Overview

Dataset statistics

Number of variables10
Number of observations440
Missing cells440
Missing cells (%)10.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.9 KiB
Average record size in memory88.3 B

Variable types

Numeric7
Categorical2
Unsupported1

Dataset

Description연령별 경제활동인구 분기별 현황입니다. 연령, 시도명, 생산가능인구, 경제활동인구, 비경제활동인구수, 경제활동참가율, 고용률 정보를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=139

Alerts

승인상태(W : 대기 has constant value ""Constant
15세이상 생산가능인구(천명) is highly overall correlated with 경제활동인구(천명) and 2 other fieldsHigh correlation
경제활동인구(천명) is highly overall correlated with 15세이상 생산가능인구(천명) and 2 other fieldsHigh correlation
비경제활동인구수(천명) is highly overall correlated with 15세이상 생산가능인구(천명) and 2 other fieldsHigh correlation
경제활동참가율 is highly overall correlated with 고용률High correlation
고용률 is highly overall correlated with 경제활동참가율High correlation
시도명 is highly overall correlated with 15세이상 생산가능인구(천명) and 2 other fieldsHigh correlation
S : 승인) has 440 (100.0%) missing valuesMissing
S : 승인) is an unsupported type, check if it needs cleaning or further analysisUnsupported
연령구분 has 44 (10.0%) zerosZeros

Reproduction

Analysis started2024-01-09 22:05:58.456402
Analysis finished2024-01-09 22:06:02.779375
Duration4.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준분기
Real number (ℝ)

Distinct22
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean202029.68
Minimum201801
Maximum202302
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-01-10T07:06:02.824405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201801
5-th percentile201802
Q1201902
median202003.5
Q3202201
95-th percentile202301
Maximum202302
Range501
Interquartile range (IQR)299

Descriptive statistics

Standard deviation160.09291
Coefficient of variation (CV)0.00079242271
Kurtosis-1.171088
Mean202029.68
Median Absolute Deviation (MAD)102
Skewness0.079696598
Sum88893060
Variance25629.739
MonotonicityIncreasing
2024-01-10T07:06:02.914432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
201801 20
 
4.5%
202101 20
 
4.5%
202302 20
 
4.5%
202301 20
 
4.5%
202204 20
 
4.5%
202203 20
 
4.5%
202202 20
 
4.5%
202201 20
 
4.5%
202104 20
 
4.5%
202103 20
 
4.5%
Other values (12) 240
54.5%
ValueCountFrequency (%)
201801 20
4.5%
201802 20
4.5%
201803 20
4.5%
201804 20
4.5%
201901 20
4.5%
201902 20
4.5%
201903 20
4.5%
201904 20
4.5%
202001 20
4.5%
202002 20
4.5%
ValueCountFrequency (%)
202302 20
4.5%
202301 20
4.5%
202204 20
4.5%
202203 20
4.5%
202202 20
4.5%
202201 20
4.5%
202104 20
4.5%
202103 20
4.5%
202102 20
4.5%
202101 20
4.5%

연령구분
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.8
Minimum0
Maximum75
Zeros44
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-01-10T07:06:02.992938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median45
Q363
95-th percentile75
Maximum75
Range75
Interquartile range (IQR)43

Descriptive statistics

Standard deviation24.770031
Coefficient of variation (CV)0.59258448
Kurtosis-1.2704432
Mean41.8
Median Absolute Deviation (MAD)21.5
Skewness-0.27873412
Sum18392
Variance613.55444
MonotonicityNot monotonic
2024-01-10T07:06:03.073509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 44
10.0%
10 44
10.0%
20 44
10.0%
30 44
10.0%
40 44
10.0%
50 44
10.0%
60 44
10.0%
63 44
10.0%
70 44
10.0%
75 44
10.0%
ValueCountFrequency (%)
0 44
10.0%
10 44
10.0%
20 44
10.0%
30 44
10.0%
40 44
10.0%
50 44
10.0%
60 44
10.0%
63 44
10.0%
70 44
10.0%
75 44
10.0%
ValueCountFrequency (%)
75 44
10.0%
70 44
10.0%
63 44
10.0%
60 44
10.0%
50 44
10.0%
40 44
10.0%
30 44
10.0%
20 44
10.0%
10 44
10.0%
0 44
10.0%

시도명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
220 
충청남도
220 

Length

Max length4
Median length2.5
Mean length2.5
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
220
50.0%
충청남도 220
50.0%

Length

2024-01-10T07:06:03.174116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:06:03.254424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
220
50.0%
충청남도 220
50.0%

15세이상 생산가능인구(천명)
Real number (ℝ)

HIGH CORRELATION 

Distinct434
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7309.6959
Minimum95.5
Maximum45377.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-01-10T07:06:03.351732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum95.5
5-th percentile200.59
Q1333.85
median2080.45
Q38424.65
95-th percentile37182.66
Maximum45377.9
Range45282.4
Interquartile range (IQR)8090.8

Descriptive statistics

Standard deviation11790.819
Coefficient of variation (CV)1.6130382
Kurtosis4.1645595
Mean7309.6959
Median Absolute Deviation (MAD)1918.65
Skewness2.2933256
Sum3216266.2
Variance1.3902341 × 108
MonotonicityNot monotonic
2024-01-10T07:06:03.453679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
332.0 2
 
0.5%
331.7 2
 
0.5%
338.2 2
 
0.5%
332.5 2
 
0.5%
339.4 2
 
0.5%
269.5 2
 
0.5%
266.2 1
 
0.2%
8743.6 1
 
0.2%
1893.2 1
 
0.2%
97.0 1
 
0.2%
Other values (424) 424
96.4%
ValueCountFrequency (%)
95.5 1
0.2%
95.6 1
0.2%
95.9 1
0.2%
96.0 1
0.2%
96.6 1
0.2%
97.0 1
0.2%
97.1 1
0.2%
97.5 1
0.2%
97.8 1
0.2%
99.4 1
0.2%
ValueCountFrequency (%)
45377.9 1
0.2%
45357.9 1
0.2%
45317.1 1
0.2%
45270.5 1
0.2%
45242.3 1
0.2%
45210.6 1
0.2%
45178.4 1
0.2%
45106.0 1
0.2%
45048.2 1
0.2%
44987.4 1
0.2%

경제활동인구(천명)
Real number (ℝ)

HIGH CORRELATION 

Distinct431
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4583.1509
Minimum5.1
Maximum29492.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-01-10T07:06:03.553600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.1
5-th percentile51.46
Q1224.225
median1122.05
Q35476.975
95-th percentile25886.715
Maximum29492.5
Range29487.4
Interquartile range (IQR)5252.75

Descriptive statistics

Standard deviation7805.6397
Coefficient of variation (CV)1.7031165
Kurtosis3.9787973
Mean4583.1509
Median Absolute Deviation (MAD)1001.95
Skewness2.2871015
Sum2016586.4
Variance60928011
MonotonicityNot monotonic
2024-01-10T07:06:03.660263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.3 2
 
0.5%
276.4 2
 
0.5%
162.2 2
 
0.5%
7.8 2
 
0.5%
6.2 2
 
0.5%
283.1 2
 
0.5%
257.9 2
 
0.5%
267.7 2
 
0.5%
281.1 2
 
0.5%
274.8 1
 
0.2%
Other values (421) 421
95.7%
ValueCountFrequency (%)
5.1 1
0.2%
5.2 1
0.2%
5.9 1
0.2%
6.2 2
0.5%
6.5 1
0.2%
7.1 1
0.2%
7.3 2
0.5%
7.8 2
0.5%
7.9 1
0.2%
8.6 1
0.2%
ValueCountFrequency (%)
29492.5 1
0.2%
29227.4 1
0.2%
29142.7 1
0.2%
28956.8 1
0.2%
28684.5 1
0.2%
28596.0 1
0.2%
28451.1 1
0.2%
28444.7 1
0.2%
28431.9 1
0.2%
28359.5 1
0.2%

비경제활동인구수(천명)
Real number (ℝ)

HIGH CORRELATION 

Distinct426
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2726.5441
Minimum44.5
Maximum17239.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-01-10T07:06:03.766067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum44.5
5-th percentile59.475
Q1137.8
median1009.05
Q32767.75
95-th percentile11881.06
Maximum17239.4
Range17194.9
Interquartile range (IQR)2629.95

Descriptive statistics

Standard deviation4179.158
Coefficient of variation (CV)1.5327674
Kurtosis3.9164406
Mean2726.5441
Median Absolute Deviation (MAD)937.4
Skewness2.1468719
Sum1199679.4
Variance17465362
MonotonicityNot monotonic
2024-01-10T07:06:03.871291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
97.4 5
 
1.1%
62.1 2
 
0.5%
68.7 2
 
0.5%
101.3 2
 
0.5%
198.7 2
 
0.5%
62.0 2
 
0.5%
69.8 2
 
0.5%
102.8 2
 
0.5%
86.1 2
 
0.5%
107.7 2
 
0.5%
Other values (416) 417
94.8%
ValueCountFrequency (%)
44.5 1
0.2%
48.6 1
0.2%
49.6 1
0.2%
49.7 1
0.2%
50.6 1
0.2%
50.7 1
0.2%
51.4 1
0.2%
51.9 1
0.2%
52.4 1
0.2%
52.8 1
0.2%
ValueCountFrequency (%)
17239.4 1
0.2%
16888.8 1
0.2%
16851.0 1
0.2%
16781.2 1
0.2%
16744.2 1
0.2%
16733.7 1
0.2%
16676.8 1
0.2%
16673.4 1
0.2%
16668.2 1
0.2%
16654.9 1
0.2%

경제활동참가율
Real number (ℝ)

HIGH CORRELATION 

Distinct271
Distinct (%)61.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.847045
Minimum5.1
Maximum85.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-01-10T07:06:03.977593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.1
5-th percentile7.995
Q144.775
median63.5
Q377.425
95-th percentile81.705
Maximum85.1
Range80
Interquartile range (IQR)32.65

Descriptive statistics

Standard deviation22.744424
Coefficient of variation (CV)0.40009861
Kurtosis-0.30666887
Mean56.847045
Median Absolute Deviation (MAD)15.4
Skewness-0.85530986
Sum25012.7
Variance517.30883
MonotonicityNot monotonic
2024-01-10T07:06:04.119857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80.0 5
 
1.1%
79.8 5
 
1.1%
77.8 5
 
1.1%
62.4 5
 
1.1%
77.5 4
 
0.9%
79.7 4
 
0.9%
65.8 4
 
0.9%
78.0 4
 
0.9%
46.8 4
 
0.9%
78.2 4
 
0.9%
Other values (261) 396
90.0%
ValueCountFrequency (%)
5.1 1
 
0.2%
5.2 1
 
0.2%
6.1 1
 
0.2%
6.3 2
0.5%
6.4 2
0.5%
6.9 3
0.7%
7.1 2
0.5%
7.2 2
0.5%
7.4 2
0.5%
7.5 2
0.5%
ValueCountFrequency (%)
85.1 1
0.2%
84.7 1
0.2%
84.6 1
0.2%
84.4 1
0.2%
84.3 1
0.2%
84.2 1
0.2%
84.1 1
0.2%
83.5 1
0.2%
82.9 2
0.5%
82.8 1
0.2%

고용률
Real number (ℝ)

HIGH CORRELATION 

Distinct277
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.550227
Minimum4.6
Maximum83.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-01-10T07:06:04.477593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.6
5-th percentile7.2
Q142.475
median60
Q375.225
95-th percentile80.11
Maximum83.4
Range78.8
Interquartile range (IQR)32.75

Descriptive statistics

Standard deviation22.560754
Coefficient of variation (CV)0.41357763
Kurtosis-0.45908169
Mean54.550227
Median Absolute Deviation (MAD)16.1
Skewness-0.76776368
Sum24002.1
Variance508.98761
MonotonicityNot monotonic
2024-01-10T07:06:04.586909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75.7 7
 
1.6%
78.4 5
 
1.1%
78.3 5
 
1.1%
80.5 4
 
0.9%
76.5 4
 
0.9%
42.6 4
 
0.9%
27.7 4
 
0.9%
6.3 4
 
0.9%
78.8 4
 
0.9%
77.6 4
 
0.9%
Other values (267) 395
89.8%
ValueCountFrequency (%)
4.6 1
 
0.2%
5.2 1
 
0.2%
5.4 1
 
0.2%
5.9 2
0.5%
6.0 1
 
0.2%
6.1 1
 
0.2%
6.3 4
0.9%
6.4 1
 
0.2%
6.7 2
0.5%
6.8 2
0.5%
ValueCountFrequency (%)
83.4 1
0.2%
83.3 1
0.2%
83.0 2
0.5%
82.8 1
0.2%
82.6 1
0.2%
82.3 1
0.2%
82.0 1
0.2%
81.7 1
0.2%
81.5 1
0.2%
81.2 2
0.5%

승인상태(W : 대기
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
S
440 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
S 440
100.0%

Length

2024-01-10T07:06:04.686337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:06:04.762680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
s 440
100.0%

S : 승인)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size4.0 KiB

Interactions

2024-01-10T07:06:02.057343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:05:58.729467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:05:59.222174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:05:59.741669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:00.287376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:01.007604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:01.533966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:02.130635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:05:58.793953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:05:59.290622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:05:59.827802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:00.355132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:01.081309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:01.612450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:02.204391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:05:58.862691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:05:59.364025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:05:59.920926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:00.646330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:01.156010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:01.688518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:02.273414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:05:58.927938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:05:59.428011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:00.000227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:00.713141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:01.230021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:01.755807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:02.346226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:05:58.995891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:05:59.509137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:00.077662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:00.782604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:01.304832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:01.828076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:02.426905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:05:59.071367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:05:59.582859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:00.147253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:00.854831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:01.379977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:01.902055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:02.509393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:05:59.143083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:05:59.656207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:00.218328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:00.933565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:01.453505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:01.978634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:06:04.830417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준분기연령구분시도명15세이상 생산가능인구(천명)경제활동인구(천명)비경제활동인구수(천명)경제활동참가율고용률
기준분기1.0000.0000.0000.0000.0000.0000.0000.000
연령구분0.0001.0000.0000.7940.7860.7810.9630.960
시도명0.0000.0001.0000.9880.6820.9520.1170.000
15세이상 생산가능인구(천명)0.0000.7940.9881.0000.8970.9260.6880.669
경제활동인구(천명)0.0000.7860.6820.8971.0000.8720.6210.619
비경제활동인구수(천명)0.0000.7810.9520.9260.8721.0000.6770.636
경제활동참가율0.0000.9630.1170.6880.6210.6771.0000.985
고용률0.0000.9600.0000.6690.6190.6360.9851.000
2024-01-10T07:06:04.954052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준분기연령구분15세이상 생산가능인구(천명)경제활동인구(천명)비경제활동인구수(천명)경제활동참가율고용률시도명
기준분기1.0000.000-0.018-0.012-0.0190.0130.0400.000
연령구분0.0001.0000.0670.0120.081-0.122-0.1320.000
15세이상 생산가능인구(천명)-0.0180.0671.0000.9270.9100.1050.1150.899
경제활동인구(천명)-0.0120.0120.9271.0000.7470.3930.4030.812
비경제활동인구수(천명)-0.0190.0810.9100.7471.000-0.275-0.2660.804
경제활동참가율0.013-0.1220.1050.393-0.2751.0000.9960.133
고용률0.040-0.1320.1150.403-0.2660.9961.0000.000
시도명0.0000.0000.8990.8120.8040.1330.0001.000

Missing values

2024-01-10T07:06:02.613272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:06:02.733042image/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

기준분기연령구분시도명15세이상 생산가능인구(천명)경제활동인구(천명)비경제활동인구수(천명)경제활동참가율고용률승인상태(W : 대기S : 승인)
0201801044088.427464.016624.462.359.6S<NA>
1201801102817.9255.22562.79.18.0S<NA>
2201801206379.64054.42325.263.657.2S<NA>
3201801307420.55797.81622.778.175.6S<NA>
4201801408483.56849.21634.380.778.7S<NA>
5201801508411.76411.32000.476.274.3S<NA>
62018016010575.24096.16479.138.736.6S<NA>
72018016336819.225346.611472.668.866.0S<NA>
8201801705799.31728.54070.829.826.3S<NA>
9201801759197.54309.64887.946.942.1S<NA>
기준분기연령구분시도명15세이상 생산가능인구(천명)경제활동인구(천명)비경제활동인구수(천명)경제활동참가율고용률승인상태(W : 대기S : 승인)
4302023020충청남도1923.01309.6613.468.166.5S<NA>
43120230210충청남도97.56.291.46.46.4S<NA>
43220230220충청남도254.8170.084.866.761.0S<NA>
43320230230충청남도277.3226.850.681.880.5S<NA>
43420230240충청남도331.9267.764.280.779.2S<NA>
43520230250충청남도344.4277.167.380.579.1S<NA>
43620230260충청남도617.1361.9255.258.658.0S<NA>
43720230263충청남도1484.91076.8408.072.570.5S<NA>
43820230270충청남도204.958.8146.128.726.2S<NA>
43920230275충청남도352.3176.1176.150.045.9S<NA>