimum5043700
Maximum6615700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T09:25:11.223650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5043700
5-th percentile5122300
Q15436700
median5829700
Q36222700
95-th percentile6537100
Maximum6615700
Range1572000
Interquartile range (IQR)786000

Descriptive statistics

Standard deviation510171.7
Coefficient of variation (CV)0.087512514
Kurtosis-1.2
Mean5829700
Median Absolute Deviation (MAD)393000
Skewness0
Sum75786100
Variance2.6027517 × 1011
MonotonicityStrictly increasing
2023-12-13T09:25:11.309378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
5043700 1
 
3.7%
5174700 1
 
3.7%
5305700 1
 
3.7%
5436700 1
 
3.7%
5567700 1
 
3.7%
5698700 1
 
3.7%
5829700 1
 
3.7%
5960700 1
 
3.7%
6091700 1
 
3.7%
6222700 1
 
3.7%
Other values (3) 3
 
11.1%
(Missing) 14
51.9%
ValueCountFrequency (%)
5043700 1
3.7%
5174700 1
3.7%
5305700 1
3.7%
5436700 1
3.7%
5567700 1
3.7%
5698700 1
3.7%
5829700 1
3.7%
5960700 1
3.7%
6091700 1
3.7%
6222700 1
3.7%
ValueCountFrequency (%)
6615700 1
3.7%
6484700 1
3.7%
6353700 1
3.7%
6222700 1
3.7%
6091700 1
3.7%
5960700 1
3.7%
5829700 1
3.7%
5698700 1
3.7%
5567700 1
3.7%
5436700 1
3.7%

대령
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)100.0%
Missing12
Missing (%)44.4%
Infinite0
Infinite (%)0.0%
Mean5058400
Minimum4094500
Maximum6022300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T09:25:11.401821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4094500
5-th percentile4190890
Q14576450
median5058400
Q35540350
95-th percentile5925910
Maximum6022300
Range1927800
Interquartile range (IQR)963900

Descriptive statistics

Standard deviation615813.12
Coefficient of variation (CV)0.12174069
Kurtosis-1.2
Mean5058400
Median Absolute Deviation (MAD)550800
Skewness0
Sum75876000
Variance3.792258 × 1011
MonotonicityStrictly increasing
2023-12-13T09:25:11.490732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
4094500 1
 
3.7%
4232200 1
 
3.7%
4369900 1
 
3.7%
4507600 1
 
3.7%
4645300 1
 
3.7%
4783000 1
 
3.7%
4920700 1
 
3.7%
5058400 1
 
3.7%
5196100 1
 
3.7%
5333800 1
 
3.7%
Other values (5) 5
18.5%
(Missing) 12
44.4%
ValueCountFrequency (%)
4094500 1
3.7%
4232200 1
3.7%
4369900 1
3.7%
4507600 1
3.7%
4645300 1
3.7%
4783000 1
3.7%
4920700 1
3.7%
5058400 1
3.7%
5196100 1
3.7%
5333800 1
3.7%
ValueCountFrequency (%)
6022300 1
3.7%
5884600 1
3.7%
5746900 1
3.7%
5609200 1
3.7%
5471500 1
3.7%
5333800 1
3.7%
5196100 1
3.7%
5058400 1
3.7%
4920700 1
3.7%
4783000 1
3.7%

중령
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)100.0%
Missing12
Missing (%)44.4%
Infinite0
Infinite (%)0.0%
Mean4562400
Minimum3599200
Maximum5525600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T09:25:11.580692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3599200
5-th percentile3695520
Q14080800
median4562400
Q35044000
95-th percentile5429280
Maximum5525600
Range1926400
Interquartile range (IQR)963200

Descriptive statistics

Standard deviation615365.91
Coefficient of variation (CV)0.13487768
Kurtosis-1.2
Mean4562400
Median Absolute Deviation (MAD)550400
Skewness0
Sum68436000
Variance3.786752 × 1011
MonotonicityStrictly increasing
2023-12-13T09:25:11.668127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3599200 1
 
3.7%
3736800 1
 
3.7%
3874400 1
 
3.7%
4012000 1
 
3.7%
4149600 1
 
3.7%
4287200 1
 
3.7%
4424800 1
 
3.7%
4562400 1
 
3.7%
4700000 1
 
3.7%
4837600 1
 
3.7%
Other values (5) 5
18.5%
(Missing) 12
44.4%
ValueCountFrequency (%)
3599200 1
3.7%
3736800 1
3.7%
3874400 1
3.7%
4012000 1
3.7%
4149600 1
3.7%
4287200 1
3.7%
4424800 1
3.7%
4562400 1
3.7%
4700000 1
3.7%
4837600 1
3.7%
ValueCountFrequency (%)
5525600 1
3.7%
5388000 1
3.7%
5250400 1
3.7%
5112800 1
3.7%
4975200 1
3.7%
4837600 1
3.7%
4700000 1
3.7%
4562400 1
3.7%
4424800 1
3.7%
4287200 1
3.7%

소령
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct14
Distinct (%)100.0%
Missing13
Missing (%)48.1%
Infinite0
Infinite (%)0.0%
Mean3838900
Minimum2965300
Maximum4712500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T09:25:11.756305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2965300
5-th percentile3052660
Q13402100
median3838900
Q34275700
95-th percentile4625140
Maximum4712500
Range1747200
Interquartile range (IQR)873600

Descriptive statistics

Standard deviation562235.54
Coefficient of variation (CV)0.14645746
Kurtosis-1.2
Mean3838900
Median Absolute Deviation (MAD)470400
Skewness0
Sum53744600
Variance3.161088 × 1011
MonotonicityStrictly increasing
2023-12-13T09:25:11.846563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2965300 1
 
3.7%
3099700 1
 
3.7%
3234100 1
 
3.7%
3368500 1
 
3.7%
3502900 1
 
3.7%
3637300 1
 
3.7%
3771700 1
 
3.7%
3906100 1
 
3.7%
4040500 1
 
3.7%
4174900 1
 
3.7%
Other values (4) 4
 
14.8%
(Missing) 13
48.1%
ValueCountFrequency (%)
2965300 1
3.7%
3099700 1
3.7%
3234100 1
3.7%
3368500 1
3.7%
3502900 1
3.7%
3637300 1
3.7%
3771700 1
3.7%
3906100 1
3.7%
4040500 1
3.7%
4174900 1
3.7%
ValueCountFrequency (%)
4712500 1
3.7%
4578100 1
3.7%
4443700 1
3.7%
4309300 1
3.7%
4174900 1
3.7%
4040500 1
3.7%
3906100 1
3.7%
3771700 1
3.7%
3637300 1
3.7%
3502900 1
3.7%

대위
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Infinite0
Infinite (%)0.0%
Mean3108750
Minimum2411900
Maximum3805600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T09:25:11.931083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2411900
5-th percentile2481585
Q12760325
median3108750
Q33457175
95-th percentile3735915
Maximum3805600
Range1393700
Interquartile range (IQR)696850

Descriptive statistics

Standard deviation456823.35
Coefficient of variation (CV)0.1469476
Kurtosis-1.2
Mean3108750
Median Absolute Deviation (MAD)380100
Skewness-7.3235839 × 10-17
Sum37305000
Variance2.0868757 × 1011
MonotonicityStrictly increasing
2023-12-13T09:25:12.023565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2411900 1
 
3.7%
2538600 1
 
3.7%
2665300 1
 
3.7%
2792000 1
 
3.7%
2918700 1
 
3.7%
3045400 1
 
3.7%
3172100 1
 
3.7%
3298800 1
 
3.7%
3425500 1
 
3.7%
3552200 1
 
3.7%
Other values (2) 2
 
7.4%
(Missing) 15
55.6%
ValueCountFrequency (%)
2411900 1
3.7%
2538600 1
3.7%
2665300 1
3.7%
2792000 1
3.7%
2918700 1
3.7%
3045400 1
3.7%
3172100 1
3.7%
3298800 1
3.7%
3425500 1
3.7%
3552200 1
3.7%
ValueCountFrequency (%)
3805600 1
3.7%
3678900 1
3.7%
3552200 1
3.7%
3425500 1
3.7%
3298800 1
3.7%
3172100 1
3.7%
3045400 1
3.7%
2918700 1
3.7%
2792000 1
3.7%
2665300 1
3.7%

중위
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)100.0%
Missing20
Missing (%)74.1%
Infinite0
Infinite (%)0.0%
Mean2189800
Minimum1871200
Maximum2508400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T09:25:12.121631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1871200
5-th percentile1903060
Q12030500
median2189800
Q32349100
95-th percentile2476540
Maximum2508400
Range637200
Interquartile range (IQR)318600

Descriptive statistics

Standard deviation229418.22
Coefficient of variation (CV)0.10476675
Kurtosis-1.2
Mean2189800
Median Absolute Deviation (MAD)212400
Skewness0
Sum15328600
Variance5.263272 × 1010
MonotonicityStrictly increasing
2023-12-13T09:25:12.205599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1871200 1
 
3.7%
1977400 1
 
3.7%
2083600 1
 
3.7%
2189800 1
 
3.7%
2296000 1
 
3.7%
2402200 1
 
3.7%
2508400 1
 
3.7%
(Missing) 20
74.1%
ValueCountFrequency (%)
1871200 1
3.7%
1977400 1
3.7%
2083600 1
3.7%
2189800 1
3.7%
2296000 1
3.7%
2402200 1
3.7%
2508400 1
3.7%
ValueCountFrequency (%)
2508400 1
3.7%
2402200 1
3.7%
2296000 1
3.7%
2189800 1
3.7%
2083600 1
3.7%
1977400 1
3.7%
1871200 1
3.7%

소위
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size348.0 B
<NA>
24 
1710000
 
1
1810800
 
1
1911600
 
1

Length

Max length7
Median length4
Mean length4.3333333
Min length4

Unique

Unique3 ?
Unique (%)11.1%

Sample

1st row1710000
2nd row1810800
3rd row1911600
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 24
88.9%
1710000 1
 
3.7%
1810800 1
 
3.7%
1911600 1
 
3.7%

Length

2023-12-13T09:25:12.300250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:25:12.387775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
88.9%
1710000 1
 
3.7%
1810800 1
 
3.7%
1911600 1
 
3.7%

준위
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3609600
Minimum2230300
Maximum4988900
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T09:25:12.462940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2230300
5-th percentile2368230
Q12919950
median3609600
Q34299250
95-th percentile4850970
Maximum4988900
Range2758600
Interquartile range (IQR)1379300

Descriptive statistics

Standard deviation842142.64
Coefficient of variation (CV)0.23330636
Kurtosis-1.2
Mean3609600
Median Absolute Deviation (MAD)742700
Skewness3.5609296 × 10-17
Sum97459200
Variance7.0920423 × 1011
MonotonicityStrictly increasing
2023-12-13T09:25:12.547831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2230300 1
 
3.7%
2336400 1
 
3.7%
4988900 1
 
3.7%
4882800 1
 
3.7%
4776700 1
 
3.7%
4670600 1
 
3.7%
4564500 1
 
3.7%
4458400 1
 
3.7%
4352300 1
 
3.7%
4246200 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
2230300 1
3.7%
2336400 1
3.7%
2442500 1
3.7%
2548600 1
3.7%
2654700 1
3.7%
2760800 1
3.7%
2866900 1
3.7%
2973000 1
3.7%
3079100 1
3.7%
3185200 1
3.7%
ValueCountFrequency (%)
4988900 1
3.7%
4882800 1
3.7%
4776700 1
3.7%
4670600 1
3.7%
4564500 1
3.7%
4458400 1
3.7%
4352300 1
3.7%
4246200 1
3.7%
4140100 1
3.7%
4034000 1
3.7%

원사
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)100.0%
Missing12
Missing (%)44.4%
Infinite0
Infinite (%)0.0%
Mean3827700
Minimum3127700
Maximum4527700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T09:25:12.633287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3127700
5-th percentile3197700
Q13477700
median3827700
Q34177700
95-th percentile4457700
Maximum4527700
Range1400000
Interquartile range (IQR)700000

Descriptive statistics

Standard deviation447213.6
Coefficient of variation (CV)0.11683611
Kurtosis-1.2
Mean3827700
Median Absolute Deviation (MAD)400000
Skewness0
Sum57415500
Variance2 × 1011
MonotonicityStrictly increasing
2023-12-13T09:25:12.727092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3127700 1
 
3.7%
3227700 1
 
3.7%
3327700 1
 
3.7%
3427700 1
 
3.7%
3527700 1
 
3.7%
3627700 1
 
3.7%
3727700 1
 
3.7%
3827700 1
 
3.7%
3927700 1
 
3.7%
4027700 1
 
3.7%
Other values (5) 5
18.5%
(Missing) 12
44.4%
ValueCountFrequency (%)
3127700 1
3.7%
3227700 1
3.7%
3327700 1
3.7%
3427700 1
3.7%
3527700 1
3.7%
3627700 1
3.7%
3727700 1
3.7%
3827700 1
3.7%
3927700 1
3.7%
4027700 1
3.7%
ValueCountFrequency (%)
4527700 1
3.7%
4427700 1
3.7%
4327700 1
3.7%
4227700 1
3.7%
4127700 1
3.7%
4027700 1
3.7%
3927700 1
3.7%
3827700 1
3.7%
3727700 1
3.7%
3627700 1
3.7%

상사
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)100.0%
Missing8
Missing (%)29.6%
Infinite0
Infinite (%)0.0%
Mean3026300
Minimum2163200
Maximum3889400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T09:25:12.810602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2163200
5-th percentile2249510
Q12594750
median3026300
Q33457850
95-th percentile3803090
Maximum3889400
Range1726200
Interquartile range (IQR)863100

Descriptive statistics

Standard deviation539659.45
Coefficient of variation (CV)0.17832318
Kurtosis-1.2
Mean3026300
Median Absolute Deviation (MAD)479500
Skewness0
Sum57499700
Variance2.9123232 × 1011
MonotonicityStrictly increasing
2023-12-13T09:25:12.901407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
2259100 1
 
3.7%
3889400 1
 
3.7%
3793500 1
 
3.7%
3697600 1
 
3.7%
3601700 1
 
3.7%
3505800 1
 
3.7%
3409900 1
 
3.7%
3314000 1
 
3.7%
3218100 1
 
3.7%
2163200 1
 
3.7%
Other values (9) 9
33.3%
(Missing) 8
29.6%
ValueCountFrequency (%)
2163200 1
3.7%
2259100 1
3.7%
2355000 1
3.7%
2450900 1
3.7%
2546800 1
3.7%
2642700 1
3.7%
2738600 1
3.7%
2834500 1
3.7%
2930400 1
3.7%
3026300 1
3.7%
ValueCountFrequency (%)
3889400 1
3.7%
3793500 1
3.7%
3697600 1
3.7%
3601700 1
3.7%
3505800 1
3.7%
3409900 1
3.7%
3314000 1
3.7%
3218100 1
3.7%
3122200 1
3.7%
3026300 1
3.7%

중사
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)100.0%
Missing5
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2686650
Minimum1744800
Maximum3628500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T09:25:12.999421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1744800
5-th percentile1838985
Q12215725
median2686650
Q33157575
95-th percentile3534315
Maximum3628500
Range1883700
Interquartile range (IQR)941850

Descriptive statistics

Standard deviation582474.72
Coefficient of variation (CV)0.21680335
Kurtosis-1.2
Mean2686650
Median Absolute Deviation (MAD)493350
Skewness3.3927521 × 10-17
Sum59106300
Variance3.392768 × 1011
MonotonicityStrictly increasing
2023-12-13T09:25:13.099109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2821200 1
 
3.7%
3628500 1
 
3.7%
3538800 1
 
3.7%
3449100 1
 
3.7%
3359400 1
 
3.7%
3269700 1
 
3.7%
3180000 1
 
3.7%
3090300 1
 
3.7%
3000600 1
 
3.7%
2910900 1
 
3.7%
Other values (12) 12
44.4%
(Missing) 5
18.5%
ValueCountFrequency (%)
1744800 1
3.7%
1834500 1
3.7%
1924200 1
3.7%
2013900 1
3.7%
2103600 1
3.7%
2193300 1
3.7%
2283000 1
3.7%
2372700 1
3.7%
2462400 1
3.7%
2552100 1
3.7%
ValueCountFrequency (%)
3628500 1
3.7%
3538800 1
3.7%
3449100 1
3.7%
3359400 1
3.7%
3269700 1
3.7%
3180000 1
3.7%
3090300 1
3.7%
3000600 1
3.7%
2910900 1
3.7%
2821200 1
3.7%

하사
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)100.0%
Missing17
Missing (%)63.0%
Infinite0
Infinite (%)0.0%
Mean1789000
Minimum1661200
Maximum1916800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T09:25:13.210468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1661200
5-th percentile1673980
Q11725100
median1789000
Q31852900
95-th percentile1904020
Maximum1916800
Range255600
Interquartile range (IQR)127800

Descriptive statistics

Standard deviation85985.27
Coefficient of variation (CV)0.048063315
Kurtosis-1.2
Mean1789000
Median Absolute Deviation (MAD)71000
Skewness0
Sum17890000
Variance7.3934667 × 109
MonotonicityStrictly increasing
2023-12-13T09:25:13.294441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1661200 1
 
3.7%
1689600 1
 
3.7%
1718000 1
 
3.7%
1746400 1
 
3.7%
1774800 1
 
3.7%
1803200 1
 
3.7%
1831600 1
 
3.7%
1860000 1
 
3.7%
1888400 1
 
3.7%
1916800 1
 
3.7%
(Missing) 17
63.0%
ValueCountFrequency (%)
1661200 1
3.7%
1689600 1
3.7%
1718000 1
3.7%
1746400 1
3.7%
1774800 1
3.7%
1803200 1
3.7%
1831600 1
3.7%
1860000 1
3.7%
1888400 1
3.7%
1916800 1
3.7%
ValueCountFrequency (%)
1916800 1
3.7%
1888400 1
3.7%
1860000 1
3.7%
1831600 1
3.7%
1803200 1
3.7%
1774800 1
3.7%
1746400 1
3.7%
1718000 1
3.7%
1689600 1
3.7%
1661200 1
3.7%

Interactions

2023-12-13T09:25:09.333601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:57.933108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:58.786848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:59.702419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:00.642361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:01.773570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:02.655529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:03.584042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:04.502858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:05.570993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:06.588894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:07.469854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:08.381051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:09.405779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:57.993333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:58.849416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:59.769355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:00.709394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:01.841336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:02.728248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:03.648840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:04.565707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:05.628844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:06.654136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:07.535157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:08.449920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:09.469671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:58.062111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:58.939747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:59.843345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:00.780426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:01.915138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:02.801573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:03.732300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:04.638351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:05.712183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:06.723245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:07.623831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:08.535549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:09.753015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:58.127529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:59.028063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:59.915952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:00.852462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:01.983830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:02.878055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:03.802037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:04.707307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:05.800343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:06.794209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:07.696820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:08.623481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:09.813721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:58.198665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:59.103138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:59.990372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:00.924451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:02.056365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:02.952497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:03.869840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:04.767900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:05.893670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:06.873376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:07.766864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:08.711931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:09.878248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:58.265416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:59.168485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:00.064503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:00.995580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:02.128994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:03.021613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:03.953281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:04.828455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:05.980441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:06.944140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:07.837078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:08.797596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:09.947375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:58.333051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:59.241256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:00.139134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:01.066107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:02.196553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:03.095254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:04.038252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:04.897966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:06.070370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:07.011508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:07.903938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:08.869035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:10.031981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:58.396442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:59.308247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:00.208742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:01.357420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:02.262983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:03.171753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:04.112955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:04.972975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:06.153684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:07.078938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:07.976253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:08.933075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:10.117138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:58.461402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:59.374707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:00.282174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:01.417766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:02.325121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:03.242405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:04.181690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:05.037711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:06.217794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:07.143653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:08.051893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:08.993997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:10.184372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:58.520316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:59.441436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:00.366905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:01.487477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:02.392589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:03.319523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:04.249144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:05.102967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:06.275356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:07.209960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:08.118968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:09.056082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:10.246434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:58.582894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:59.507834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:00.434212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:01.554136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:02.459610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:03.385646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:04.312009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:05.167809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:06.353194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:07.276411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:08.185058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:09.121614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:10.313709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:58.649336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:59.574574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:00.499245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:01.622823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:02.524535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:03.457463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:04.375405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:05.445584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:06.435159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:07.341299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:08.249250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:09.190135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:10.381926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:58.717707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:24:59.643109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:00.570200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:01.697760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:02.591391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:03.520263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:04.435051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:05.505312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:06.516967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:07.408455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:08.320397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:09.257486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:25:13.366751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호봉소장준장대령중령소령대위중위소위준위원사상사중사하사
호봉1.0000.9720.9720.9530.9530.8790.5961.000NaN0.9990.9530.9480.9111.000
소장0.9721.0001.0000.7780.7780.8840.9501.0000.0000.9720.7780.9291.0001.000
준장0.9721.0001.0000.7780.7780.8840.9501.0000.0000.9720.7780.9291.0001.000
대령0.9530.7780.7781.0001.0000.2631.0001.0000.0000.8491.0000.8920.8901.000
중령0.9530.7780.7781.0001.0000.2631.0001.0000.0000.8491.0000.8920.8901.000
소령0.8790.8840.8840.2630.2631.0000.8211.0000.0001.0000.2630.9350.4201.000
대위0.5960.9500.9501.0001.0000.8211.0001.0000.0000.5961.0000.5110.6541.000
중위1.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.000
소위NaN0.0000.0000.0000.0000.0000.0000.0001.000NaN0.0000.000NaN0.000
준위0.9990.9720.9720.8490.8491.0000.5961.000NaN1.0000.8490.9060.8731.000
원사0.9530.7780.7781.0001.0000.2631.0001.0000.0000.8491.0000.8920.8901.000
상사0.9480.9290.9290.8920.8920.9350.5111.0000.0000.9060.8921.0000.9031.000
중사0.9111.0001.0000.8900.8900.4200.6541.000NaN0.8730.8900.9031.0001.000
하사1.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.000
2023-12-13T09:25:13.481359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호봉소장준장대령중령소령대위중위준위원사상사중사하사소위
호봉1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소장1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
준장1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
대령1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
중령1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소령1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
대위1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
중위1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
준위1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
원사1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
상사1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
중사1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
하사1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소위1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-13T09:25:10.472452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:25:10.603368image/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.
2023-12-13T09:25:10.722677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

호봉소장준장대령중령소령대위중위소위준위원사상사중사하사
015346400504370040945003599200296530024119001871200171000022303003127700216320017448001661200
125478600517470042322003736800309970025386001977400181080023364003227700225910018345001689600
235610800530570043699003874400323410026653002083600191160024425003327700235500019242001718000
345743000543670045076004012000336850027920002189800<NA>25486003427700245090020139001746400
455875200556770046453004149600350290029187002296000<NA>26547003527700254680021036001774800
566007400569870047830004287200363730030454002402200<NA>27608003627700264270021933001803200
676139600582970049207004424800377170031721002508400<NA>28669003727700273860022830001831600
78627180059607005058400456240039061003298800<NA><NA>29730003827700283450023727001860000
89640400060917005196100470000040405003425500<NA><NA>30791003927700293040024624001888400
910653620062227005333800483760041749003552200<NA><NA>31852004027700302630025521001916800
호봉소장준장대령중령소령대위중위소위준위원사상사중사하사
1718<NA><NA><NA><NA><NA><NA><NA><NA>4034000<NA>37935003269700<NA>
1819<NA><NA><NA><NA><NA><NA><NA><NA>4140100<NA>38894003359400<NA>
1920<NA><NA><NA><NA><NA><NA><NA><NA>4246200<NA><NA>3449100<NA>
2021<NA><NA><NA><NA><NA><NA><NA><NA>4352300<NA><NA>3538800<NA>
2122<NA><NA><NA><NA><NA><NA><NA><NA>4458400<NA><NA>3628500<NA>
2223<NA><NA><NA><NA><NA><NA><NA><NA>4564500<NA><NA><NA><NA>
2324<NA><NA><NA><NA><NA><NA><NA><NA>4670600<NA><NA><NA><NA>
2425<NA><NA><NA><NA><NA><NA><NA><NA>4776700<NA><NA><NA><NA>
2526<NA><NA><NA><NA><NA><NA><NA><NA>4882800<NA><NA><NA><NA>
2627<NA><NA><NA><NA><NA><NA><NA><NA>4988900<NA><NA><NA><NA>