Overview

Dataset statistics

Number of variables53
Number of observations100
Missing cells3
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory45.1 KiB
Average record size in memory462.3 B

Variable types

Text8
Categorical13
Numeric32

Alerts

lclas has constant value ""Constant
mlsfc has constant value ""Constant
update_date has constant value ""Constant
data_ref has constant value ""Constant
file_name has constant value ""Constant
base_ymd has constant value ""Constant
ctprvn_nm is highly imbalanced (80.6%)Imbalance
pub_priv is highly imbalanced (80.6%)Imbalance
cmptemp_ntotal is highly imbalanced (63.5%)Imbalance
cmptemp_total is highly imbalanced (67.1%)Imbalance
hmpg has 3 (3.0%) missing valuesMissing
id has unique valuesUnique
fclt_name has unique valuesUnique
cttpc has unique valuesUnique
psgud_book has unique valuesUnique
wrkbdg_total has unique valuesUnique
wrkbdg_etc has unique valuesUnique
usemem_total has unique valuesUnique
usebook_total has unique valuesUnique
psgud_nobook has 23 (23.0%) zerosZeros
psgud_paper has 3 (3.0%) zerosZeros
psgud_addnobook has 35 (35.0%) zerosZeros
psgud_addpaper has 31 (31.0%) zerosZeros
admemp_ntotal has 41 (41.0%) zerosZeros
admemp_total has 41 (41.0%) zerosZeros
lbrrnemp_total has 2 (2.0%) zerosZeros
etcemp_ntotal has 40 (40.0%) zerosZeros
etcemp_total has 41 (41.0%) zerosZeros
crqfc_3st has 39 (39.0%) zerosZeros

Reproduction

Analysis started2023-12-10 09:54:13.316395
Analysis finished2023-12-10 09:54:15.022733
Duration1.71 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

id
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:54:15.251549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1900
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowKCDMIBL21N000000001
2nd rowKCDMIBL21N000001132
3rd rowKCDMIBL21N000000003
4th rowKCDMIBL21N000000004
5th rowKCDMIBL21N000000005
ValueCountFrequency (%)
kcdmibl21n000000001 1
 
1.0%
kcdmibl21n000000063 1
 
1.0%
kcdmibl21n000000074 1
 
1.0%
kcdmibl21n000000073 1
 
1.0%
kcdmibl21n000000072 1
 
1.0%
kcdmibl21n000000071 1
 
1.0%
kcdmibl21n000000070 1
 
1.0%
kcdmibl21n000000069 1
 
1.0%
kcdmibl21n000000068 1
 
1.0%
kcdmibl21n000000067 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:54:15.891018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 711
37.4%
1 127
 
6.7%
2 119
 
6.3%
K 100
 
5.3%
L 100
 
5.3%
C 100
 
5.3%
N 100
 
5.3%
B 100
 
5.3%
I 100
 
5.3%
M 100
 
5.3%
Other values (8) 243
 
12.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1100
57.9%
Uppercase Letter 800
42.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 711
64.6%
1 127
 
11.5%
2 119
 
10.8%
3 23
 
2.1%
4 21
 
1.9%
5 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
9 20
 
1.8%
8 19
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
K 100
12.5%
L 100
12.5%
C 100
12.5%
N 100
12.5%
B 100
12.5%
I 100
12.5%
M 100
12.5%
D 100
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1100
57.9%
Latin 800
42.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 711
64.6%
1 127
 
11.5%
2 119
 
10.8%
3 23
 
2.1%
4 21
 
1.9%
5 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
9 20
 
1.8%
8 19
 
1.7%
Latin
ValueCountFrequency (%)
K 100
12.5%
L 100
12.5%
C 100
12.5%
N 100
12.5%
B 100
12.5%
I 100
12.5%
M 100
12.5%
D 100
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 711
37.4%
1 127
 
6.7%
2 119
 
6.3%
K 100
 
5.3%
L 100
 
5.3%
C 100
 
5.3%
N 100
 
5.3%
B 100
 
5.3%
I 100
 
5.3%
M 100
 
5.3%
Other values (8) 243
 
12.8%

lclas
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
문화시설 100
100.0%

Length

2023-12-10T18:54:16.156828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:54:16.385680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화시설 100
100.0%

mlsfc
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공도서관 100
100.0%

Length

2023-12-10T18:54:16.619167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:54:16.783587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공도서관 100
100.0%

fclt_name
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:54:17.166095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length9.46
Min length5

Characters and Unicode

Total characters946
Distinct characters168
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row서울특별시교육청강남도서관
2nd row김해지혜의바다
3rd row서울특별시교육청강동도서관
4th row서울특별시교육청고덕평생학습관
5th row서울특별시교육청강서도서관
ValueCountFrequency (%)
도서관 5
 
4.3%
서울특별시교육청마포평생학습관 2
 
1.7%
강서구립 2
 
1.7%
동작어린이도서관 1
 
0.9%
하늘도서관 1
 
0.9%
글마루한옥어린이도서관 1
 
0.9%
궁동어린이도서관 1
 
0.9%
구로꿈나무도서관 1
 
0.9%
온누리도서관 1
 
0.9%
구로구립 1
 
0.9%
Other values (99) 99
86.1%
2023-12-10T18:54:18.094520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
125
 
13.2%
99
 
10.5%
99
 
10.5%
23
 
2.4%
23
 
2.4%
21
 
2.2%
21
 
2.2%
21
 
2.2%
21
 
2.2%
20
 
2.1%
Other values (158) 473
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 925
97.8%
Space Separator 15
 
1.6%
Decimal Number 5
 
0.5%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
125
 
13.5%
99
 
10.7%
99
 
10.7%
23
 
2.5%
23
 
2.5%
21
 
2.3%
21
 
2.3%
21
 
2.3%
21
 
2.3%
20
 
2.2%
Other values (152) 452
48.9%
Decimal Number
ValueCountFrequency (%)
4 2
40.0%
3 1
20.0%
1 1
20.0%
9 1
20.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 925
97.8%
Common 21
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
125
 
13.5%
99
 
10.7%
99
 
10.7%
23
 
2.5%
23
 
2.5%
21
 
2.3%
21
 
2.3%
21
 
2.3%
21
 
2.3%
20
 
2.2%
Other values (152) 452
48.9%
Common
ValueCountFrequency (%)
15
71.4%
4 2
 
9.5%
3 1
 
4.8%
. 1
 
4.8%
1 1
 
4.8%
9 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 925
97.8%
ASCII 21
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
125
 
13.5%
99
 
10.7%
99
 
10.7%
23
 
2.5%
23
 
2.5%
21
 
2.3%
21
 
2.3%
21
 
2.3%
21
 
2.3%
20
 
2.2%
Other values (152) 452
48.9%
ASCII
ValueCountFrequency (%)
15
71.4%
4 2
 
9.5%
3 1
 
4.8%
. 1
 
4.8%
1 1
 
4.8%
9 1
 
4.8%

ctprvn_nm
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
97 
경상남도
 
3

Length

Max length5
Median length5
Mean length4.97
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시
2nd row경상남도
3rd row서울특별시
4th row서울특별시
5th row서울특별시

Common Values

ValueCountFrequency (%)
서울특별시 97
97.0%
경상남도 3
 
3.0%

Length

2023-12-10T18:54:18.387885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:54:18.639444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 97
97.0%
경상남도 3
 
3.0%

sgnr_nm
Categorical

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
강남구
11 
노원구
10 
구로구
10 
강서구
강동구
Other values (17)
52 

Length

Max length4
Median length3
Mean length3.05
Min length2

Unique

Unique5 ?
Unique (%)5.0%

Sample

1st row강남구
2nd row김해시
3rd row강동구
4th row강동구
5th row강서구

Common Values

ValueCountFrequency (%)
강남구 11
11.0%
노원구 10
 
10.0%
구로구 10
 
10.0%
강서구 9
 
9.0%
강동구 8
 
8.0%
강북구 7
 
7.0%
도봉구 6
 
6.0%
동작구 5
 
5.0%
동대문구 4
 
4.0%
관악구 4
 
4.0%
Other values (12) 26
26.0%

Length

2023-12-10T18:54:19.002650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강남구 11
11.0%
구로구 10
 
10.0%
노원구 10
 
10.0%
강서구 9
 
9.0%
강동구 8
 
8.0%
강북구 7
 
7.0%
도봉구 6
 
6.0%
동작구 5
 
5.0%
광진구 4
 
4.0%
종로구 4
 
4.0%
Other values (12) 26
26.0%

legaldong_cd
Real number (ℝ)

Distinct65
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2736959 × 109
Minimum1.1110115 × 109
Maximum4.825032 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:19.331796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110115 × 109
5-th percentile1.1168603 × 109
Q11.1320107 × 109
median1.1500106 × 109
Q31.1635102 × 109
95-th percentile1.1740109 × 109
Maximum4.825032 × 109
Range3.7140205 × 109
Interquartile range (IQR)31499500

Descriptive statistics

Standard deviation6.4910082 × 108
Coefficient of variation (CV)0.50961995
Kurtosis25.93533
Mean1.2736959 × 109
Median Absolute Deviation (MAD)17999800
Skewness5.1743422
Sum1.2736959 × 1011
Variance4.2133188 × 1017
MonotonicityNot monotonic
2023-12-10T18:54:19.683140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1150010300 5
 
5.0%
1130510100 5
 
5.0%
1153010200 5
 
5.0%
1162010100 3
 
3.0%
1153010700 3
 
3.0%
1168010600 3
 
3.0%
1135010600 3
 
3.0%
1135010200 3
 
3.0%
1117010100 2
 
2.0%
1174010900 2
 
2.0%
Other values (55) 66
66.0%
ValueCountFrequency (%)
1111011500 2
2.0%
1111014300 1
1.0%
1111017700 1
1.0%
1114013600 1
1.0%
1117010100 2
2.0%
1121510100 1
1.0%
1121510300 1
1.0%
1121510400 1
1.0%
1121510500 1
1.0%
1123010100 1
1.0%
ValueCountFrequency (%)
4825032025 1
1.0%
4817012700 1
1.0%
4817011900 1
1.0%
2826010700 1
1.0%
1174011000 1
1.0%
1174010900 2
2.0%
1174010800 1
1.0%
1174010700 1
1.0%
1174010500 1
1.0%
1174010200 1
1.0%
Distinct65
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:54:20.212236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.01
Min length2

Characters and Unicode

Total characters301
Distinct characters87
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)44.0%

Sample

1st row삼성동
2nd row주촌면 내삼리
3rd row길동
4th row고덕동
5th row등촌동
ValueCountFrequency (%)
화곡동 5
 
5.0%
미아동 5
 
5.0%
구로동 5
 
5.0%
월계동 3
 
3.0%
개봉동 3
 
3.0%
대치동 3
 
3.0%
중계동 3
 
3.0%
봉천동 3
 
3.0%
공릉동 2
 
2.0%
사직동 2
 
2.0%
Other values (56) 67
66.3%
2023-12-10T18:54:21.010300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
99
32.9%
9
 
3.0%
8
 
2.7%
7
 
2.3%
7
 
2.3%
7
 
2.3%
6
 
2.0%
5
 
1.7%
5
 
1.7%
5
 
1.7%
Other values (77) 143
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 299
99.3%
Decimal Number 1
 
0.3%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
99
33.1%
9
 
3.0%
8
 
2.7%
7
 
2.3%
7
 
2.3%
7
 
2.3%
6
 
2.0%
5
 
1.7%
5
 
1.7%
5
 
1.7%
Other values (75) 141
47.2%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 299
99.3%
Common 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
99
33.1%
9
 
3.0%
8
 
2.7%
7
 
2.3%
7
 
2.3%
7
 
2.3%
6
 
2.0%
5
 
1.7%
5
 
1.7%
5
 
1.7%
Other values (75) 141
47.2%
Common
ValueCountFrequency (%)
1 1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 299
99.3%
ASCII 2
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
99
33.1%
9
 
3.0%
8
 
2.7%
7
 
2.3%
7
 
2.3%
7
 
2.3%
6
 
2.0%
5
 
1.7%
5
 
1.7%
5
 
1.7%
Other values (75) 141
47.2%
ASCII
ValueCountFrequency (%)
1 1
50.0%
1
50.0%

adstrd_cd
Real number (ℝ)

Distinct89
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2737455 × 109
Minimum1.111053 × 109
Maximum4.825032 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:21.337269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111053 × 109
5-th percentile1.1169014 × 109
Q11.1320626 × 109
median1.1500628 × 109
Q31.1635676 × 109
95-th percentile1.1740661 × 109
Maximum4.825032 × 109
Range3.713979 × 109
Interquartile range (IQR)31505100

Descriptive statistics

Standard deviation6.4909867 × 108
Coefficient of variation (CV)0.5095984
Kurtosis25.935337
Mean1.2737455 × 109
Median Absolute Deviation (MAD)17994950
Skewness5.1743429
Sum1.2737455 × 1011
Variance4.2132909 × 1017
MonotonicityNot monotonic
2023-12-10T18:54:21.652398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1168064000 2
 
2.0%
1132066000 2
 
2.0%
1168070000 2
 
2.0%
1111053000 2
 
2.0%
1117051000 2
 
2.0%
1153053000 2
 
2.0%
1144056500 2
 
2.0%
1159052000 2
 
2.0%
1153074000 2
 
2.0%
1168061000 2
 
2.0%
Other values (79) 80
80.0%
ValueCountFrequency (%)
1111053000 2
2.0%
1111054000 1
1.0%
1111058000 1
1.0%
1114058000 1
1.0%
1117051000 2
2.0%
1121576000 1
1.0%
1121581000 1
1.0%
1121584700 1
1.0%
1121587000 1
1.0%
1123053600 1
1.0%
ValueCountFrequency (%)
4825032000 1
1.0%
4817072000 1
1.0%
4817067300 1
1.0%
2826053000 1
1.0%
1174068500 1
1.0%
1174066000 1
1.0%
1174062000 1
1.0%
1174061000 1
1.0%
1174057000 1
1.0%
1174056000 1
1.0%
Distinct89
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:54:22.385401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.66
Min length2

Characters and Unicode

Total characters366
Distinct characters102
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)78.0%

Sample

1st row삼성2동
2nd row주촌면
3rd row길동
4th row고덕2동
5th row등촌2동
ValueCountFrequency (%)
역삼1동 2
 
2.0%
노량진2동 2
 
2.0%
사직동 2
 
2.0%
세곡동 2
 
2.0%
구로2동 2
 
2.0%
후암동 2
 
2.0%
개봉1동 2
 
2.0%
공덕동 2
 
2.0%
우장산동 2
 
2.0%
쌍문1동 2
 
2.0%
Other values (79) 80
80.0%
2023-12-10T18:54:23.268089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
99
27.0%
2 20
 
5.5%
1 18
 
4.9%
3 12
 
3.3%
8
 
2.2%
4 7
 
1.9%
6
 
1.6%
6
 
1.6%
6
 
1.6%
6
 
1.6%
Other values (92) 178
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 303
82.8%
Decimal Number 62
 
16.9%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
99
32.7%
8
 
2.6%
6
 
2.0%
6
 
2.0%
6
 
2.0%
6
 
2.0%
5
 
1.7%
5
 
1.7%
5
 
1.7%
5
 
1.7%
Other values (84) 152
50.2%
Decimal Number
ValueCountFrequency (%)
2 20
32.3%
1 18
29.0%
3 12
19.4%
4 7
 
11.3%
5 3
 
4.8%
0 1
 
1.6%
8 1
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 303
82.8%
Common 63
 
17.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
99
32.7%
8
 
2.6%
6
 
2.0%
6
 
2.0%
6
 
2.0%
6
 
2.0%
5
 
1.7%
5
 
1.7%
5
 
1.7%
5
 
1.7%
Other values (84) 152
50.2%
Common
ValueCountFrequency (%)
2 20
31.7%
1 18
28.6%
3 12
19.0%
4 7
 
11.1%
5 3
 
4.8%
0 1
 
1.6%
8 1
 
1.6%
. 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 303
82.8%
ASCII 63
 
17.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
99
32.7%
8
 
2.6%
6
 
2.0%
6
 
2.0%
6
 
2.0%
6
 
2.0%
5
 
1.7%
5
 
1.7%
5
 
1.7%
5
 
1.7%
Other values (84) 152
50.2%
ASCII
ValueCountFrequency (%)
2 20
31.7%
1 18
28.6%
3 12
19.0%
4 7
 
11.1%
5 3
 
4.8%
0 1
 
1.6%
8 1
 
1.6%
. 1
 
1.6%

rdnmaddr_cd
Real number (ℝ)

Distinct94
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3415204 × 1011
Minimum1.1110301 × 1011
Maximum4.82505 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:23.570919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110301 × 1011
5-th percentile1.1168815 × 1011
Q11.1320387 × 1011
median1.15303 × 1011
Q31.1680312 × 1011
95-th percentile2.8357421 × 1011
Maximum4.82505 × 1011
Range3.7140199 × 1011
Interquartile range (IQR)3.5992495 × 109

Descriptive statistics

Standard deviation7.5384972 × 1010
Coefficient of variation (CV)0.56193682
Kurtosis14.90072
Mean1.3415204 × 1011
Median Absolute Deviation (MAD)1.799445 × 109
Skewness3.962069
Sum1.3415204 × 1013
Variance5.6828939 × 1021
MonotonicityNot monotonic
2023-12-10T18:54:23.899351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
115003115001 2
 
2.0%
115304148151 2
 
2.0%
111104100137 2
 
2.0%
113503107018 2
 
2.0%
117403124007 2
 
2.0%
116803122014 2
 
2.0%
116203120001 1
 
1.0%
115454151003 1
 
1.0%
115304148200 1
 
1.0%
115304148331 1
 
1.0%
Other values (84) 84
84.0%
ValueCountFrequency (%)
111103005004 1
1.0%
111104100112 1
1.0%
111104100137 2
2.0%
111404103105 1
1.0%
111703101018 1
1.0%
111703102002 1
1.0%
112153000002 1
1.0%
112153104001 1
1.0%
112153104007 1
1.0%
112154112246 1
1.0%
ValueCountFrequency (%)
482505000000 1
1.0%
481705000000 1
1.0%
481703000000 1
1.0%
437504535432 1
1.0%
302003167042 1
1.0%
282604268377 1
1.0%
282004259715 1
1.0%
117404172235 1
1.0%
117404172211 1
1.0%
117404172138 1
1.0%
Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:54:24.647709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length18.77
Min length16

Characters and Unicode

Total characters1877
Distinct characters147
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st row서울특별시 강남구 선릉로116길 45
2nd row경상남도 김해시 주촌면 서부로1541번길 8
3rd row서울특별시 강동구 양재대로116길 57
4th row서울특별시 강동구 고덕로 295
5th row서울특별시 강서구 등촌로51나길 29
ValueCountFrequency (%)
서울특별시 96
23.9%
노원구 10
 
2.5%
강남구 10
 
2.5%
구로구 10
 
2.5%
강서구 9
 
2.2%
강동구 8
 
2.0%
강북구 7
 
1.7%
도봉구 6
 
1.5%
동작구 5
 
1.2%
종로구 4
 
1.0%
Other values (193) 236
58.9%
2023-12-10T18:54:25.631598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
301
16.0%
115
 
6.1%
114
 
6.1%
111
 
5.9%
104
 
5.5%
97
 
5.2%
96
 
5.1%
96
 
5.1%
1 66
 
3.5%
63
 
3.4%
Other values (137) 714
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1222
65.1%
Decimal Number 348
 
18.5%
Space Separator 301
 
16.0%
Dash Punctuation 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
115
 
9.4%
114
 
9.3%
111
 
9.1%
104
 
8.5%
97
 
7.9%
96
 
7.9%
96
 
7.9%
63
 
5.2%
38
 
3.1%
28
 
2.3%
Other values (125) 360
29.5%
Decimal Number
ValueCountFrequency (%)
1 66
19.0%
2 41
11.8%
4 39
11.2%
3 39
11.2%
5 37
10.6%
7 33
9.5%
6 32
9.2%
9 23
 
6.6%
0 20
 
5.7%
8 18
 
5.2%
Space Separator
ValueCountFrequency (%)
301
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1222
65.1%
Common 655
34.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
115
 
9.4%
114
 
9.3%
111
 
9.1%
104
 
8.5%
97
 
7.9%
96
 
7.9%
96
 
7.9%
63
 
5.2%
38
 
3.1%
28
 
2.3%
Other values (125) 360
29.5%
Common
ValueCountFrequency (%)
301
46.0%
1 66
 
10.1%
2 41
 
6.3%
4 39
 
6.0%
3 39
 
6.0%
5 37
 
5.6%
7 33
 
5.0%
6 32
 
4.9%
9 23
 
3.5%
0 20
 
3.1%
Other values (2) 24
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1222
65.1%
ASCII 655
34.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
301
46.0%
1 66
 
10.1%
2 41
 
6.3%
4 39
 
6.0%
3 39
 
6.0%
5 37
 
5.6%
7 33
 
5.0%
6 32
 
4.9%
9 23
 
3.5%
0 20
 
3.1%
Other values (2) 24
 
3.7%
Hangul
ValueCountFrequency (%)
115
 
9.4%
114
 
9.3%
111
 
9.1%
104
 
8.5%
97
 
7.9%
96
 
7.9%
96
 
7.9%
63
 
5.2%
38
 
3.1%
28
 
2.3%
Other values (125) 360
29.5%

zip_cd
Real number (ℝ)

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6736.93
Minimum1103
Maximum52786
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:25.998416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1103
5-th percentile1186
Q12563.75
median5619.5
Q37716.75
95-th percentile8750.8
Maximum52786
Range51683
Interquartile range (IQR)5153

Descriptive statistics

Standard deviation8604.6481
Coefficient of variation (CV)1.2772358
Kurtosis22.02294
Mean6736.93
Median Absolute Deviation (MAD)2592.5
Skewness4.5420485
Sum673693
Variance74039969
MonotonicityNot monotonic
2023-12-10T18:54:26.285557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7690 2
 
2.0%
3027 2
 
2.0%
4202 2
 
2.0%
8333 1
 
1.0%
8611 1
 
1.0%
8521 1
 
1.0%
8317 1
 
1.0%
8372 1
 
1.0%
8243 1
 
1.0%
8249 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
1103 1
1.0%
1133 1
1.0%
1151 1
1.0%
1165 1
1.0%
1167 1
1.0%
1187 1
1.0%
1199 1
1.0%
1320 1
1.0%
1359 1
1.0%
1368 1
1.0%
ValueCountFrequency (%)
52786 1
1.0%
52669 1
1.0%
50877 1
1.0%
22714 1
1.0%
8766 1
1.0%
8750 1
1.0%
8734 1
1.0%
8726 1
1.0%
8645 1
1.0%
8611 1
1.0%
Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:54:26.813096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters800
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)96.0%

Sample

1st row다사599461
2nd row마라202942
3rd row다사685488
4th row다사697508
5th row다사434500
ValueCountFrequency (%)
다사419516 2
 
2.0%
다사520506 2
 
2.0%
다사626621 1
 
1.0%
다사432435 1
 
1.0%
다사616483 1
 
1.0%
다사462417 1
 
1.0%
다사453433 1
 
1.0%
다사460432 1
 
1.0%
다사421454 1
 
1.0%
다사407449 1
 
1.0%
Other values (88) 88
88.0%
2023-12-10T18:54:27.591271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 120
15.0%
5 102
12.8%
97
12.1%
97
12.1%
6 84
10.5%
0 49
6.1%
2 48
 
6.0%
8 43
 
5.4%
1 40
 
5.0%
7 40
 
5.0%
Other values (4) 80
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 600
75.0%
Other Letter 200
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 120
20.0%
5 102
17.0%
6 84
14.0%
0 49
8.2%
2 48
 
8.0%
8 43
 
7.2%
1 40
 
6.7%
7 40
 
6.7%
3 39
 
6.5%
9 35
 
5.8%
Other Letter
ValueCountFrequency (%)
97
48.5%
97
48.5%
5
 
2.5%
1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 600
75.0%
Hangul 200
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 120
20.0%
5 102
17.0%
6 84
14.0%
0 49
8.2%
2 48
 
8.0%
8 43
 
7.2%
1 40
 
6.7%
7 40
 
6.7%
3 39
 
6.5%
9 35
 
5.8%
Hangul
ValueCountFrequency (%)
97
48.5%
97
48.5%
5
 
2.5%
1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 600
75.0%
Hangul 200
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 120
20.0%
5 102
17.0%
6 84
14.0%
0 49
8.2%
2 48
 
8.0%
8 43
 
7.2%
1 40
 
6.7%
7 40
 
6.7%
3 39
 
6.5%
9 35
 
5.8%
Hangul
ValueCountFrequency (%)
97
48.5%
97
48.5%
5
 
2.5%
1
 
0.5%

x_cd
Real number (ℝ)

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.481978
Minimum35.183101
Maximum37.680803
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:27.878006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.183101
5-th percentile37.467054
Q137.499701
median37.545666
Q337.58312
95-th percentile37.658004
Maximum37.680803
Range2.4977022
Interquartile range (IQR)0.08341885

Descriptive statistics

Standard deviation0.40695241
Coefficient of variation (CV)0.010857282
Kurtosis28.60027
Mean37.481978
Median Absolute Deviation (MAD)0.04498705
Skewness-5.4151562
Sum3748.1978
Variance0.16561026
MonotonicityNot monotonic
2023-12-10T18:54:28.182073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5538442 2
 
2.0%
37.5136843 1
 
1.0%
37.5340978 1
 
1.0%
37.4734915 1
 
1.0%
37.4873774 1
 
1.0%
37.4871432 1
 
1.0%
37.5069156 1
 
1.0%
37.5022114 1
 
1.0%
37.4898803 1
 
1.0%
37.4974619 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
35.1831008 1
1.0%
35.1897592 1
1.0%
35.2361291 1
1.0%
37.4496319 1
1.0%
37.4570657 1
1.0%
37.4675802 1
1.0%
37.4715379 1
1.0%
37.4733062 1
1.0%
37.4734915 1
1.0%
37.4825633 1
1.0%
ValueCountFrequency (%)
37.680803 1
1.0%
37.6785285 1
1.0%
37.6621598 1
1.0%
37.6610997 1
1.0%
37.6590468 1
1.0%
37.6579494 1
1.0%
37.6525475 1
1.0%
37.6524299 1
1.0%
37.6465087 1
1.0%
37.6453608 1
1.0%

y_cd
Real number (ℝ)

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.03274
Minimum126.68007
Maximum128.82187
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:28.490203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.68007
5-th percentile126.84235
Q1126.90803
median127.02287
Q3127.06689
95-th percentile127.14686
Maximum128.82187
Range2.1417992
Interquartile range (IQR)0.1588614

Descriptive statistics

Standard deviation0.25616698
Coefficient of variation (CV)0.002016543
Kurtosis28.591805
Mean127.03274
Median Absolute Deviation (MAD)0.06821785
Skewness4.8327619
Sum12703.274
Variance0.065621522
MonotonicityNot monotonic
2023-12-10T18:54:28.753297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9572208 2
 
2.0%
127.0468388 1
 
1.0%
127.0662584 1
 
1.0%
126.8921298 1
 
1.0%
126.8813503 1
 
1.0%
126.8901547 1
 
1.0%
126.845637 1
 
1.0%
126.8292615 1
 
1.0%
126.8865602 1
 
1.0%
126.8865543 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
126.6800696 1
1.0%
126.8136575 1
1.0%
126.8292615 1
1.0%
126.8351791 1
1.0%
126.8418363 1
1.0%
126.8423748 1
1.0%
126.845637 1
1.0%
126.8488982 1
1.0%
126.8530522 1
1.0%
126.8559112 1
1.0%
ValueCountFrequency (%)
128.8218688 1
1.0%
128.1019511 1
1.0%
128.0617296 1
1.0%
127.1739072 1
1.0%
127.1580394 1
1.0%
127.1462752 1
1.0%
127.1435009 1
1.0%
127.1348515 1
1.0%
127.1340815 1
1.0%
127.1333655 1
1.0%

estbl_nt
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
지자체
74 
교육청
21 
사립
 
5

Length

Max length3
Median length3
Mean length2.95
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지자체 74
74.0%
교육청 21
 
21.0%
사립 5
 
5.0%

Length

2023-12-10T18:54:29.026542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:54:29.209944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지자체 74
74.0%
교육청 21
 
21.0%
사립 5
 
5.0%

pub_priv
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
공공
97 
[NULL]
 
3

Length

Max length6
Median length2
Mean length2.12
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공공
2nd row[NULL]
3rd row공공
4th row공공
5th row공공

Common Values

ValueCountFrequency (%)
공공 97
97.0%
[NULL] 3
 
3.0%

Length

2023-12-10T18:54:29.441473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:54:29.653948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공 97
97.0%
null 3
 
3.0%

cttpc
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:54:30.051418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length11.49
Min length11

Characters and Unicode

Total characters1149
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row02-3448-4741
2nd row055-330-9800
3rd row02-2225-9800
4th row02-6902-2600
5th row02-3219-7000
ValueCountFrequency (%)
02-3448-4741 1
 
1.0%
02-3437-5095 1
 
1.0%
02-864-9585 1
 
1.0%
02-830-5807 1
 
1.0%
02-2615-8200 1
 
1.0%
02-2060-8229 1
 
1.0%
02-860-2383 1
 
1.0%
02-858-9080 1
 
1.0%
02-2066-1695 1
 
1.0%
02-2689-1695 1
 
1.0%
Other values (91) 91
90.1%
2023-12-10T18:54:30.856969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 199
17.3%
0 194
16.9%
2 172
15.0%
5 77
 
6.7%
9 76
 
6.6%
4 75
 
6.5%
7 75
 
6.5%
3 74
 
6.4%
1 71
 
6.2%
6 70
 
6.1%
Other values (4) 66
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 947
82.4%
Dash Punctuation 199
 
17.3%
Close Punctuation 1
 
0.1%
Space Separator 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 194
20.5%
2 172
18.2%
5 77
 
8.1%
9 76
 
8.0%
4 75
 
7.9%
7 75
 
7.9%
3 74
 
7.8%
1 71
 
7.5%
6 70
 
7.4%
8 63
 
6.7%
Dash Punctuation
ValueCountFrequency (%)
- 199
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1149
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 199
17.3%
0 194
16.9%
2 172
15.0%
5 77
 
6.7%
9 76
 
6.6%
4 75
 
6.5%
7 75
 
6.5%
3 74
 
6.4%
1 71
 
6.2%
6 70
 
6.1%
Other values (4) 66
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1149
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 199
17.3%
0 194
16.9%
2 172
15.0%
5 77
 
6.7%
9 76
 
6.6%
4 75
 
6.5%
7 75
 
6.5%
3 74
 
6.4%
1 71
 
6.2%
6 70
 
6.1%
Other values (4) 66
 
5.7%

hmpg
Text

MISSING 

Distinct74
Distinct (%)76.3%
Missing3
Missing (%)3.0%
Memory size932.0 B
2023-12-10T18:54:31.441452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length55
Mean length27.587629
Min length13

Characters and Unicode

Total characters2676
Distinct characters39
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)64.9%

Sample

1st rowhttp://gnlib.sen.go.kr
2nd rowhttp://ghjhlib.gne.go.kr
3rd rowhttp://gdlib.sen.go.kr
4th rowhttp://gdllc.sen.go.kr
5th rowhttp://gslib.sen.go.kr
ValueCountFrequency (%)
http://lib.gangseo.seoul.kr 8
 
7.9%
http://lib.guro.go.kr 8
 
7.9%
http://www.nowonlib.kr 5
 
5.0%
http://www.gwanakcullib.seoul.kr 4
 
4.0%
http://lib.gwanak.go.kr 4
 
4.0%
http://lib.dongjak.go.kr 4
 
4.0%
http://www.gwangjinlib.seoul.kr 3
 
3.0%
http://www.unilib.dobong.kr 2
 
2.0%
http://geumcheonlib.seoul.kr 2
 
2.0%
http://geumcheonlib.seoul.kr/index.do 2
 
2.0%
Other values (57) 59
58.4%
2023-12-10T18:54:32.265205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 294
 
11.0%
/ 248
 
9.3%
t 205
 
7.7%
g 154
 
5.8%
o 148
 
5.5%
r 148
 
5.5%
l 139
 
5.2%
w 124
 
4.6%
k 121
 
4.5%
h 117
 
4.4%
Other values (29) 978
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2006
75.0%
Other Punctuation 647
 
24.2%
Decimal Number 14
 
0.5%
Space Separator 5
 
0.2%
Uppercase Letter 3
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 205
 
10.2%
g 154
 
7.7%
o 148
 
7.4%
r 148
 
7.4%
l 139
 
6.9%
w 124
 
6.2%
k 121
 
6.0%
h 117
 
5.8%
i 116
 
5.8%
n 111
 
5.5%
Other values (13) 623
31.1%
Decimal Number
ValueCountFrequency (%)
4 5
35.7%
1 3
21.4%
0 3
21.4%
3 1
 
7.1%
9 1
 
7.1%
6 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 294
45.4%
/ 248
38.3%
: 100
 
15.5%
, 4
 
0.6%
? 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
D 1
33.3%
L 1
33.3%
Space Separator
ValueCountFrequency (%)
5
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2009
75.1%
Common 667
 
24.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 205
 
10.2%
g 154
 
7.7%
o 148
 
7.4%
r 148
 
7.4%
l 139
 
6.9%
w 124
 
6.2%
k 121
 
6.0%
h 117
 
5.8%
i 116
 
5.8%
n 111
 
5.5%
Other values (16) 626
31.2%
Common
ValueCountFrequency (%)
. 294
44.1%
/ 248
37.2%
: 100
 
15.0%
5
 
0.7%
4 5
 
0.7%
, 4
 
0.6%
1 3
 
0.4%
0 3
 
0.4%
? 1
 
0.1%
3 1
 
0.1%
Other values (3) 3
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2676
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 294
 
11.0%
/ 248
 
9.3%
t 205
 
7.7%
g 154
 
5.8%
o 148
 
5.5%
r 148
 
5.5%
l 139
 
5.2%
w 124
 
4.6%
k 121
 
4.5%
h 117
 
4.4%
Other values (29) 978
36.5%

opnng_yy
Real number (ℝ)

Distinct41
Distinct (%)41.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2002.15
Minimum1920
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:33.256405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1920
5-th percentile1976.85
Q11998.75
median2008
Q32012
95-th percentile2018
Maximum2019
Range99
Interquartile range (IQR)13.25

Descriptive statistics

Standard deviation16.879475
Coefficient of variation (CV)0.0084306744
Kurtosis9.2949008
Mean2002.15
Median Absolute Deviation (MAD)6.5
Skewness-2.5871259
Sum200215
Variance284.91667
MonotonicityNot monotonic
2023-12-10T18:54:33.573536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
2008 8
 
8.0%
2009 7
 
7.0%
2007 6
 
6.0%
2010 6
 
6.0%
2018 5
 
5.0%
2015 5
 
5.0%
2017 5
 
5.0%
2006 5
 
5.0%
2013 4
 
4.0%
1999 3
 
3.0%
Other values (31) 46
46.0%
ValueCountFrequency (%)
1920 1
1.0%
1922 1
1.0%
1964 1
1.0%
1971 1
1.0%
1974 1
1.0%
1977 1
1.0%
1979 1
1.0%
1980 1
1.0%
1981 2
2.0%
1982 1
1.0%
ValueCountFrequency (%)
2019 1
 
1.0%
2018 5
5.0%
2017 5
5.0%
2016 1
 
1.0%
2015 5
5.0%
2014 3
3.0%
2013 4
4.0%
2012 3
3.0%
2011 3
3.0%
2010 6
6.0%

fcltscl_place
Real number (ℝ)

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3482.18
Minimum243
Maximum36470
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:33.855028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum243
5-th percentile306.8
Q1743
median1185.5
Q33353.75
95-th percentile13456.3
Maximum36470
Range36227
Interquartile range (IQR)2610.75

Descriptive statistics

Standard deviation5821.0859
Coefficient of variation (CV)1.6716786
Kurtosis14.567908
Mean3482.18
Median Absolute Deviation (MAD)717.5
Skewness3.527253
Sum348218
Variance33885041
MonotonicityNot monotonic
2023-12-10T18:54:34.128313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1500 2
 
2.0%
701 2
 
2.0%
992 2
 
2.0%
1079 1
 
1.0%
3500 1
 
1.0%
880 1
 
1.0%
1078 1
 
1.0%
2430 1
 
1.0%
460 1
 
1.0%
445 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
243 1
1.0%
257 1
1.0%
264 1
1.0%
269 1
1.0%
303 1
1.0%
307 1
1.0%
333 1
1.0%
351 1
1.0%
378 1
1.0%
396 1
1.0%
ValueCountFrequency (%)
36470 1
1.0%
30145 1
1.0%
21561 1
1.0%
17946 1
1.0%
14545 1
1.0%
13399 1
1.0%
13316 1
1.0%
12807 1
1.0%
9679 1
1.0%
9507 1
1.0%

fcltscl_bulding
Real number (ℝ)

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2170.31
Minimum264
Maximum13266
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:34.529462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum264
5-th percentile324.1
Q1518.5
median1132
Q32867.75
95-th percentile7283.9
Maximum13266
Range13002
Interquartile range (IQR)2349.25

Descriptive statistics

Standard deviation2445.4144
Coefficient of variation (CV)1.1267581
Kurtosis4.8327281
Mean2170.31
Median Absolute Deviation (MAD)750.5
Skewness2.0888079
Sum217031
Variance5980051.4
MonotonicityNot monotonic
2023-12-10T18:54:35.195168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1963 2
 
2.0%
307 2
 
2.0%
1631 1
 
1.0%
333 1
 
1.0%
476 1
 
1.0%
441 1
 
1.0%
659 1
 
1.0%
638 1
 
1.0%
460 1
 
1.0%
492 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
264 1
1.0%
278 1
1.0%
306 1
1.0%
307 2
2.0%
325 1
1.0%
329 1
1.0%
333 1
1.0%
343 1
1.0%
348 1
1.0%
359 1
1.0%
ValueCountFrequency (%)
13266 1
1.0%
9716 1
1.0%
9410 1
1.0%
8260 1
1.0%
7301 1
1.0%
7283 1
1.0%
6946 1
1.0%
6864 1
1.0%
6805 1
1.0%
6526 1
1.0%

fcltscl_chair
Real number (ℝ)

Distinct81
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean309.45
Minimum52
Maximum1080
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:35.872702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum52
5-th percentile67.6
Q1116.5
median211.5
Q3416.75
95-th percentile902.45
Maximum1080
Range1028
Interquartile range (IQR)300.25

Descriptive statistics

Standard deviation256.30212
Coefficient of variation (CV)0.8282505
Kurtosis1.4817911
Mean309.45
Median Absolute Deviation (MAD)119.5
Skewness1.4300415
Sum30945
Variance65690.775
MonotonicityNot monotonic
2023-12-10T18:54:36.343796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 5
 
5.0%
60 4
 
4.0%
214 3
 
3.0%
92 3
 
3.0%
504 2
 
2.0%
68 2
 
2.0%
193 2
 
2.0%
124 2
 
2.0%
147 2
 
2.0%
449 2
 
2.0%
Other values (71) 73
73.0%
ValueCountFrequency (%)
52 1
 
1.0%
60 4
4.0%
68 2
2.0%
70 1
 
1.0%
77 1
 
1.0%
80 1
 
1.0%
86 1
 
1.0%
89 1
 
1.0%
92 3
3.0%
93 1
 
1.0%
ValueCountFrequency (%)
1080 1
1.0%
1052 1
1.0%
1042 1
1.0%
1028 1
1.0%
949 1
1.0%
900 1
1.0%
885 1
1.0%
769 1
1.0%
738 1
1.0%
662 1
1.0%

psgud_book
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97457.62
Minimum7078
Maximum508757
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:36.661696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7078
5-th percentile12697.65
Q133331
median58436
Q3136799.5
95-th percentile254628
Maximum508757
Range501679
Interquartile range (IQR)103468.5

Descriptive statistics

Standard deviation96944.433
Coefficient of variation (CV)0.99473425
Kurtosis4.5708989
Mean97457.62
Median Absolute Deviation (MAD)32533.5
Skewness1.9309547
Sum9745762
Variance9.398223 × 109
MonotonicityNot monotonic
2023-12-10T18:54:37.092202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
153583 1
 
1.0%
26884 1
 
1.0%
72781 1
 
1.0%
34363 1
 
1.0%
38963 1
 
1.0%
33030 1
 
1.0%
16300 1
 
1.0%
85867 1
 
1.0%
27460 1
 
1.0%
38903 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
7078 1
1.0%
10544 1
1.0%
11366 1
1.0%
11414 1
1.0%
11912 1
1.0%
12739 1
1.0%
15129 1
1.0%
16300 1
1.0%
18354 1
1.0%
18691 1
1.0%
ValueCountFrequency (%)
508757 1
1.0%
494318 1
1.0%
298165 1
1.0%
290889 1
1.0%
287422 1
1.0%
252902 1
1.0%
250587 1
1.0%
239389 1
1.0%
237333 1
1.0%
236227 1
1.0%

psgud_nobook
Real number (ℝ)

ZEROS 

Distinct75
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3708.75
Minimum0
Maximum26329
Zeros23
Zeros (%)23.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:37.483923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median1136
Q35808.75
95-th percentile12739.45
Maximum26329
Range26329
Interquartile range (IQR)5806.75

Descriptive statistics

Standard deviation5278.8929
Coefficient of variation (CV)1.4233617
Kurtosis3.2146049
Mean3708.75
Median Absolute Deviation (MAD)1136
Skewness1.7772877
Sum370875
Variance27866710
MonotonicityNot monotonic
2023-12-10T18:54:37.829412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 23
 
23.0%
2 3
 
3.0%
10192 2
 
2.0%
41 1
 
1.0%
8066 1
 
1.0%
4711 1
 
1.0%
181 1
 
1.0%
521 1
 
1.0%
148 1
 
1.0%
2082 1
 
1.0%
Other values (65) 65
65.0%
ValueCountFrequency (%)
0 23
23.0%
1 1
 
1.0%
2 3
 
3.0%
41 1
 
1.0%
52 1
 
1.0%
76 1
 
1.0%
148 1
 
1.0%
181 1
 
1.0%
231 1
 
1.0%
262 1
 
1.0%
ValueCountFrequency (%)
26329 1
1.0%
19394 1
1.0%
18004 1
1.0%
16602 1
1.0%
14401 1
1.0%
12652 1
1.0%
12383 1
1.0%
11559 1
1.0%
11550 1
1.0%
11318 1
1.0%

psgud_paper
Real number (ℝ)

ZEROS 

Distinct75
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean176.69
Minimum0
Maximum1100
Zeros3
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:38.124115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.95
Q112
median55.5
Q3185.75
95-th percentile759.25
Maximum1100
Range1100
Interquartile range (IQR)173.75

Descriptive statistics

Standard deviation262.48254
Coefficient of variation (CV)1.485554
Kurtosis1.9629485
Mean176.69
Median Absolute Deviation (MAD)45
Skewness1.7487652
Sum17669
Variance68897.085
MonotonicityNot monotonic
2023-12-10T18:54:38.451849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 7
 
7.0%
12 4
 
4.0%
11 4
 
4.0%
55 3
 
3.0%
0 3
 
3.0%
93 2
 
2.0%
60 2
 
2.0%
3 2
 
2.0%
106 2
 
2.0%
50 2
 
2.0%
Other values (65) 69
69.0%
ValueCountFrequency (%)
0 3
3.0%
3 2
 
2.0%
4 1
 
1.0%
5 2
 
2.0%
6 1
 
1.0%
8 1
 
1.0%
9 1
 
1.0%
10 7
7.0%
11 4
4.0%
12 4
4.0%
ValueCountFrequency (%)
1100 1
1.0%
922 1
1.0%
904 1
1.0%
836 1
1.0%
764 1
1.0%
759 1
1.0%
724 1
1.0%
702 1
1.0%
686 1
1.0%
650 1
1.0%

psgud_addbook
Real number (ℝ)

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7350.09
Minimum651
Maximum46553
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:38.804698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum651
5-th percentile1117.8
Q12588
median5336
Q310462.25
95-th percentile18645.35
Maximum46553
Range45902
Interquartile range (IQR)7874.25

Descriptive statistics

Standard deviation6875.3222
Coefficient of variation (CV)0.93540653
Kurtosis10.086541
Mean7350.09
Median Absolute Deviation (MAD)3233.5
Skewness2.4883781
Sum735009
Variance47270055
MonotonicityNot monotonic
2023-12-10T18:54:39.098893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2588 2
 
2.0%
2769 2
 
2.0%
8651 1
 
1.0%
2187 1
 
1.0%
2146 1
 
1.0%
2003 1
 
1.0%
2716 1
 
1.0%
3463 1
 
1.0%
2365 1
 
1.0%
2419 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
651 1
1.0%
875 1
1.0%
992 1
1.0%
1081 1
1.0%
1095 1
1.0%
1119 1
1.0%
1193 1
1.0%
1749 1
1.0%
1819 1
1.0%
1847 1
1.0%
ValueCountFrequency (%)
46553 1
1.0%
26787 1
1.0%
24022 1
1.0%
21046 1
1.0%
21008 1
1.0%
18521 1
1.0%
17509 1
1.0%
17328 1
1.0%
16455 1
1.0%
14395 1
1.0%

psgud_addnobook
Real number (ℝ)

ZEROS 

Distinct64
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean204.76
Minimum0
Maximum1371
Zeros35
Zeros (%)35.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:39.362581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median85.5
Q3305.5
95-th percentile724.55
Maximum1371
Range1371
Interquartile range (IQR)305.5

Descriptive statistics

Standard deviation293.90056
Coefficient of variation (CV)1.4353417
Kurtosis4.2982853
Mean204.76
Median Absolute Deviation (MAD)85.5
Skewness2.0121489
Sum20476
Variance86377.538
MonotonicityNot monotonic
2023-12-10T18:54:39.664081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 35
35.0%
112 2
 
2.0%
414 2
 
2.0%
157 1
 
1.0%
94 1
 
1.0%
97 1
 
1.0%
104 1
 
1.0%
366 1
 
1.0%
106 1
 
1.0%
906 1
 
1.0%
Other values (54) 54
54.0%
ValueCountFrequency (%)
0 35
35.0%
2 1
 
1.0%
5 1
 
1.0%
24 1
 
1.0%
26 1
 
1.0%
29 1
 
1.0%
42 1
 
1.0%
48 1
 
1.0%
52 1
 
1.0%
53 1
 
1.0%
ValueCountFrequency (%)
1371 1
1.0%
1309 1
1.0%
1181 1
1.0%
933 1
1.0%
906 1
1.0%
715 1
1.0%
682 1
1.0%
631 1
1.0%
617 1
1.0%
605 1
1.0%

psgud_addpaper
Real number (ℝ)

ZEROS 

Distinct50
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.01
Minimum0
Maximum922
Zeros31
Zeros (%)31.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:39.940772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6.5
Q347.75
95-th percentile478.2
Maximum922
Range922
Interquartile range (IQR)47.75

Descriptive statistics

Standard deviation173.22202
Coefficient of variation (CV)2.5470081
Kurtosis13.881317
Mean68.01
Median Absolute Deviation (MAD)6.5
Skewness3.72655
Sum6801
Variance30005.869
MonotonicityNot monotonic
2023-12-10T18:54:40.274106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 31
31.0%
5 4
 
4.0%
2 4
 
4.0%
1 4
 
4.0%
3 3
 
3.0%
6 3
 
3.0%
50 2
 
2.0%
38 2
 
2.0%
17 2
 
2.0%
7 2
 
2.0%
Other values (40) 43
43.0%
ValueCountFrequency (%)
0 31
31.0%
1 4
 
4.0%
2 4
 
4.0%
3 3
 
3.0%
4 1
 
1.0%
5 4
 
4.0%
6 3
 
3.0%
7 2
 
2.0%
9 1
 
1.0%
10 1
 
1.0%
ValueCountFrequency (%)
922 1
1.0%
857 1
1.0%
836 1
1.0%
606 1
1.0%
520 1
1.0%
476 1
1.0%
270 1
1.0%
213 1
1.0%
193 1
1.0%
152 1
1.0%

emp_ntotal
Real number (ℝ)

Distinct30
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.58
Minimum0
Maximum52
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:40.528787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.95
Q13
median7
Q314.25
95-th percentile29.1
Maximum52
Range52
Interquartile range (IQR)11.25

Descriptive statistics

Standard deviation10.287955
Coefficient of variation (CV)0.97239651
Kurtosis2.4918338
Mean10.58
Median Absolute Deviation (MAD)4
Skewness1.626791
Sum1058
Variance105.84202
MonotonicityNot monotonic
2023-12-10T18:54:40.887945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
3 17
17.0%
7 11
 
11.0%
4 11
 
11.0%
6 6
 
6.0%
9 6
 
6.0%
2 5
 
5.0%
5 4
 
4.0%
1 4
 
4.0%
11 4
 
4.0%
28 4
 
4.0%
Other values (20) 28
28.0%
ValueCountFrequency (%)
0 1
 
1.0%
1 4
 
4.0%
2 5
 
5.0%
3 17
17.0%
4 11
11.0%
5 4
 
4.0%
6 6
 
6.0%
7 11
11.0%
8 2
 
2.0%
9 6
 
6.0%
ValueCountFrequency (%)
52 1
 
1.0%
42 1
 
1.0%
38 1
 
1.0%
32 1
 
1.0%
31 1
 
1.0%
29 1
 
1.0%
28 4
4.0%
27 2
2.0%
25 1
 
1.0%
24 2
2.0%

emp_total
Real number (ℝ)

Distinct31
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.27
Minimum0
Maximum60
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:41.124696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13.75
median7
Q317.25
95-th percentile31.05
Maximum60
Range60
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation11.398968
Coefficient of variation (CV)1.0114435
Kurtosis3.9442074
Mean11.27
Median Absolute Deviation (MAD)4
Skewness1.8561362
Sum1127
Variance129.93646
MonotonicityNot monotonic
2023-12-10T18:54:41.399120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
3 15
15.0%
4 13
13.0%
7 10
 
10.0%
6 5
 
5.0%
1 5
 
5.0%
19 5
 
5.0%
8 4
 
4.0%
5 4
 
4.0%
2 4
 
4.0%
11 4
 
4.0%
Other values (21) 31
31.0%
ValueCountFrequency (%)
0 1
 
1.0%
1 5
 
5.0%
2 4
 
4.0%
3 15
15.0%
4 13
13.0%
5 4
 
4.0%
6 5
 
5.0%
7 10
10.0%
8 4
 
4.0%
9 3
 
3.0%
ValueCountFrequency (%)
60 1
 
1.0%
52 1
 
1.0%
42 1
 
1.0%
39 1
 
1.0%
32 1
 
1.0%
31 1
 
1.0%
29 1
 
1.0%
28 3
3.0%
27 2
2.0%
26 1
 
1.0%

admemp_ntotal
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7
Minimum0
Maximum11
Zeros41
Zeros (%)41.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:41.660848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile5
Maximum11
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.0523453
Coefficient of variation (CV)1.2072619
Kurtosis3.4011592
Mean1.7
Median Absolute Deviation (MAD)1
Skewness1.5738429
Sum170
Variance4.2121212
MonotonicityNot monotonic
2023-12-10T18:54:41.927733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 41
41.0%
1 16
 
16.0%
2 15
 
15.0%
3 9
 
9.0%
4 9
 
9.0%
5 6
 
6.0%
7 2
 
2.0%
6 1
 
1.0%
11 1
 
1.0%
ValueCountFrequency (%)
0 41
41.0%
1 16
 
16.0%
2 15
 
15.0%
3 9
 
9.0%
4 9
 
9.0%
5 6
 
6.0%
6 1
 
1.0%
7 2
 
2.0%
11 1
 
1.0%
ValueCountFrequency (%)
11 1
 
1.0%
7 2
 
2.0%
6 1
 
1.0%
5 6
 
6.0%
4 9
 
9.0%
3 9
 
9.0%
2 15
 
15.0%
1 16
 
16.0%
0 41
41.0%

admemp_total
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.85
Minimum0
Maximum15
Zeros41
Zeros (%)41.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:42.132172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile6
Maximum15
Range15
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.4756389
Coefficient of variation (CV)1.3381832
Kurtosis8.5664274
Mean1.85
Median Absolute Deviation (MAD)1
Skewness2.4009851
Sum185
Variance6.1287879
MonotonicityNot monotonic
2023-12-10T18:54:42.424115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 41
41.0%
1 15
 
15.0%
2 15
 
15.0%
3 10
 
10.0%
4 8
 
8.0%
5 5
 
5.0%
6 2
 
2.0%
8 1
 
1.0%
7 1
 
1.0%
11 1
 
1.0%
ValueCountFrequency (%)
0 41
41.0%
1 15
 
15.0%
2 15
 
15.0%
3 10
 
10.0%
4 8
 
8.0%
5 5
 
5.0%
6 2
 
2.0%
7 1
 
1.0%
8 1
 
1.0%
11 1
 
1.0%
ValueCountFrequency (%)
15 1
 
1.0%
11 1
 
1.0%
8 1
 
1.0%
7 1
 
1.0%
6 2
 
2.0%
5 5
 
5.0%
4 8
8.0%
3 10
10.0%
2 15
15.0%
1 15
15.0%

lbrrnemp_ntotal
Real number (ℝ)

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.98
Minimum0
Maximum39
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:42.764327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median4
Q39
95-th percentile20.05
Maximum39
Range39
Interquartile range (IQR)6

Descriptive statistics

Standard deviation7.0867354
Coefficient of variation (CV)1.0152916
Kurtosis4.3522249
Mean6.98
Median Absolute Deviation (MAD)2
Skewness1.9484449
Sum698
Variance50.221818
MonotonicityNot monotonic
2023-12-10T18:54:43.560130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3 16
16.0%
4 15
15.0%
2 12
12.0%
1 11
11.0%
5 9
9.0%
6 6
 
6.0%
7 3
 
3.0%
14 3
 
3.0%
17 3
 
3.0%
9 2
 
2.0%
Other values (15) 20
20.0%
ValueCountFrequency (%)
0 1
 
1.0%
1 11
11.0%
2 12
12.0%
3 16
16.0%
4 15
15.0%
5 9
9.0%
6 6
 
6.0%
7 3
 
3.0%
8 1
 
1.0%
9 2
 
2.0%
ValueCountFrequency (%)
39 1
 
1.0%
31 1
 
1.0%
23 2
2.0%
21 1
 
1.0%
20 2
2.0%
19 2
2.0%
18 1
 
1.0%
17 3
3.0%
16 1
 
1.0%
15 1
 
1.0%

lbrrnemp_total
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.26
Minimum0
Maximum39
Zeros2
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:43.846737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median4
Q311
95-th percentile20.05
Maximum39
Range39
Interquartile range (IQR)8

Descriptive statistics

Standard deviation7.0876475
Coefficient of variation (CV)0.97625999
Kurtosis3.984162
Mean7.26
Median Absolute Deviation (MAD)2
Skewness1.8170982
Sum726
Variance50.234747
MonotonicityNot monotonic
2023-12-10T18:54:44.141893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
3 19
19.0%
4 13
13.0%
1 10
10.0%
2 9
9.0%
6 8
 
8.0%
5 7
 
7.0%
11 4
 
4.0%
14 3
 
3.0%
9 3
 
3.0%
12 3
 
3.0%
Other values (14) 21
21.0%
ValueCountFrequency (%)
0 2
 
2.0%
1 10
10.0%
2 9
9.0%
3 19
19.0%
4 13
13.0%
5 7
 
7.0%
6 8
8.0%
7 1
 
1.0%
9 3
 
3.0%
10 1
 
1.0%
ValueCountFrequency (%)
39 1
1.0%
31 1
1.0%
23 2
2.0%
21 1
1.0%
20 1
1.0%
19 2
2.0%
18 2
2.0%
17 2
2.0%
16 2
2.0%
15 2
2.0%

cmptemp_ntotal
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
88 
1
11 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 88
88.0%
1 11
 
11.0%
2 1
 
1.0%

Length

2023-12-10T18:54:44.433308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:54:44.665030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 88
88.0%
1 11
 
11.0%
2 1
 
1.0%

cmptemp_total
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
87 
1
11 
2
 
1
15
 
1

Length

Max length2
Median length1
Mean length1.01
Min length1

Unique

Unique2 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 87
87.0%
1 11
 
11.0%
2 1
 
1.0%
15 1
 
1.0%

Length

2023-12-10T18:54:44.879829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:54:45.115544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 87
87.0%
1 11
 
11.0%
2 1
 
1.0%
15 1
 
1.0%

etcemp_ntotal
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.77
Minimum0
Maximum12
Zeros40
Zeros (%)40.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:45.317019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile6.05
Maximum12
Range12
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.2734968
Coefficient of variation (CV)1.2844615
Kurtosis3.5716521
Mean1.77
Median Absolute Deviation (MAD)1
Skewness1.7167708
Sum177
Variance5.1687879
MonotonicityNot monotonic
2023-12-10T18:54:45.572498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 40
40.0%
1 23
23.0%
3 9
 
9.0%
2 8
 
8.0%
4 7
 
7.0%
5 6
 
6.0%
7 3
 
3.0%
6 2
 
2.0%
8 1
 
1.0%
12 1
 
1.0%
ValueCountFrequency (%)
0 40
40.0%
1 23
23.0%
2 8
 
8.0%
3 9
 
9.0%
4 7
 
7.0%
5 6
 
6.0%
6 2
 
2.0%
7 3
 
3.0%
8 1
 
1.0%
12 1
 
1.0%
ValueCountFrequency (%)
12 1
 
1.0%
8 1
 
1.0%
7 3
 
3.0%
6 2
 
2.0%
5 6
 
6.0%
4 7
 
7.0%
3 9
 
9.0%
2 8
 
8.0%
1 23
23.0%
0 40
40.0%

etcemp_total
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.88
Minimum0
Maximum15
Zeros41
Zeros (%)41.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:45.849593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile7
Maximum15
Range15
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.6334292
Coefficient of variation (CV)1.4007602
Kurtosis7.0958347
Mean1.88
Median Absolute Deviation (MAD)1
Skewness2.2932761
Sum188
Variance6.9349495
MonotonicityNot monotonic
2023-12-10T18:54:46.080674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 41
41.0%
1 22
22.0%
3 9
 
9.0%
4 9
 
9.0%
2 7
 
7.0%
7 4
 
4.0%
5 4
 
4.0%
8 1
 
1.0%
6 1
 
1.0%
12 1
 
1.0%
ValueCountFrequency (%)
0 41
41.0%
1 22
22.0%
2 7
 
7.0%
3 9
 
9.0%
4 9
 
9.0%
5 4
 
4.0%
6 1
 
1.0%
7 4
 
4.0%
8 1
 
1.0%
12 1
 
1.0%
ValueCountFrequency (%)
15 1
 
1.0%
12 1
 
1.0%
8 1
 
1.0%
7 4
 
4.0%
6 1
 
1.0%
5 4
 
4.0%
4 9
9.0%
3 9
9.0%
2 7
 
7.0%
1 22
22.0%

crqfc_1st
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
57 
1
25 
2
12 
3
 
5
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row2
2nd row0
3rd row1
4th row3
5th row2

Common Values

ValueCountFrequency (%)
0 57
57.0%
1 25
25.0%
2 12
 
12.0%
3 5
 
5.0%
4 1
 
1.0%

Length

2023-12-10T18:54:46.367430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:54:46.612744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 57
57.0%
1 25
25.0%
2 12
 
12.0%
3 5
 
5.0%
4 1
 
1.0%

crqfc_2st
Real number (ℝ)

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.52
Minimum0
Maximum25
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:46.852421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4.5
Q311
95-th percentile17
Maximum25
Range25
Interquartile range (IQR)9

Descriptive statistics

Standard deviation5.4113237
Coefficient of variation (CV)0.82995762
Kurtosis0.58059731
Mean6.52
Median Absolute Deviation (MAD)2.5
Skewness1.1043418
Sum652
Variance29.282424
MonotonicityNot monotonic
2023-12-10T18:54:47.099352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
2 15
15.0%
1 12
12.0%
3 12
12.0%
4 10
10.0%
6 9
9.0%
5 5
 
5.0%
11 5
 
5.0%
14 5
 
5.0%
7 4
 
4.0%
15 4
 
4.0%
Other values (11) 19
19.0%
ValueCountFrequency (%)
0 1
 
1.0%
1 12
12.0%
2 15
15.0%
3 12
12.0%
4 10
10.0%
5 5
 
5.0%
6 9
9.0%
7 4
 
4.0%
8 4
 
4.0%
9 1
 
1.0%
ValueCountFrequency (%)
25 1
 
1.0%
21 1
 
1.0%
19 1
 
1.0%
18 1
 
1.0%
17 2
 
2.0%
15 4
4.0%
14 5
5.0%
13 2
 
2.0%
12 4
4.0%
11 5
5.0%

crqfc_3st
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.89
Minimum0
Maximum15
Zeros39
Zeros (%)39.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:47.614617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile7
Maximum15
Range15
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.6010682
Coefficient of variation (CV)1.3762265
Kurtosis6.42101
Mean1.89
Median Absolute Deviation (MAD)1
Skewness2.2140843
Sum189
Variance6.7655556
MonotonicityNot monotonic
2023-12-10T18:54:47.970125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 39
39.0%
1 20
20.0%
2 17
17.0%
3 7
 
7.0%
7 5
 
5.0%
6 4
 
4.0%
4 3
 
3.0%
5 2
 
2.0%
8 1
 
1.0%
10 1
 
1.0%
ValueCountFrequency (%)
0 39
39.0%
1 20
20.0%
2 17
17.0%
3 7
 
7.0%
4 3
 
3.0%
5 2
 
2.0%
6 4
 
4.0%
7 5
 
5.0%
8 1
 
1.0%
10 1
 
1.0%
ValueCountFrequency (%)
15 1
 
1.0%
10 1
 
1.0%
8 1
 
1.0%
7 5
 
5.0%
6 4
 
4.0%
5 2
 
2.0%
4 3
 
3.0%
3 7
 
7.0%
2 17
17.0%
1 20
20.0%

wrkbdg_total
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1005911.3
Minimum30475
Maximum5759181
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:48.213053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30475
5-th percentile124710.75
Q1230915
median524366
Q31530473.5
95-th percentile3090047.4
Maximum5759181
Range5728706
Interquartile range (IQR)1299558.5

Descriptive statistics

Standard deviation1153563.7
Coefficient of variation (CV)1.1467848
Kurtosis3.6285439
Mean1005911.3
Median Absolute Deviation (MAD)300912
Skewness1.8556492
Sum1.0059113 × 108
Variance1.3307092 × 1012
MonotonicityNot monotonic
2023-12-10T18:54:48.563053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1763282 1
 
1.0%
276667 1
 
1.0%
524806 1
 
1.0%
224959 1
 
1.0%
225119 1
 
1.0%
225741 1
 
1.0%
273838 1
 
1.0%
416969 1
 
1.0%
223173 1
 
1.0%
223735 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
30475 1
1.0%
32474 1
1.0%
46041 1
1.0%
65577 1
1.0%
70822 1
1.0%
127547 1
1.0%
163793 1
1.0%
164601 1
1.0%
166895 1
1.0%
170726 1
1.0%
ValueCountFrequency (%)
5759181 1
1.0%
5317856 1
1.0%
3869551 1
1.0%
3394602 1
1.0%
3329094 1
1.0%
3077466 1
1.0%
3041436 1
1.0%
2814669 1
1.0%
2809765 1
1.0%
2754669 1
1.0%

wrkbdg_mem
Real number (ℝ)

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean563119.6
Minimum17411
Maximum3542398
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:48.895923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17411
5-th percentile49530.8
Q1159275.75
median249646
Q3771867.25
95-th percentile1892706.6
Maximum3542398
Range3524987
Interquartile range (IQR)612591.5

Descriptive statistics

Standard deviation678074.24
Coefficient of variation (CV)1.2041389
Kurtosis4.7778821
Mean563119.6
Median Absolute Deviation (MAD)131764
Skewness2.0868043
Sum56311960
Variance4.5978468 × 1011
MonotonicityNot monotonic
2023-12-10T18:54:49.342689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
169441 4
 
4.0%
167868 2
 
2.0%
1053119 1
 
1.0%
200030 1
 
1.0%
185012 1
 
1.0%
271364 1
 
1.0%
209835 1
 
1.0%
335736 1
 
1.0%
330245 1
 
1.0%
155025 1
 
1.0%
Other values (86) 86
86.0%
ValueCountFrequency (%)
17411 1
1.0%
22655 1
1.0%
22988 1
1.0%
24946 1
1.0%
39780 1
1.0%
50044 1
1.0%
53674 1
1.0%
61994 1
1.0%
70242 1
1.0%
84118 1
1.0%
ValueCountFrequency (%)
3542398 1
1.0%
3100195 1
1.0%
2440133 1
1.0%
1944750 1
1.0%
1943942 1
1.0%
1890010 1
1.0%
1791688 1
1.0%
1710624 1
1.0%
1626047 1
1.0%
1603777 1
1.0%

wrkbdg_dta
Real number (ℝ)

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90806.41
Minimum1156
Maximum550226
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:49.838070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1156
5-th percentile12300.7
Q132606
median54696.5
Q3143665.5
95-th percentile221521.2
Maximum550226
Range549070
Interquartile range (IQR)111059.5

Descriptive statistics

Standard deviation87713.431
Coefficient of variation (CV)0.96593876
Kurtosis6.6989813
Mean90806.41
Median Absolute Deviation (MAD)32470.5
Skewness2.0784419
Sum9080641
Variance7.693646 × 109
MonotonicityNot monotonic
2023-12-10T18:54:50.191975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40000 2
 
2.0%
22213 2
 
2.0%
142827 1
 
1.0%
35022 1
 
1.0%
74300 1
 
1.0%
34920 1
 
1.0%
33440 1
 
1.0%
35370 1
 
1.0%
35059 1
 
1.0%
49889 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
1156 1
1.0%
2562 1
1.0%
4793 1
1.0%
8576 1
1.0%
8799 1
1.0%
12485 1
1.0%
14075 1
1.0%
17319 1
1.0%
21339 1
1.0%
22185 1
1.0%
ValueCountFrequency (%)
550226 1
1.0%
321359 1
1.0%
302226 1
1.0%
255078 1
1.0%
248448 1
1.0%
220104 1
1.0%
219804 1
1.0%
219392 1
1.0%
217455 1
1.0%
210679 1
1.0%

wrkbdg_etc
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean351985.25
Minimum3699
Maximum1997391
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:50.578324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3699
5-th percentile20119.35
Q143821.75
median164226.5
Q3520469.75
95-th percentile1214847
Maximum1997391
Range1993692
Interquartile range (IQR)476648

Descriptive statistics

Standard deviation436795.05
Coefficient of variation (CV)1.240947
Kurtosis2.6483986
Mean351985.25
Median Absolute Deviation (MAD)134499
Skewness1.7088256
Sum35198525
Variance1.9078992 × 1011
MonotonicityNot monotonic
2023-12-10T18:54:50.926979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
567336 1
 
1.0%
89012 1
 
1.0%
179142 1
 
1.0%
20598 1
 
1.0%
22238 1
 
1.0%
22503 1
 
1.0%
28944 1
 
1.0%
31344 1
 
1.0%
20758 1
 
1.0%
20968 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
3699 1
1.0%
4373 1
1.0%
4663 1
1.0%
6264 1
1.0%
11025 1
1.0%
20598 1
1.0%
20683 1
1.0%
20758 1
1.0%
20968 1
1.0%
22238 1
1.0%
ValueCountFrequency (%)
1997391 1
1.0%
1896302 1
1.0%
1432956 1
1.0%
1397537 1
1.0%
1269644 1
1.0%
1211963 1
1.0%
1195582 1
1.0%
1190636 1
1.0%
1173383 1
1.0%
974441 1
1.0%

usemem_total
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean422630.36
Minimum3200
Maximum1838885
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:51.253414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3200
5-th percentile40599.85
Q186268.5
median261398
Q3562814.5
95-th percentile1247043.6
Maximum1838885
Range1835685
Interquartile range (IQR)476546

Descriptive statistics

Standard deviation424493.78
Coefficient of variation (CV)1.0044091
Kurtosis1.2668069
Mean422630.36
Median Absolute Deviation (MAD)195341.5
Skewness1.3657368
Sum42263036
Variance1.8019497 × 1011
MonotonicityNot monotonic
2023-12-10T18:54:51.605211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
536553 1
 
1.0%
144023 1
 
1.0%
344742 1
 
1.0%
97664 1
 
1.0%
67402 1
 
1.0%
44180 1
 
1.0%
79021 1
 
1.0%
63020 1
 
1.0%
51495 1
 
1.0%
58724 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
3200 1
1.0%
6002 1
1.0%
9000 1
1.0%
19220 1
1.0%
37386 1
1.0%
40769 1
1.0%
41753 1
1.0%
44180 1
1.0%
45873 1
1.0%
47933 1
1.0%
ValueCountFrequency (%)
1838885 1
1.0%
1610741 1
1.0%
1584679 1
1.0%
1554970 1
1.0%
1367458 1
1.0%
1240706 1
1.0%
1186981 1
1.0%
1186097 1
1.0%
1163219 1
1.0%
1072250 1
1.0%

usebook_total
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean146168.92
Minimum0
Maximum677968
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:52.010613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4798.15
Q157623
median96682
Q3211374.25
95-th percentile372946.65
Maximum677968
Range677968
Interquartile range (IQR)153751.25

Descriptive statistics

Standard deviation130235.81
Coefficient of variation (CV)0.8909952
Kurtosis3.3677625
Mean146168.92
Median Absolute Deviation (MAD)62923.5
Skewness1.6409109
Sum14616892
Variance1.6961365 × 1010
MonotonicityNot monotonic
2023-12-10T18:54:52.370331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
206633 1
 
1.0%
84429 1
 
1.0%
72399 1
 
1.0%
14382 1
 
1.0%
22039 1
 
1.0%
26055 1
 
1.0%
41523 1
 
1.0%
43396 1
 
1.0%
12868 1
 
1.0%
33633 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
0 1
1.0%
566 1
1.0%
1410 1
1.0%
3527 1
1.0%
4269 1
1.0%
4826 1
1.0%
12868 1
1.0%
14382 1
1.0%
22039 1
1.0%
24589 1
1.0%
ValueCountFrequency (%)
677968 1
1.0%
592156 1
1.0%
531870 1
1.0%
479782 1
1.0%
377443 1
1.0%
372710 1
1.0%
338789 1
1.0%
327539 1
1.0%
323189 1
1.0%
315101 1
1.0%

update_date
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210101
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210101
2nd row20210101
3rd row20210101
4th row20210101
5th row20210101

Common Values

ValueCountFrequency (%)
20210101 100
100.0%

Length

2023-12-10T18:54:52.740626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:54:52.999810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210101 100
100.0%

data_ref
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
문화데이터총람2020
100 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row문화데이터총람2020
2nd row문화데이터총람2020
3rd row문화데이터총람2020
4th row문화데이터총람2020
5th row문화데이터총람2020

Common Values

ValueCountFrequency (%)
문화데이터총람2020 100
100.0%

Length

2023-12-10T18:54:53.248874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:54:53.471772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화데이터총람2020 100
100.0%

file_name
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC_476_DMSTC_MCST_IBLLBR_2021
100 

Length

Max length29
Median length29
Mean length29
Min length29

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_476_DMSTC_MCST_IBLLBR_2021
2nd rowKC_476_DMSTC_MCST_IBLLBR_2021
3rd rowKC_476_DMSTC_MCST_IBLLBR_2021
4th rowKC_476_DMSTC_MCST_IBLLBR_2021
5th rowKC_476_DMSTC_MCST_IBLLBR_2021

Common Values

ValueCountFrequency (%)
KC_476_DMSTC_MCST_IBLLBR_2021 100
100.0%

Length

2023-12-10T18:54:53.709228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:54:53.925494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_476_dmstc_mcst_ibllbr_2021 100
100.0%

base_ymd
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20200101
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20200101
2nd row20200101
3rd row20200101
4th row20200101
5th row20200101

Common Values

ValueCountFrequency (%)
20200101 100
100.0%

Length

2023-12-10T18:54:54.236151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:54:54.476257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20200101 100
100.0%

Sample

idlclasmlsfcfclt_namectprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrzip_cdgrid_cdx_cdy_cdestbl_ntpub_privcttpchmpgopnng_yyfcltscl_placefcltscl_buldingfcltscl_chairpsgud_bookpsgud_nobookpsgud_paperpsgud_addbookpsgud_addnobookpsgud_addpaperemp_ntotalemp_totaladmemp_ntotaladmemp_totallbrrnemp_ntotallbrrnemp_totalcmptemp_ntotalcmptemp_totaletcemp_ntotaletcemp_totalcrqfc_1stcrqfc_2stcrqfc_3stwrkbdg_totalwrkbdg_memwrkbdg_dtawrkbdg_etcusemem_totalusebook_totalupdate_datedata_reffile_namebase_ymd
0KCDMIBL21N000000001문화시설공공도서관서울특별시교육청강남도서관서울특별시강남구1168010500삼성동1168059000삼성2동116803122006서울특별시 강남구 선릉로116길 456093다사59946137.513684127.046839교육청공공02-3448-4741http://gnlib.sen.go.kr198210791631338153583888047686513964761919331414002221131763282105311914282756733653655320663320210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
1KCDMIBL21N000001132문화시설공공도서관김해지혜의바다경상남도김해시4825032025주촌면 내삼리4825032000주촌면482505000000경상남도 김해시 주촌면 서부로1541번길 850877마라20294235.236129128.821869교육청[NULL]055-330-9800http://ghjhlib.gne.go.kr201913399344943146553004655300914115100033046203188184118550226139753779160020210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
2KCDMIBL21N000000003문화시설공공도서관서울특별시교육청강동도서관서울특별시강동구1174010500길동1174068500길동117404172235서울특별시 강동구 양재대로116길 575344다사68548837.538083127.143501교육청공공02-2225-9800http://gdlib.sen.go.kr198431963082547187078706968696433052132020331515002211251797876112020114618153149494920227656020210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
3KCDMIBL21N000000004문화시설공공도서관서울특별시교육청고덕평생학습관서울특별시강동구1174010200고덕동1174056000고덕2동117403124001서울특별시 강동구 고덕로 2955225다사69750837.55612127.158039교육청공공02-6902-2600http://gdllc.sen.go.kr1984950738541052168765588372412214491324254413140077311228097651451971184411117338394228733878920210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
4KCDMIBL21N000000005문화시설공공도서관서울특별시교육청강서도서관서울특별시강서구1150010200등촌동1150053000등촌2동115004145312서울특별시 강서구 등촌로51나길 297669다사43450037.547903126.859928교육청공공02-3219-7000http://gslib.sen.go.kr19833576402490025058712383606134416176062828551919004421542814669171062420929589475095943830339020210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
5KCDMIBL21N000000006문화시설공공도서관서울특별시교육청고척도서관서울특별시구로구1153010600고척동1153073000고척2동115304148171서울특별시 구로구 고척로45길 318239다사42845337.505347126.853052교육청공공02-2680-2415http://gclib.sen.go.kr199033055438631237333108285201395963152025255516160044213425257951429094207461889240118698137744320210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
6KCDMIBL21N000000007문화시설공공도서관서울특별시교육청구로도서관서울특별시구로구1153010200구로동1153056000구로5동115303116004서울특별시 구로구 공원로 158298다사46244537.498657126.891544교육청공공02-6958-2800http://grlib.sen.go.kr1984173825385741503479242515967740171919221414003311172133798118035714804280539991108231037420210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
7KCDMIBL21N000001133문화시설공공도서관진주시립서부도서관경상남도진주시4817012700이현동4817072000이현동481703000000경상남도 진주시 평거로 24952669라라51188435.189759128.06173지자체[NULL]055-749-5983http://lib.jinju.go.kr/1998145453782769182977534616490498549920450034033151214359914310696280603832466824135420210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
8KCDMIBL21N000000009문화시설공공도서관서울특별시교육청도봉도서관서울특별시도봉구1132010500쌍문동1132066000쌍문1동113203005041서울특별시 도봉구 삼양로 5561368다사57061537.652547127.012772교육청공공02-6714-7400http://dblib.sen.go.kr1981202427435672256471112756211859470912221221716003301272030674113442517501672123373947932318920210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
9KCDMIBL21N000000010문화시설공공도서관서울특별시교육청동대문도서관서울특별시동대문구1123010100신설동1123053600용신동112304115545서울특별시 동대문구 천호대로4길 222586다사57952837.573857127.024185교육청공공02-2170-1024http://ddmlib.sen.go.kr1971992435266222446312652922125834669222727551818004421272754669158528419494497444171997122559820210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
idlclasmlsfcfclt_namectprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrzip_cdgrid_cdx_cdy_cdestbl_ntpub_privcttpchmpgopnng_yyfcltscl_placefcltscl_buldingfcltscl_chairpsgud_bookpsgud_nobookpsgud_paperpsgud_addbookpsgud_addnobookpsgud_addpaperemp_ntotalemp_totaladmemp_ntotaladmemp_totallbrrnemp_ntotallbrrnemp_totalcmptemp_ntotalcmptemp_totaletcemp_ntotaletcemp_totalcrqfc_1stcrqfc_2stcrqfc_3stwrkbdg_totalwrkbdg_memwrkbdg_dtawrkbdg_etcusemem_totalusebook_totalupdate_datedata_reffile_namebase_ymd
90KCDMIBL21N000000091문화시설공공도서관도봉아이나라도서관서울특별시도봉구1132010700창동1132051400창4동113204127032서울특별시 도봉구 노해로69길 1511411다사60262237.659047127.049507지자체공공02-995-4171http://www.kidlib.dobong.kr2008870149815292307157830591053099226600111526908654070597237721142920323617389920210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
91KCDMIBL21N000000092문화시설공공도서관둘리도서관서울특별시도봉구1132010500쌍문동1132066000쌍문1동113204127254서울특별시 도봉구 시루봉로1길 61376다사58361537.65243127.027638지자체공공070-4291-1112http://www.doolymuseum.or.kr/Contents.asp?code=10001436201556003431001141423120651003322110000010309826116077857618517345873141020210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
92KCDMIBL21N000000093문화시설공공도서관학마을도서관서울특별시도봉구1132010600방학동1132071000방학3동302003167042서울특별시 도봉구 시루봉로 1281359다사58362637.66216127.027832지자체공공02-955-0655http://www.hakmaeul.or.kr/2009383812683846788837716129616017883344001115273617453530351072149799192208778520210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
93KCDMIBL21N000000094문화시설공공도서관동대문구 답십리 도서관서울특별시동대문구1123010500답십리동1123060000답십리1동112304115203서울특별시 동대문구 서울시립대로4길 752596다사60252737.573193127.05036지자체공공02-982-1959https://www.l4d.or.kr/dsn/index.do201488331421936772522931531250329947181912111201640152131049275835716016639196967689623459320210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
94KCDMIBL21N000000095문화시설공공도서관동대문구정보화도서관서울특별시동대문구1123010700청량리동1123070500청량리동112304115684서울특별시 동대문구 회기로10길 602456다사60054637.58997127.04729지자체공공02-960-1959http://www.L4D.or.kr20061161309421413611879942121016117417191922111111552132132474281239815240135994393656319045520210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
95KCDMIBL21N000000096문화시설공공도서관휘경어린이도서관서울특별시동대문구1123010900휘경동1123073000휘경2동112304115118서울특별시 동대문구 망우로18가길 382497다사61254437.588684127.060608지자체공공02-2248-1959www.l4d.or.kr201425730686216731112182996861844113300000031707269341632534447761267915869620210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
96KCDMIBL21N000000097문화시설공공도서관대방어린이도서관서울특별시동작구1159010800대방동1159066000대방동115904157106서울특별시 동작구 대방동길 556945다사49145037.503025126.925223지자체공공02-813-6740http://lib.dongjak.go.kr2014378391522221629813258813832200220000020163793619944182659973700519605820210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
97KCDMIBL21N000000098문화시설공공도서관동작상도국주도서관서울특별시동작구1159010300상도1동1159053000상도1동115903119003서울특별시 동작구 매봉로 376919다사51445437.506821126.950995지자체공공02-813-6750http://lib.dongjak.go.kr/200957452510043471117212302420441133000003036432615990847931996251633127441520210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
98KCDMIBL21N000000099문화시설공공도서관동작어린이도서관서울특별시동작구1159010100노량진동1159052000노량진2동115904157578서울특별시 동작구 장승배기로16길 986926다사50845637.509205126.943432지자체공공02-823-6750http://lib.dongjak.go.kr20081544444130453001149103043004411330000030314960132030443411385891345468346320210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101
99KCDMIBL21N000000100문화시설공공도서관사당솔밭도서관서울특별시동작구1159010700사당동1159065100사당5동115903005079서울특별시 동작구 솔밭로 867019다사52942837.484081126.967351지자체공공02-585-8411http://lib.dongjak.go.kr/2013822172528052299353438421038911015600440705780434052811048126795023022414563620210101문화데이터총람2020KC_476_DMSTC_MCST_IBLLBR_202120200101