Overview

Dataset statistics

Number of variables13
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory120.3 B

Variable types

Categorical2
Numeric10
Text1

Dataset

Description경기도_인구동향조사출생B형집계기본
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=D9HCCWXPXKOSUZ05W5RO33753745&infSeq=1

Alerts

년도 has constant value ""Constant
생성일자 has constant value ""Constant
시군코드 is highly overall correlated with 출생아수 and 6 other fieldsHigh correlation
출생아수 is highly overall correlated with 시군코드 and 8 other fieldsHigh correlation
결혼출산출생아수 is highly overall correlated with 시군코드 and 8 other fieldsHigh correlation
어머니1519출생아수 is highly overall correlated with 시군코드 and 8 other fieldsHigh correlation
어머니2024출생아수 is highly overall correlated with 출생아수 and 7 other fieldsHigh correlation
어머니2529출생아수 is highly overall correlated with 시군코드 and 8 other fieldsHigh correlation
어머니3034출생아수 is highly overall correlated with 시군코드 and 8 other fieldsHigh correlation
어머니3539출생아수 is highly overall correlated with 시군코드 and 8 other fieldsHigh correlation
어머니4044출생아수 is highly overall correlated with 시군코드 and 8 other fieldsHigh correlation
어머니4549출생아수 is highly overall correlated with 출생아수 and 7 other fieldsHigh correlation
시군코드 has unique valuesUnique
시군명 has unique valuesUnique
출생아수 has unique valuesUnique
결혼출산출생아수 has unique valuesUnique
어머니2529출생아수 has unique valuesUnique
어머니3539출생아수 has unique valuesUnique
어머니4044출생아수 has unique valuesUnique
어머니1519출생아수 has 1 (3.2%) zerosZeros
어머니4549출생아수 has 3 (9.7%) zerosZeros

Reproduction

Analysis started2023-12-10 22:03:46.866353
Analysis finished2023-12-10 22:03:55.779808
Duration8.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
2017
31 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2017 31
100.0%

Length

2023-12-11T07:03:55.836224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:03:55.924880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 31
100.0%

시군코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4142.4194
Minimum4111
Maximum4183
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T07:03:56.009028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4111
5-th percentile4114
Q14126
median4141
Q34158
95-th percentile4181
Maximum4183
Range72
Interquartile range (IQR)32

Descriptive statistics

Standard deviation20.881849
Coefficient of variation (CV)0.005040979
Kurtosis-0.78287209
Mean4142.4194
Median Absolute Deviation (MAD)16
Skewness0.36277728
Sum128415
Variance436.05161
MonotonicityStrictly increasing
2023-12-11T07:03:56.119922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
4111 1
 
3.2%
4113 1
 
3.2%
4183 1
 
3.2%
4182 1
 
3.2%
4180 1
 
3.2%
4167 1
 
3.2%
4165 1
 
3.2%
4163 1
 
3.2%
4161 1
 
3.2%
4159 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
4111 1
3.2%
4113 1
3.2%
4115 1
3.2%
4117 1
3.2%
4119 1
3.2%
4121 1
3.2%
4122 1
3.2%
4125 1
3.2%
4127 1
3.2%
4128 1
3.2%
ValueCountFrequency (%)
4183 1
3.2%
4182 1
3.2%
4180 1
3.2%
4167 1
3.2%
4165 1
3.2%
4163 1
3.2%
4161 1
3.2%
4159 1
3.2%
4157 1
3.2%
4155 1
3.2%

시군명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T07:03:56.326171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0967742
Min length3

Characters and Unicode

Total characters96
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row수원시
2nd row성남시
3rd row의정부시
4th row안양시
5th row부천시
ValueCountFrequency (%)
수원시 1
 
3.2%
의왕시 1
 
3.2%
가평군 1
 
3.2%
연천군 1
 
3.2%
여주시 1
 
3.2%
포천시 1
 
3.2%
양주시 1
 
3.2%
광주시 1
 
3.2%
화성시 1
 
3.2%
김포시 1
 
3.2%
Other values (21) 21
67.7%
2023-12-11T07:03:56.618610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
30.2%
6
 
6.2%
5
 
5.2%
5
 
5.2%
4
 
4.2%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
Other values (28) 32
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 96
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
29
30.2%
6
 
6.2%
5
 
5.2%
5
 
5.2%
4
 
4.2%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
Other values (28) 32
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 96
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
29
30.2%
6
 
6.2%
5
 
5.2%
5
 
5.2%
4
 
4.2%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
Other values (28) 32
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 96
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
29
30.2%
6
 
6.2%
5
 
5.2%
5
 
5.2%
4
 
4.2%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
3
 
3.1%
Other values (28) 32
33.3%

출생아수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2932.2258
Minimum306
Maximum9198
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T07:03:56.736035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum306
5-th percentile343.5
Q11038
median2293
Q34100.5
95-th percentile6949.5
Maximum9198
Range8892
Interquartile range (IQR)3062.5

Descriptive statistics

Standard deviation2388.8179
Coefficient of variation (CV)0.81467733
Kurtosis0.1843508
Mean2932.2258
Median Absolute Deviation (MAD)1470
Skewness0.98857478
Sum90899
Variance5706450.9
MonotonicityNot monotonic
2023-12-11T07:03:56.844401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
9198 1
 
3.2%
7141 1
 
3.2%
592 1
 
3.2%
354 1
 
3.2%
333 1
 
3.2%
606 1
 
3.2%
859 1
 
3.2%
1354 1
 
3.2%
2750 1
 
3.2%
6758 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
306 1
3.2%
333 1
3.2%
354 1
3.2%
558 1
3.2%
592 1
3.2%
606 1
3.2%
859 1
3.2%
905 1
3.2%
1171 1
3.2%
1256 1
3.2%
ValueCountFrequency (%)
9198 1
3.2%
7141 1
3.2%
6758 1
3.2%
6746 1
3.2%
6433 1
3.2%
5866 1
3.2%
4268 1
3.2%
4239 1
3.2%
3962 1
3.2%
3763 1
3.2%

결혼출산출생아수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2885.4194
Minimum305
Maximum9053
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T07:03:56.952605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum305
5-th percentile336.5
Q11020
median2268
Q34024.5
95-th percentile6868.5
Maximum9053
Range8748
Interquartile range (IQR)3004.5

Descriptive statistics

Standard deviation2356.7628
Coefficient of variation (CV)0.81678347
Kurtosis0.18074065
Mean2885.4194
Median Absolute Deviation (MAD)1427
Skewness0.99169232
Sum89448
Variance5554331
MonotonicityNot monotonic
2023-12-11T07:03:57.077863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
9053 1
 
3.2%
7045 1
 
3.2%
576 1
 
3.2%
342 1
 
3.2%
331 1
 
3.2%
591 1
 
3.2%
841 1
 
3.2%
1323 1
 
3.2%
2724 1
 
3.2%
6692 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
305 1
3.2%
331 1
3.2%
342 1
3.2%
542 1
3.2%
576 1
3.2%
591 1
3.2%
841 1
3.2%
890 1
3.2%
1150 1
3.2%
1237 1
3.2%
ValueCountFrequency (%)
9053 1
3.2%
7045 1
3.2%
6692 1
3.2%
6658 1
3.2%
6345 1
3.2%
5785 1
3.2%
4178 1
3.2%
4151 1
3.2%
3898 1
3.2%
3692 1
3.2%

어머니1519출생아수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)58.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9
Minimum0
Maximum24
Zeros1
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T07:03:57.188101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14.5
median7
Q312.5
95-th percentile22
Maximum24
Range24
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.7970582
Coefficient of variation (CV)0.75522869
Kurtosis-0.25943146
Mean9
Median Absolute Deviation (MAD)4
Skewness0.77272789
Sum279
Variance46.2
MonotonicityNot monotonic
2023-12-11T07:03:57.289425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
5 4
12.9%
1 4
12.9%
6 3
 
9.7%
22 2
 
6.5%
15 2
 
6.5%
12 2
 
6.5%
4 2
 
6.5%
9 2
 
6.5%
8 1
 
3.2%
3 1
 
3.2%
Other values (8) 8
25.8%
ValueCountFrequency (%)
0 1
 
3.2%
1 4
12.9%
3 1
 
3.2%
4 2
6.5%
5 4
12.9%
6 3
9.7%
7 1
 
3.2%
8 1
 
3.2%
9 2
6.5%
10 1
 
3.2%
ValueCountFrequency (%)
24 1
3.2%
22 2
6.5%
21 1
3.2%
16 1
3.2%
15 2
6.5%
13 1
3.2%
12 2
6.5%
11 1
3.2%
10 1
3.2%
9 2
6.5%

어머니2024출생아수
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean119.77419
Minimum11
Maximum301
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T07:03:57.387858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile22.5
Q153
median106
Q3172
95-th percentile245
Maximum301
Range290
Interquartile range (IQR)119

Descriptive statistics

Standard deviation79.668358
Coefficient of variation (CV)0.66515462
Kurtosis-0.70256438
Mean119.77419
Median Absolute Deviation (MAD)66
Skewness0.53406159
Sum3713
Variance6347.0473
MonotonicityNot monotonic
2023-12-11T07:03:57.489287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
172 2
 
6.5%
84 2
 
6.5%
301 1
 
3.2%
35 1
 
3.2%
31 1
 
3.2%
26 1
 
3.2%
60 1
 
3.2%
129 1
 
3.2%
233 1
 
3.2%
106 1
 
3.2%
Other values (19) 19
61.3%
ValueCountFrequency (%)
11 1
3.2%
19 1
3.2%
26 1
3.2%
31 1
3.2%
33 1
3.2%
35 1
3.2%
40 1
3.2%
46 1
3.2%
60 1
3.2%
65 1
3.2%
ValueCountFrequency (%)
301 1
3.2%
247 1
3.2%
243 1
3.2%
233 1
3.2%
229 1
3.2%
217 1
3.2%
173 1
3.2%
172 2
6.5%
169 1
3.2%
167 1
3.2%

어머니2529출생아수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean591.70968
Minimum53
Maximum1816
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T07:03:57.628213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum53
5-th percentile99.5
Q1228.5
median507
Q3910.5
95-th percentile1315.5
Maximum1816
Range1763
Interquartile range (IQR)682

Descriptive statistics

Standard deviation452.62679
Coefficient of variation (CV)0.76494742
Kurtosis0.20879345
Mean591.70968
Median Absolute Deviation (MAD)349
Skewness0.9026968
Sum18343
Variance204871.01
MonotonicityNot monotonic
2023-12-11T07:03:57.768054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1816 1
 
3.2%
1196 1
 
3.2%
122 1
 
3.2%
84 1
 
3.2%
115 1
 
3.2%
142 1
 
3.2%
271 1
 
3.2%
333 1
 
3.2%
577 1
 
3.2%
1435 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
53 1
3.2%
84 1
3.2%
115 1
3.2%
122 1
3.2%
142 1
3.2%
153 1
3.2%
158 1
3.2%
207 1
3.2%
250 1
3.2%
271 1
3.2%
ValueCountFrequency (%)
1816 1
3.2%
1435 1
3.2%
1196 1
3.2%
1190 1
3.2%
1125 1
3.2%
1094 1
3.2%
1008 1
3.2%
948 1
3.2%
873 1
3.2%
835 1
3.2%

어머니3034출생아수
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1328.7419
Minimum120
Maximum4454
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T07:03:57.871215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum120
5-th percentile151
Q1472.5
median1099
Q31753
95-th percentile3316.5
Maximum4454
Range4334
Interquartile range (IQR)1280.5

Descriptive statistics

Standard deviation1145.4206
Coefficient of variation (CV)0.86203394
Kurtosis0.55953817
Mean1328.7419
Median Absolute Deviation (MAD)669
Skewness1.1274069
Sum41191
Variance1311988.5
MonotonicityNot monotonic
2023-12-11T07:03:57.969172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
515 2
 
6.5%
3167 2
 
6.5%
4454 1
 
3.2%
3466 1
 
3.2%
230 1
 
3.2%
147 1
 
3.2%
120 1
 
3.2%
232 1
 
3.2%
300 1
 
3.2%
1170 1
 
3.2%
Other values (19) 19
61.3%
ValueCountFrequency (%)
120 1
3.2%
147 1
3.2%
155 1
3.2%
228 1
3.2%
230 1
3.2%
232 1
3.2%
300 1
3.2%
430 1
3.2%
515 2
6.5%
613 1
3.2%
ValueCountFrequency (%)
4454 1
3.2%
3466 1
3.2%
3167 2
6.5%
2924 1
3.2%
2809 1
3.2%
1945 1
3.2%
1789 1
3.2%
1717 1
3.2%
1579 1
3.2%
1397 1
3.2%

어머니3539출생아수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean775.06452
Minimum61
Maximum2356
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T07:03:58.087910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum61
5-th percentile76
Q1250.5
median656
Q31041
95-th percentile2032
Maximum2356
Range2295
Interquartile range (IQR)790.5

Descriptive statistics

Standard deviation657.65239
Coefficient of variation (CV)0.84851309
Kurtosis-0.027373074
Mean775.06452
Median Absolute Deviation (MAD)400
Skewness0.97933667
Sum24027
Variance432506.66
MonotonicityNot monotonic
2023-12-11T07:03:58.187083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
2356 1
 
3.2%
2030 1
 
3.2%
171 1
 
3.2%
75 1
 
3.2%
61 1
 
3.2%
149 1
 
3.2%
174 1
 
3.2%
338 1
 
3.2%
750 1
 
3.2%
1709 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
61 1
3.2%
75 1
3.2%
77 1
3.2%
111 1
3.2%
149 1
3.2%
171 1
3.2%
174 1
3.2%
245 1
3.2%
256 1
3.2%
338 1
3.2%
ValueCountFrequency (%)
2356 1
3.2%
2034 1
3.2%
2030 1
3.2%
1811 1
3.2%
1709 1
3.2%
1504 1
3.2%
1311 1
3.2%
1052 1
3.2%
1030 1
3.2%
892 1
3.2%

어머니4044출생아수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean103.58065
Minimum9
Maximum270
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T07:03:58.293786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile12
Q136.5
median90
Q3141.5
95-th percentile254.5
Maximum270
Range261
Interquartile range (IQR)105

Descriptive statistics

Standard deviation80.830182
Coefficient of variation (CV)0.7803599
Kurtosis-0.56586616
Mean103.58065
Median Absolute Deviation (MAD)54
Skewness0.73573341
Sum3211
Variance6533.5183
MonotonicityNot monotonic
2023-12-11T07:03:58.415783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
240 1
 
3.2%
249 1
 
3.2%
31 1
 
3.2%
14 1
 
3.2%
9 1
 
3.2%
17 1
 
3.2%
23 1
 
3.2%
76 1
 
3.2%
109 1
 
3.2%
192 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
9 1
3.2%
10 1
3.2%
14 1
3.2%
17 1
3.2%
18 1
3.2%
23 1
3.2%
31 1
3.2%
33 1
3.2%
40 1
3.2%
41 1
3.2%
ValueCountFrequency (%)
270 1
3.2%
260 1
3.2%
249 1
3.2%
240 1
3.2%
215 1
3.2%
192 1
3.2%
181 1
3.2%
144 1
3.2%
139 1
3.2%
128 1
3.2%

어머니4549출생아수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)25.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0645161
Minimum0
Maximum8
Zeros3
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T07:03:58.526448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q35
95-th percentile7.5
Maximum8
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.4891161
Coefficient of variation (CV)0.81223788
Kurtosis-0.74904006
Mean3.0645161
Median Absolute Deviation (MAD)1
Skewness0.72553716
Sum95
Variance6.1956989
MonotonicityNot monotonic
2023-12-11T07:03:58.626989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 9
29.0%
1 7
22.6%
4 3
 
9.7%
7 3
 
9.7%
5 3
 
9.7%
0 3
 
9.7%
8 2
 
6.5%
6 1
 
3.2%
ValueCountFrequency (%)
0 3
 
9.7%
1 7
22.6%
2 9
29.0%
4 3
 
9.7%
5 3
 
9.7%
6 1
 
3.2%
7 3
 
9.7%
8 2
 
6.5%
ValueCountFrequency (%)
8 2
 
6.5%
7 3
 
9.7%
6 1
 
3.2%
5 3
 
9.7%
4 3
 
9.7%
2 9
29.0%
1 7
22.6%
0 3
 
9.7%

생성일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
20181122
31 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20181122
2nd row20181122
3rd row20181122
4th row20181122
5th row20181122

Common Values

ValueCountFrequency (%)
20181122 31
100.0%

Length

2023-12-11T07:03:58.755459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:03:58.835504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20181122 31
100.0%

Interactions

2023-12-11T07:03:54.494423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:47.159015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:48.124694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:48.945868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:49.651333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:50.345388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:51.345013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:52.106264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:52.874113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:53.685496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:54.575010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:47.251487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:48.240677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:49.025902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:49.728268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:50.425524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:51.419885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:52.185124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:52.953779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:53.832645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:54.646002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:47.329241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:48.326216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:49.089798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:49.794324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:50.503533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:51.492805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:52.251693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:53.018698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:53.905883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:54.723217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:47.439983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:48.396638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:49.153940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:49.857289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:50.571246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:51.560589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:52.340371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:53.098308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:53.976746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:54.822240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:47.543983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:48.469023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:49.221797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:49.922230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:50.876667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:51.640152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:52.420784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:53.177050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:54.050286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:54.906202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:47.651639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:48.573177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:49.291800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:49.999503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:50.942368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:51.714692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:52.504688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:53.259840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:54.123700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:54.985911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:47.763634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:48.659102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:49.373749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:50.069944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:51.023908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:51.796383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:52.579475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:53.339386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:54.203495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:55.066308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:47.846595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:48.723739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:49.437779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:50.135854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:51.091059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:51.869040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:52.645072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:53.415292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:54.275306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:55.133184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:47.930552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:48.792369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:49.504232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:50.197283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:51.167771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:51.944263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:52.713312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:53.499408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:54.343999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:55.207562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:48.029685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:48.860607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:49.575043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:50.264332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:51.256784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:52.023076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:52.781581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:53.573345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:54.416518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:03:58.901348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군코드시군명출생아수결혼출산출생아수어머니1519출생아수어머니2024출생아수어머니2529출생아수어머니3034출생아수어머니3539출생아수어머니4044출생아수어머니4549출생아수
시군코드1.0001.0000.0000.0000.5450.5330.3540.0000.2810.2410.000
시군명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
출생아수0.0001.0001.0001.0000.5650.7460.8270.9920.9600.9250.768
결혼출산출생아수0.0001.0001.0001.0000.5650.7460.8270.9920.9600.9250.768
어머니1519출생아수0.5451.0000.5650.5651.0000.9240.8830.6340.6430.6580.418
어머니2024출생아수0.5331.0000.7460.7460.9241.0000.9140.7680.7270.7300.722
어머니2529출생아수0.3541.0000.8270.8270.8830.9141.0000.8940.8380.8770.541
어머니3034출생아수0.0001.0000.9920.9920.6340.7680.8941.0000.9200.9230.731
어머니3539출생아수0.2811.0000.9600.9600.6430.7270.8380.9201.0000.9780.587
어머니4044출생아수0.2411.0000.9250.9250.6580.7300.8770.9230.9781.0000.452
어머니4549출생아수0.0001.0000.7680.7680.4180.7220.5410.7310.5870.4521.000
2023-12-11T07:03:59.027528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군코드출생아수결혼출산출생아수어머니1519출생아수어머니2024출생아수어머니2529출생아수어머니3034출생아수어머니3539출생아수어머니4044출생아수어머니4549출생아수
시군코드1.000-0.521-0.521-0.592-0.442-0.502-0.551-0.548-0.515-0.406
출생아수-0.5211.0001.0000.8210.8940.9770.9950.9910.9830.783
결혼출산출생아수-0.5211.0001.0000.8210.8940.9770.9950.9910.9830.783
어머니1519출생아수-0.5920.8210.8211.0000.9110.8800.7980.7800.7840.641
어머니2024출생아수-0.4420.8940.8940.9111.0000.9490.8720.8500.8550.752
어머니2529출생아수-0.5020.9770.9770.8800.9491.0000.9660.9520.9480.779
어머니3034출생아수-0.5510.9950.9950.7980.8720.9661.0000.9920.9800.782
어머니3539출생아수-0.5480.9910.9910.7800.8500.9520.9921.0000.9880.782
어머니4044출생아수-0.5150.9830.9830.7840.8550.9480.9800.9881.0000.787
어머니4549출생아수-0.4060.7830.7830.6410.7520.7790.7820.7820.7871.000

Missing values

2023-12-11T07:03:55.544233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:03:55.712463image/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

년도시군코드시군명출생아수결혼출산출생아수어머니1519출생아수어머니2024출생아수어머니2529출생아수어머니3034출생아수어머니3539출생아수어머니4044출생아수어머니4549출생아수생성일자
020174111수원시9198905322301181644542356240820181122
120174113성남시7141704524172119634662030249420181122
220174115의정부시2579249415139549109967795420181122
320174117안양시396238981211169519451052144220181122
420174119부천시5866578511229112528091504181720181122
520174121광명시22932268565347112765890120181122
620174122평택시37633692212479481579835128520181122
720174125동두천시55854264015322811118220181122
820174127안산시4239415122243100817891030139720181122
920174128고양시6433634513217119029241811270720181122
년도시군코드시군명출생아수결혼출산출생아수어머니1519출생아수어머니2024출생아수어머니2529출생아수어머니3034출생아수어머니3539출생아수어머니4044출생아수어머니4549출생아수생성일자
2120174155안성시1171115067529251524533120181122
2220174157김포시3048301341065271397892120220181122
2320174159화성시6758669210233143531671709192520181122
2420174161광주시2750272471295771170750109620181122
2520174163양주시1354132358433351533876220181122
2620174165포천시85984168427130017423120181122
2720174167여주시60659146014223214917220181122
2820174180연천군333331126115120619120181122
2920174182가평군354342331841477514020181122
3020174183양평군59257613512223017131120181122