Overview

Dataset statistics

Number of variables23
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory209.4 B

Variable types

Text1
Categorical11
Numeric11

Dataset

Description충청남도_논산시_외국인 등록 현황 데이터로 행정동, 성별, 0세부터 100세이상까지의 연령대 정보를 제공하고있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=387&beforeMenuCd=DOM_000000201001001000&publicdatapk=15028835

Alerts

95~99세 has constant value ""Constant
100세이상 has constant value ""Constant
5~9세 is highly imbalanced (64.1%)Imbalance
70~74세 is highly imbalanced (64.6%)Imbalance
75~79세 is highly imbalanced (64.7%)Imbalance
80~84세 is highly imbalanced (64.7%)Imbalance
85~89세 is highly imbalanced (53.1%)Imbalance
90~94세 is highly imbalanced (64.7%)Imbalance
0~4세 has 23 (76.7%) zerosZeros
15~19세 has 7 (23.3%) zerosZeros
35~39세 has 1 (3.3%) zerosZeros
40~44세 has 3 (10.0%) zerosZeros
45~49세 has 3 (10.0%) zerosZeros
50~54세 has 4 (13.3%) zerosZeros
55~59세 has 1 (3.3%) zerosZeros
60~64세 has 3 (10.0%) zerosZeros

Reproduction

Analysis started2024-01-09 21:39:45.791976
Analysis finished2024-01-09 21:39:45.937718
Duration0.15 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동
Text

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-01-10T06:39:46.028252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0666667
Min length3

Characters and Unicode

Total characters92
Distinct characters29
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

Unique0 ?
Unique (%)0.0%

Sample

1st row강경읍
2nd row강경읍
3rd row연무읍
4th row연무읍
5th row성동면
ValueCountFrequency (%)
강경읍 2
 
6.7%
연무읍 2
 
6.7%
성동면 2
 
6.7%
광석면 2
 
6.7%
노성면 2
 
6.7%
상월면 2
 
6.7%
부적면 2
 
6.7%
연산면 2
 
6.7%
벌곡면 2
 
6.7%
양촌면 2
 
6.7%
Other values (5) 10
33.3%
2024-01-10T06:39:46.258895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
면 22
23.9%
동 6
 
6.5%
곡 4
 
4.3%
읍 4
 
4.3%
연 4
 
4.3%
성 4
 
4.3%
부 4
 
4.3%
은 2
 
2.2%
촌 2
 
2.2%
가 2
 
2.2%
Other values (19) 38
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 22
23.9%
동 6
 
6.5%
곡 4
 
4.3%
읍 4
 
4.3%
연 4
 
4.3%
성 4
 
4.3%
부 4
 
4.3%
은 2
 
2.2%
촌 2
 
2.2%
가 2
 
2.2%
Other values (19) 38
41.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 22
23.9%
동 6
 
6.5%
곡 4
 
4.3%
읍 4
 
4.3%
연 4
 
4.3%
성 4
 
4.3%
부 4
 
4.3%
은 2
 
2.2%
촌 2
 
2.2%
가 2
 
2.2%
Other values (19) 38
41.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
면 22
23.9%
동 6
 
6.5%
곡 4
 
4.3%
읍 4
 
4.3%
연 4
 
4.3%
성 4
 
4.3%
부 4
 
4.3%
은 2
 
2.2%
촌 2
 
2.2%
가 2
 
2.2%
Other values (19) 38
41.3%

성별
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
남자
15 
여자
15 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남자
2nd row여자
3rd row남자
4th row여자
5th row남자

Common Values

ValueCountFrequency (%)
남자 15
50.0%
여자 15
50.0%

Length

2024-01-10T06:39:46.361409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:39:46.456448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남자 15
50.0%
여자 15
50.0%

0~4세
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.93333333
Minimum0
Maximum11
Zeros23
Zeros (%)76.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-01-10T06:39:46.530014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6.3
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.5721765
Coefficient of variation (CV)2.7559034
Kurtosis10.753703
Mean0.93333333
Median Absolute Deviation (MAD)0
Skewness3.3355096
Sum28
Variance6.616092
MonotonicityNot monotonic
2024-01-10T06:39:46.610732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 23
76.7%
1 3
 
10.0%
2 1
 
3.3%
9 1
 
3.3%
11 1
 
3.3%
3 1
 
3.3%
ValueCountFrequency (%)
0 23
76.7%
1 3
 
10.0%
2 1
 
3.3%
3 1
 
3.3%
9 1
 
3.3%
11 1
 
3.3%
ValueCountFrequency (%)
11 1
 
3.3%
9 1
 
3.3%
3 1
 
3.3%
2 1
 
3.3%
1 3
 
10.0%
0 23
76.7%

5~9세
Categorical

IMBALANCE 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
26 
1
 
1
7
 
1
3
 
1
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique4 ?
Unique (%)13.3%

Sample

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

Common Values

ValueCountFrequency (%)
0 26
86.7%
1 1
 
3.3%
7 1
 
3.3%
3 1
 
3.3%
2 1
 
3.3%

Length

2024-01-10T06:39:46.704471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:39:46.791210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 26
86.7%
1 1
 
3.3%
7 1
 
3.3%
3 1
 
3.3%
2 1
 
3.3%

10~14세
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
24 
1
3 
2
3 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24
80.0%
1 3
 
10.0%
2 3
 
10.0%

Length

2024-01-10T06:39:46.874703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:39:46.949873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 24
80.0%
1 3
 
10.0%
2 3
 
10.0%

15~19세
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6333333
Minimum0
Maximum12
Zeros7
Zeros (%)23.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-01-10T06:39:47.038712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31.75
95-th percentile5.65
Maximum12
Range12
Interquartile range (IQR)0.75

Descriptive statistics

Standard deviation2.4138013
Coefficient of variation (CV)1.4778375
Kurtosis12.239704
Mean1.6333333
Median Absolute Deviation (MAD)0.5
Skewness3.2846535
Sum49
Variance5.8264368
MonotonicityNot monotonic
2024-01-10T06:39:47.146168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 15
50.0%
0 7
23.3%
2 4
 
13.3%
3 1
 
3.3%
4 1
 
3.3%
7 1
 
3.3%
12 1
 
3.3%
ValueCountFrequency (%)
0 7
23.3%
1 15
50.0%
2 4
 
13.3%
3 1
 
3.3%
4 1
 
3.3%
7 1
 
3.3%
12 1
 
3.3%
ValueCountFrequency (%)
12 1
 
3.3%
7 1
 
3.3%
4 1
 
3.3%
3 1
 
3.3%
2 4
 
13.3%
1 15
50.0%
0 7
23.3%

20~24세
Real number (ℝ)

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.766667
Minimum1
Maximum117
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-01-10T06:39:47.257043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18.25
median19.5
Q355
95-th percentile86.1
Maximum117
Range116
Interquartile range (IQR)46.75

Descriptive statistics

Standard deviation31.784493
Coefficient of variation (CV)1.0005612
Kurtosis0.31010906
Mean31.766667
Median Absolute Deviation (MAD)16
Skewness1.1268127
Sum953
Variance1010.254
MonotonicityNot monotonic
2024-01-10T06:39:47.604943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
2 2
 
6.7%
59 2
 
6.7%
3 2
 
6.7%
6 2
 
6.7%
11 2
 
6.7%
23 1
 
3.3%
85 1
 
3.3%
62 1
 
3.3%
1 1
 
3.3%
78 1
 
3.3%
Other values (15) 15
50.0%
ValueCountFrequency (%)
1 1
3.3%
2 2
6.7%
3 2
6.7%
6 2
6.7%
8 1
3.3%
9 1
3.3%
10 1
3.3%
11 2
6.7%
14 1
3.3%
15 1
3.3%
ValueCountFrequency (%)
117 1
3.3%
87 1
3.3%
85 1
3.3%
79 1
3.3%
78 1
3.3%
62 1
3.3%
59 2
6.7%
43 1
3.3%
37 1
3.3%
35 1
3.3%

25~29세
Real number (ℝ)

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.933333
Minimum1
Maximum101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-01-10T06:39:47.697399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q113.5
median25
Q350.25
95-th percentile83.15
Maximum101
Range100
Interquartile range (IQR)36.75

Descriptive statistics

Standard deviation25.985319
Coefficient of variation (CV)0.78902789
Kurtosis0.46082976
Mean32.933333
Median Absolute Deviation (MAD)17
Skewness0.96181254
Sum988
Variance675.23678
MonotonicityNot monotonic
2024-01-10T06:39:47.790798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
7 2
 
6.7%
42 2
 
6.7%
23 2
 
6.7%
3 1
 
3.3%
20 1
 
3.3%
16 1
 
3.3%
76 1
 
3.3%
48 1
 
3.3%
2 1
 
3.3%
1 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
3 1
3.3%
7 2
6.7%
9 1
3.3%
12 1
3.3%
13 1
3.3%
15 1
3.3%
16 1
3.3%
18 1
3.3%
ValueCountFrequency (%)
101 1
3.3%
89 1
3.3%
76 1
3.3%
60 1
3.3%
57 1
3.3%
54 1
3.3%
52 1
3.3%
51 1
3.3%
48 1
3.3%
42 2
6.7%

30~34세
Real number (ℝ)

Distinct22
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.333333
Minimum3
Maximum78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-01-10T06:39:47.878537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3
Q110
median16.5
Q329.75
95-th percentile57.65
Maximum78
Range75
Interquartile range (IQR)19.75

Descriptive statistics

Standard deviation18.771463
Coefficient of variation (CV)0.84051326
Kurtosis1.5213928
Mean22.333333
Median Absolute Deviation (MAD)12
Skewness1.3163628
Sum670
Variance352.36782
MonotonicityNot monotonic
2024-01-10T06:39:47.975132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
13 3
 
10.0%
3 3
 
10.0%
4 2
 
6.7%
29 2
 
6.7%
10 2
 
6.7%
20 2
 
6.7%
11 1
 
3.3%
5 1
 
3.3%
59 1
 
3.3%
36 1
 
3.3%
Other values (12) 12
40.0%
ValueCountFrequency (%)
3 3
10.0%
4 2
6.7%
5 1
 
3.3%
6 1
 
3.3%
10 2
6.7%
11 1
 
3.3%
13 3
10.0%
14 1
 
3.3%
15 1
 
3.3%
18 1
 
3.3%
ValueCountFrequency (%)
78 1
3.3%
59 1
3.3%
56 1
3.3%
49 1
3.3%
38 1
3.3%
36 1
3.3%
34 1
3.3%
30 1
3.3%
29 2
6.7%
25 1
3.3%

35~39세
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11
Minimum0
Maximum38
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-01-10T06:39:48.067534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13.25
median7.5
Q317
95-th percentile28.2
Maximum38
Range38
Interquartile range (IQR)13.75

Descriptive statistics

Standard deviation9.9099393
Coefficient of variation (CV)0.90090357
Kurtosis0.41556049
Mean11
Median Absolute Deviation (MAD)5.5
Skewness1.0413812
Sum330
Variance98.206897
MonotonicityNot monotonic
2024-01-10T06:39:48.158167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
2 3
 
10.0%
6 3
 
10.0%
1 3
 
10.0%
10 2
 
6.7%
17 2
 
6.7%
21 2
 
6.7%
11 2
 
6.7%
23 2
 
6.7%
4 2
 
6.7%
14 1
 
3.3%
Other values (8) 8
26.7%
ValueCountFrequency (%)
0 1
 
3.3%
1 3
10.0%
2 3
10.0%
3 1
 
3.3%
4 2
6.7%
5 1
 
3.3%
6 3
10.0%
7 1
 
3.3%
8 1
 
3.3%
10 2
6.7%
ValueCountFrequency (%)
38 1
3.3%
30 1
3.3%
26 1
3.3%
23 2
6.7%
21 2
6.7%
17 2
6.7%
14 1
3.3%
11 2
6.7%
10 2
6.7%
8 1
3.3%

40~44세
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.3666667
Minimum0
Maximum20
Zeros3
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-01-10T06:39:48.246240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q38.75
95-th percentile19
Maximum20
Range20
Interquartile range (IQR)6.75

Descriptive statistics

Standard deviation5.7324445
Coefficient of variation (CV)0.90038395
Kurtosis0.55576199
Mean6.3666667
Median Absolute Deviation (MAD)3
Skewness1.137805
Sum191
Variance32.86092
MonotonicityNot monotonic
2024-01-10T06:39:48.335699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
5 4
13.3%
2 4
13.3%
3 3
10.0%
8 3
10.0%
0 3
10.0%
19 2
 
6.7%
4 2
 
6.7%
1 2
 
6.7%
11 1
 
3.3%
10 1
 
3.3%
Other values (5) 5
16.7%
ValueCountFrequency (%)
0 3
10.0%
1 2
6.7%
2 4
13.3%
3 3
10.0%
4 2
6.7%
5 4
13.3%
6 1
 
3.3%
8 3
10.0%
9 1
 
3.3%
10 1
 
3.3%
ValueCountFrequency (%)
20 1
 
3.3%
19 2
6.7%
14 1
 
3.3%
12 1
 
3.3%
11 1
 
3.3%
10 1
 
3.3%
9 1
 
3.3%
8 3
10.0%
6 1
 
3.3%
5 4
13.3%

45~49세
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.2333333
Minimum0
Maximum25
Zeros3
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-01-10T06:39:48.425198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.25
median3.5
Q37
95-th percentile14.2
Maximum25
Range25
Interquartile range (IQR)5.75

Descriptive statistics

Standard deviation5.487813
Coefficient of variation (CV)1.0486267
Kurtosis4.8232708
Mean5.2333333
Median Absolute Deviation (MAD)2.5
Skewness1.9424516
Sum157
Variance30.116092
MonotonicityNot monotonic
2024-01-10T06:39:48.509221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 5
16.7%
2 4
13.3%
4 3
10.0%
7 3
10.0%
3 3
10.0%
0 3
10.0%
9 1
 
3.3%
10 1
 
3.3%
11 1
 
3.3%
6 1
 
3.3%
Other values (5) 5
16.7%
ValueCountFrequency (%)
0 3
10.0%
1 5
16.7%
2 4
13.3%
3 3
10.0%
4 3
10.0%
5 1
 
3.3%
6 1
 
3.3%
7 3
10.0%
8 1
 
3.3%
9 1
 
3.3%
ValueCountFrequency (%)
25 1
 
3.3%
16 1
 
3.3%
12 1
 
3.3%
11 1
 
3.3%
10 1
 
3.3%
9 1
 
3.3%
8 1
 
3.3%
7 3
10.0%
6 1
 
3.3%
5 1
 
3.3%

50~54세
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.6333333
Minimum0
Maximum31
Zeros4
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-01-10T06:39:48.586290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3.5
Q36
95-th percentile22.6
Maximum31
Range31
Interquartile range (IQR)4

Descriptive statistics

Standard deviation7.3319487
Coefficient of variation (CV)1.3015293
Kurtosis6.676595
Mean5.6333333
Median Absolute Deviation (MAD)2
Skewness2.5748696
Sum169
Variance53.757471
MonotonicityNot monotonic
2024-01-10T06:39:48.666531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
4 5
16.7%
2 5
16.7%
0 4
13.3%
3 4
13.3%
9 2
 
6.7%
1 2
 
6.7%
6 2
 
6.7%
8 1
 
3.3%
5 1
 
3.3%
28 1
 
3.3%
Other values (3) 3
10.0%
ValueCountFrequency (%)
0 4
13.3%
1 2
 
6.7%
2 5
16.7%
3 4
13.3%
4 5
16.7%
5 1
 
3.3%
6 2
 
6.7%
7 1
 
3.3%
8 1
 
3.3%
9 2
 
6.7%
ValueCountFrequency (%)
31 1
 
3.3%
28 1
 
3.3%
16 1
 
3.3%
9 2
 
6.7%
8 1
 
3.3%
7 1
 
3.3%
6 2
 
6.7%
5 1
 
3.3%
4 5
16.7%
3 4
13.3%

55~59세
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6333333
Minimum0
Maximum27
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-01-10T06:39:48.751930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11.25
median3
Q35.75
95-th percentile13.3
Maximum27
Range27
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation5.3658135
Coefficient of variation (CV)1.1580892
Kurtosis10.471753
Mean4.6333333
Median Absolute Deviation (MAD)2
Skewness2.9522122
Sum139
Variance28.791954
MonotonicityNot monotonic
2024-01-10T06:39:48.837756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 7
23.3%
4 4
13.3%
2 4
13.3%
3 4
13.3%
6 3
10.0%
5 2
 
6.7%
10 1
 
3.3%
0 1
 
3.3%
7 1
 
3.3%
16 1
 
3.3%
Other values (2) 2
 
6.7%
ValueCountFrequency (%)
0 1
 
3.3%
1 7
23.3%
2 4
13.3%
3 4
13.3%
4 4
13.3%
5 2
 
6.7%
6 3
10.0%
7 1
 
3.3%
8 1
 
3.3%
10 1
 
3.3%
ValueCountFrequency (%)
27 1
 
3.3%
16 1
 
3.3%
10 1
 
3.3%
8 1
 
3.3%
7 1
 
3.3%
6 3
10.0%
5 2
6.7%
4 4
13.3%
3 4
13.3%
2 4
13.3%

60~64세
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7666667
Minimum0
Maximum13
Zeros3
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-01-10T06:39:48.916346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile10.2
Maximum13
Range13
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.1148513
Coefficient of variation (CV)1.1258499
Kurtosis5.3510113
Mean2.7666667
Median Absolute Deviation (MAD)1
Skewness2.3231864
Sum83
Variance9.7022989
MonotonicityNot monotonic
2024-01-10T06:39:49.001208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 9
30.0%
2 8
26.7%
3 4
13.3%
0 3
 
10.0%
4 2
 
6.7%
5 1
 
3.3%
12 1
 
3.3%
13 1
 
3.3%
8 1
 
3.3%
ValueCountFrequency (%)
0 3
 
10.0%
1 9
30.0%
2 8
26.7%
3 4
13.3%
4 2
 
6.7%
5 1
 
3.3%
8 1
 
3.3%
12 1
 
3.3%
13 1
 
3.3%
ValueCountFrequency (%)
13 1
 
3.3%
12 1
 
3.3%
8 1
 
3.3%
5 1
 
3.3%
4 2
 
6.7%
3 4
13.3%
2 8
26.7%
1 9
30.0%
0 3
 
10.0%

65~69세
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
18 
1
8 
2
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row0

Common Values

ValueCountFrequency (%)
0 18
60.0%
1 8
26.7%
2 4
 
13.3%

Length

2024-01-10T06:39:49.090093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:39:49.165213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 18
60.0%
1 8
26.7%
2 4
 
13.3%

70~74세
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
27 
2
 
2
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row2
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 27
90.0%
2 2
 
6.7%
1 1
 
3.3%

Length

2024-01-10T06:39:49.244115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:39:49.315869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 27
90.0%
2 2
 
6.7%
1 1
 
3.3%

75~79세
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
28 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 28
93.3%
1 2
 
6.7%

Length

2024-01-10T06:39:49.396520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:39:49.472890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 28
93.3%
1 2
 
6.7%

80~84세
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
28 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 28
93.3%
1 2
 
6.7%

Length

2024-01-10T06:39:49.573527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:39:49.645893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 28
93.3%
1 2
 
6.7%

85~89세
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
27 
1
3 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 27
90.0%
1 3
 
10.0%

Length

2024-01-10T06:39:49.742714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:39:49.840956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 27
90.0%
1 3
 
10.0%

90~94세
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
28 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 28
93.3%
1 2
 
6.7%

Length

2024-01-10T06:39:49.941869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:39:50.039301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 28
93.3%
1 2
 
6.7%

95~99세
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
30 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 30
100.0%

Length

2024-01-10T06:39:50.138598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:39:50.230105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

100세이상
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
30 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 30
100.0%

Length

2024-01-10T06:39:50.326313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:39:50.406265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

Sample

행정동성별0~4세5~9세10~14세15~19세20~24세25~29세30~34세35~39세40~44세45~49세50~54세55~59세60~64세65~69세70~74세75~79세80~84세85~89세90~94세95~99세100세이상
0강경읍남자0002271123444312010000
1강경읍여자1001222318359910110101000
2연무읍남자0011591017838191096310000000
3연무읍여자200143422910111186420000100
4성동면남자00023539341710742100000000
5성동면여자0001796022145624100000000
6광석면남자0002183425218324100000000
7광석면여자00018131360243300000000
8노성면남자000015271484113000000000
9노성면여자00013121012024000000000
행정동성별0~4세5~9세10~14세15~19세20~24세25~29세30~34세35~39세40~44세45~49세50~54세55~59세60~64세65~69세70~74세75~79세80~84세85~89세90~94세95~99세100세이상
20가야곡면남자10001423301714423000000000
21가야곡면여자010169320115200001000
22은진면남자00048757492112757300000000
23은진면여자001178521343445210000000
24채운면남자000011300201100000000
25채운면여자000232311131200000000
26취암동남자972762483623201628161222001100
27취암동여자11321285765930192531271320110000
28부창동남자3200216546876210000000
29부창동여자102111202011912168800000000