Overview

Dataset statistics

Number of variables31
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory131.5 KiB
Average record size in memory269.3 B

Variable types

Text5
Categorical11
Numeric13
Boolean2

Dataset

Description해당 파일 데이터는 신용보증기금의 재물기타에너지절약계획정보에 대해 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15092931/fileData.do

Alerts

유류한도배분용량 has constant value ""Constant
유류사용계획용량 has constant value ""Constant
유류사용실적용량 has constant value ""Constant
유류사용실적금액 has constant value ""Constant
삭제여부 has constant value ""Constant
가스한도배분용량 is highly imbalanced (94.7%)Imbalance
가스사용계획용량 is highly imbalanced (94.7%)Imbalance
수도한도배분용량 is highly imbalanced (97.9%)Imbalance
에너지절약추진계획실적ID has unique valuesUnique
전력한도배분용량 has 484 (96.8%) zerosZeros
전력사용계획용량 has 477 (95.4%) zerosZeros
전력사용실적용량 has 86 (17.2%) zerosZeros
전력사용실적금액 has 82 (16.4%) zerosZeros
가스사용실적용량 has 370 (74.0%) zerosZeros
가스사용실적금액 has 341 (68.2%) zerosZeros
수도사용계획용량 has 491 (98.2%) zerosZeros
수도사용실적용량 has 163 (32.6%) zerosZeros
수도사용실적금액 has 112 (22.4%) zerosZeros
차량유류사용실적용량 has 196 (39.2%) zerosZeros
차량유류사용실적금액 has 175 (35.0%) zerosZeros

Reproduction

Analysis started2023-12-13 00:14:50.557989
Analysis finished2023-12-13 00:14:50.892804
Duration0.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

에너지절약추진계획실적ID
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T09:14:51.048343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters5000
Distinct characters62
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique500 ?
Unique (%)100.0%

Sample

1st row9dlF8OGYBk
2nd row9dnSYKi9h0
3rd row9djoIuIV3Z
4th row9dmmoaw3zN
5th row9dixu6JDmb
ValueCountFrequency (%)
9dlf8ogybk 1
 
0.2%
9dlt7yvdh5 1
 
0.2%
9dhzidyvfk 1
 
0.2%
9dlc95hupo 1
 
0.2%
9disglgnjd 1
 
0.2%
9dhgoi3tfo 1
 
0.2%
9c2dffpq8z 1
 
0.2%
9dimppz2gt 1
 
0.2%
9djyyyj6wq 1
 
0.2%
9djyyykbmp 1
 
0.2%
Other values (490) 490
98.0%
2023-12-13T09:14:51.354810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 593
 
11.9%
d 512
 
10.2%
c 132
 
2.6%
i 126
 
2.5%
k 123
 
2.5%
j 117
 
2.3%
l 114
 
2.3%
m 114
 
2.3%
h 99
 
2.0%
0 88
 
1.8%
Other values (52) 2982
59.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2402
48.0%
Uppercase Letter 1400
28.0%
Decimal Number 1198
24.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 512
21.3%
c 132
 
5.5%
i 126
 
5.2%
k 123
 
5.1%
j 117
 
4.9%
l 114
 
4.7%
m 114
 
4.7%
h 99
 
4.1%
e 82
 
3.4%
t 76
 
3.2%
Other values (16) 907
37.8%
Uppercase Letter
ValueCountFrequency (%)
V 68
 
4.9%
U 62
 
4.4%
Y 62
 
4.4%
I 62
 
4.4%
M 61
 
4.4%
P 61
 
4.4%
A 59
 
4.2%
S 58
 
4.1%
Q 58
 
4.1%
J 57
 
4.1%
Other values (16) 792
56.6%
Decimal Number
ValueCountFrequency (%)
9 593
49.5%
0 88
 
7.3%
8 82
 
6.8%
3 79
 
6.6%
2 68
 
5.7%
5 67
 
5.6%
1 64
 
5.3%
4 61
 
5.1%
7 56
 
4.7%
6 40
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 3802
76.0%
Common 1198
 
24.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 512
 
13.5%
c 132
 
3.5%
i 126
 
3.3%
k 123
 
3.2%
j 117
 
3.1%
l 114
 
3.0%
m 114
 
3.0%
h 99
 
2.6%
e 82
 
2.2%
t 76
 
2.0%
Other values (42) 2307
60.7%
Common
ValueCountFrequency (%)
9 593
49.5%
0 88
 
7.3%
8 82
 
6.8%
3 79
 
6.6%
2 68
 
5.7%
5 67
 
5.6%
1 64
 
5.3%
4 61
 
5.1%
7 56
 
4.7%
6 40
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 593
 
11.9%
d 512
 
10.2%
c 132
 
2.6%
i 126
 
2.5%
k 123
 
2.5%
j 117
 
2.3%
l 114
 
2.3%
m 114
 
2.3%
h 99
 
2.0%
0 88
 
1.8%
Other values (52) 2982
59.6%

추진년도
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2021
345 
2020
154 
2019
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 345
69.0%
2020 154
30.8%
2019 1
 
0.2%

Length

2023-12-13T09:14:51.459328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:14:51.527139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 345
69.0%
2020 154
30.8%
2019 1
 
0.2%

추진월
Real number (ℝ)

Distinct12
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.338
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T09:14:51.596975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q38
95-th percentile11
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.0781009
Coefficient of variation (CV)0.57663937
Kurtosis-0.77353462
Mean5.338
Median Absolute Deviation (MAD)2
Skewness0.37376656
Sum2669
Variance9.4747054
MonotonicityNot monotonic
2023-12-13T09:14:51.681410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 58
11.6%
2 54
10.8%
4 54
10.8%
5 54
10.8%
6 53
10.6%
3 53
10.6%
7 47
9.4%
8 39
7.8%
9 34
6.8%
10 19
 
3.8%
Other values (2) 35
7.0%
ValueCountFrequency (%)
1 58
11.6%
2 54
10.8%
3 53
10.6%
4 54
10.8%
5 54
10.8%
6 53
10.6%
7 47
9.4%
8 39
7.8%
9 34
6.8%
10 19
 
3.8%
ValueCountFrequency (%)
12 18
 
3.6%
11 17
 
3.4%
10 19
 
3.8%
9 34
6.8%
8 39
7.8%
7 47
9.4%
6 53
10.6%
5 54
10.8%
4 54
10.8%
3 53
10.6%

단독소유건물여부
Boolean

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
365 
True
135 
ValueCountFrequency (%)
False 365
73.0%
True 135
 
27.0%
2023-12-13T09:14:51.758177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

담당자직원번호
Text

Distinct68
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T09:14:51.932541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.106
Min length4

Characters and Unicode

Total characters2053
Distinct characters11
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

Unique8 ?
Unique (%)1.6%

Sample

1st row3191
2nd row3191
3rd row3191
4th row3191
5th row3191
ValueCountFrequency (%)
9a053 22
 
4.4%
9a017 21
 
4.2%
4548 21
 
4.2%
4175 13
 
2.6%
5888 13
 
2.6%
5239 13
 
2.6%
5749 13
 
2.6%
5889 12
 
2.4%
6081 12
 
2.4%
5845 12
 
2.4%
Other values (58) 348
69.6%
2023-12-13T09:14:52.219569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 446
21.7%
9 224
10.9%
4 221
10.8%
8 212
10.3%
0 209
10.2%
6 189
9.2%
7 138
 
6.7%
1 132
 
6.4%
3 115
 
5.6%
2 114
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2000
97.4%
Uppercase Letter 53
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 446
22.3%
9 224
11.2%
4 221
11.1%
8 212
10.6%
0 209
10.4%
6 189
9.4%
7 138
 
6.9%
1 132
 
6.6%
3 115
 
5.8%
2 114
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
A 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2000
97.4%
Latin 53
 
2.6%

Most frequent character per script

Common
ValueCountFrequency (%)
5 446
22.3%
9 224
11.2%
4 221
11.1%
8 212
10.6%
0 209
10.4%
6 189
9.4%
7 138
 
6.9%
1 132
 
6.6%
3 115
 
5.8%
2 114
 
5.7%
Latin
ValueCountFrequency (%)
A 53
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2053
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 446
21.7%
9 224
10.9%
4 221
10.8%
8 212
10.3%
0 209
10.2%
6 189
9.2%
7 138
 
6.7%
1 132
 
6.4%
3 115
 
5.6%
2 114
 
5.6%

전력한도배분용량
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2112.8
Minimum0
Maximum304900
Zeros484
Zeros (%)96.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T09:14:52.315836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum304900
Range304900
Interquartile range (IQR)0

Descriptive statistics

Standard deviation23878.33
Coefficient of variation (CV)11.301747
Kurtosis154.62641
Mean2112.8
Median Absolute Deviation (MAD)0
Skewness12.397673
Sum1056400
Variance5.7017467 × 108
MonotonicityNot monotonic
2023-12-13T09:14:52.391860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 484
96.8%
4000 5
 
1.0%
5500 3
 
0.6%
304900 3
 
0.6%
5000 2
 
0.4%
87200 1
 
0.2%
4500 1
 
0.2%
3500 1
 
0.2%
ValueCountFrequency (%)
0 484
96.8%
3500 1
 
0.2%
4000 5
 
1.0%
4500 1
 
0.2%
5000 2
 
0.4%
5500 3
 
0.6%
87200 1
 
0.2%
304900 3
 
0.6%
ValueCountFrequency (%)
304900 3
 
0.6%
87200 1
 
0.2%
5500 3
 
0.6%
5000 2
 
0.4%
4500 1
 
0.2%
4000 5
 
1.0%
3500 1
 
0.2%
0 484
96.8%

전력사용계획용량
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean389.4
Minimum0
Maximum25400
Zeros477
Zeros (%)95.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T09:14:52.481669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum25400
Range25400
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2307.8388
Coefficient of variation (CV)5.9266533
Kurtosis84.062874
Mean389.4
Median Absolute Deviation (MAD)0
Skewness8.5376011
Sum194700
Variance5326119.9
MonotonicityNot monotonic
2023-12-13T09:14:52.562189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 477
95.4%
4000 5
 
1.0%
5500 3
 
0.6%
25400 3
 
0.6%
5000 2
 
0.4%
5600 1
 
0.2%
7000 1
 
0.2%
9100 1
 
0.2%
9600 1
 
0.2%
12000 1
 
0.2%
Other values (5) 5
 
1.0%
ValueCountFrequency (%)
0 477
95.4%
3500 1
 
0.2%
4000 5
 
1.0%
4500 1
 
0.2%
5000 2
 
0.4%
5500 3
 
0.6%
5600 1
 
0.2%
6000 1
 
0.2%
6500 1
 
0.2%
7000 1
 
0.2%
ValueCountFrequency (%)
25400 3
0.6%
12000 1
 
0.2%
9600 1
 
0.2%
9100 1
 
0.2%
8200 1
 
0.2%
7000 1
 
0.2%
6500 1
 
0.2%
6000 1
 
0.2%
5600 1
 
0.2%
5500 3
0.6%

전력사용실적용량
Real number (ℝ)

ZEROS 

Distinct409
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22490.945
Minimum0
Maximum435684
Zeros86
Zeros (%)17.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T09:14:52.656646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11862.25
median6046
Q316148.25
95-th percentile54145.8
Maximum435684
Range435684
Interquartile range (IQR)14286

Descriptive statistics

Standard deviation64655.45
Coefficient of variation (CV)2.8747325
Kurtosis20.932969
Mean22490.945
Median Absolute Deviation (MAD)5847
Skewness4.6563968
Sum11245472
Variance4.1803272 × 109
MonotonicityNot monotonic
2023-12-13T09:14:52.757489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 86
 
17.2%
994.0 2
 
0.4%
1000.0 2
 
0.4%
3332.0 2
 
0.4%
4608.0 2
 
0.4%
11883.0 2
 
0.4%
1842.0 2
 
0.4%
14206.0 1
 
0.2%
1012.0 1
 
0.2%
8928.0 1
 
0.2%
Other values (399) 399
79.8%
ValueCountFrequency (%)
0.0 86
17.2%
799.0 1
 
0.2%
873.0 1
 
0.2%
888.0 1
 
0.2%
895.0 1
 
0.2%
922.0 1
 
0.2%
941.0 1
 
0.2%
944.0 1
 
0.2%
994.0 2
 
0.4%
995.0 1
 
0.2%
ValueCountFrequency (%)
435684.0 1
0.2%
399654.0 1
0.2%
393941.0 1
0.2%
369033.0 1
0.2%
365742.0 1
0.2%
357102.0 1
0.2%
344865.0 1
0.2%
343960.0 1
0.2%
342077.0 1
0.2%
338957.0 1
0.2%

전력사용실적금액
Real number (ℝ)

ZEROS 

Distinct419
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3744697.3
Minimum0
Maximum72787140
Zeros82
Zeros (%)16.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T09:14:52.858717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1299470
median1266906
Q33010165
95-th percentile8050181
Maximum72787140
Range72787140
Interquartile range (IQR)2710695

Descriptive statistics

Standard deviation10047000
Coefficient of variation (CV)2.682994
Kurtosis23.518677
Mean3744697.3
Median Absolute Deviation (MAD)1085705.5
Skewness4.8272126
Sum1.8723486 × 109
Variance1.0094221 × 1014
MonotonicityNot monotonic
2023-12-13T09:14:52.969081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 82
 
16.4%
1207060 1
 
0.2%
334842 1
 
0.2%
388185 1
 
0.2%
269982 1
 
0.2%
275907 1
 
0.2%
1880930 1
 
0.2%
3023410 1
 
0.2%
1665480 1
 
0.2%
2316310 1
 
0.2%
Other values (409) 409
81.8%
ValueCountFrequency (%)
0 82
16.4%
47520 1
 
0.2%
77330 1
 
0.2%
83204 1
 
0.2%
97600 1
 
0.2%
109680 1
 
0.2%
127710 1
 
0.2%
136880 1
 
0.2%
141570 1
 
0.2%
156781 1
 
0.2%
ValueCountFrequency (%)
72787140 1
0.2%
68761980 1
0.2%
66474900 1
0.2%
62620760 1
0.2%
60576380 1
0.2%
59145260 1
0.2%
54948990 1
0.2%
53554250 1
0.2%
53500410 1
0.2%
50820790 1
0.2%

유류한도배분용량
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

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 (%)
0 500
100.0%

Length

2023-12-13T09:14:53.069319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:14:53.132843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

유류사용계획용량
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

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 (%)
0 500
100.0%

Length

2023-12-13T09:14:53.208104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:14:53.274200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

유류사용실적용량
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

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 (%)
0 500
100.0%

Length

2023-12-13T09:14:53.342981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:14:53.408434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

유류사용실적금액
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

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 (%)
0 500
100.0%

Length

2023-12-13T09:14:53.474805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:14:53.537821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

가스한도배분용량
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
497 
6510
 
3

Length

Max length4
Median length1
Mean length1.018
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 497
99.4%
6510 3
 
0.6%

Length

2023-12-13T09:14:53.612209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:14:53.683567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 497
99.4%
6510 3
 
0.6%

가스사용계획용량
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
497 
540
 
3

Length

Max length3
Median length1
Mean length1.012
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 497
99.4%
540 3
 
0.6%

Length

2023-12-13T09:14:53.762876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:14:54.055214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 497
99.4%
540 3
 
0.6%

가스사용실적용량
Real number (ℝ)

ZEROS 

Distinct119
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90.84046
Minimum0
Maximum5169.11
Zeros370
Zeros (%)74.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T09:14:54.145010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.69
95-th percentile564.75
Maximum5169.11
Range5169.11
Interquartile range (IQR)0.69

Descriptive statistics

Standard deviation443.40054
Coefficient of variation (CV)4.8810909
Kurtosis85.740402
Mean90.84046
Median Absolute Deviation (MAD)0
Skewness8.7484759
Sum45420.23
Variance196604.04
MonotonicityNot monotonic
2023-12-13T09:14:54.247759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 370
74.0%
1.07 3
 
0.6%
8.82 3
 
0.6%
126.0 3
 
0.6%
1.59 2
 
0.4%
1.95 2
 
0.4%
80.0 2
 
0.4%
8.48 2
 
0.4%
7.46 2
 
0.4%
564.75 2
 
0.4%
Other values (109) 109
 
21.8%
ValueCountFrequency (%)
0.0 370
74.0%
0.12 1
 
0.2%
0.14 1
 
0.2%
0.28 1
 
0.2%
0.56 1
 
0.2%
0.67 1
 
0.2%
0.75 1
 
0.2%
0.96 1
 
0.2%
1.03 1
 
0.2%
1.07 3
 
0.6%
ValueCountFrequency (%)
5169.11 1
0.2%
4785.53 1
0.2%
4200.76 1
0.2%
3992.55 1
0.2%
2047.53 1
0.2%
1653.85 1
0.2%
1042.23 1
0.2%
816.41 1
0.2%
716.34 1
0.2%
699.08 1
0.2%

가스사용실적금액
Real number (ℝ)

ZEROS 

Distinct150
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83792.544
Minimum0
Maximum3750500
Zeros341
Zeros (%)68.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T09:14:54.349838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37186.5
95-th percentile438241
Maximum3750500
Range3750500
Interquartile range (IQR)7186.5

Descriptive statistics

Standard deviation340382.88
Coefficient of variation (CV)4.0622097
Kurtosis60.253335
Mean83792.544
Median Absolute Deviation (MAD)0
Skewness7.2502396
Sum41896272
Variance1.1586051 × 1011
MonotonicityNot monotonic
2023-12-13T09:14:54.469370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 341
68.2%
1230 11
 
2.2%
494050 1
 
0.2%
568060 1
 
0.2%
437910 1
 
0.2%
567760 1
 
0.2%
497950 1
 
0.2%
396840 1
 
0.2%
458520 1
 
0.2%
496400 1
 
0.2%
Other values (140) 140
28.0%
ValueCountFrequency (%)
0 341
68.2%
296 1
 
0.2%
701 1
 
0.2%
754 1
 
0.2%
1230 11
 
2.2%
1796 1
 
0.2%
2422 1
 
0.2%
2550 1
 
0.2%
3860 1
 
0.2%
5145 1
 
0.2%
ValueCountFrequency (%)
3750500 1
0.2%
3139167 1
0.2%
3025140 1
0.2%
2360350 1
0.2%
2291421 1
0.2%
1914620 1
0.2%
1695203 1
0.2%
1670640 1
0.2%
787600 1
0.2%
732190 1
0.2%

수도한도배분용량
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
499 
460
 
1

Length

Max length3
Median length1
Mean length1.004
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 499
99.8%
460 1
 
0.2%

Length

2023-12-13T09:14:54.590216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:14:54.669215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 499
99.8%
460 1
 
0.2%

수도사용계획용량
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.516
Minimum0
Maximum65
Zeros491
Zeros (%)98.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T09:14:54.728026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum65
Range65
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.2067967
Coefficient of variation (CV)8.1527067
Kurtosis126.9082
Mean0.516
Median Absolute Deviation (MAD)0
Skewness10.250811
Sum258
Variance17.697138
MonotonicityNot monotonic
2023-12-13T09:14:54.812503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 491
98.2%
20 2
 
0.4%
25 2
 
0.4%
65 1
 
0.2%
27 1
 
0.2%
24 1
 
0.2%
30 1
 
0.2%
22 1
 
0.2%
ValueCountFrequency (%)
0 491
98.2%
20 2
 
0.4%
22 1
 
0.2%
24 1
 
0.2%
25 2
 
0.4%
27 1
 
0.2%
30 1
 
0.2%
65 1
 
0.2%
ValueCountFrequency (%)
65 1
 
0.2%
30 1
 
0.2%
27 1
 
0.2%
25 2
 
0.4%
24 1
 
0.2%
22 1
 
0.2%
20 2
 
0.4%
0 491
98.2%

수도사용실적용량
Real number (ℝ)

ZEROS 

Distinct192
Distinct (%)38.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.68194
Minimum0
Maximum1418
Zeros163
Zeros (%)32.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T09:14:54.907862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median27.88
Q372
95-th percentile270.3
Maximum1418
Range1418
Interquartile range (IQR)72

Descriptive statistics

Standard deviation159.91495
Coefficient of variation (CV)2.1703412
Kurtosis24.990106
Mean73.68194
Median Absolute Deviation (MAD)27.88
Skewness4.630332
Sum36840.97
Variance25572.792
MonotonicityNot monotonic
2023-12-13T09:14:55.010538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 163
32.6%
48.0 8
 
1.6%
29.0 7
 
1.4%
56.0 6
 
1.2%
2.0 6
 
1.2%
26.0 6
 
1.2%
28.0 6
 
1.2%
25.0 6
 
1.2%
70.0 6
 
1.2%
65.0 5
 
1.0%
Other values (182) 281
56.2%
ValueCountFrequency (%)
0.0 163
32.6%
1.0 1
 
0.2%
2.0 6
 
1.2%
11.0 1
 
0.2%
12.0 3
 
0.6%
12.71 1
 
0.2%
12.87 1
 
0.2%
13.0 1
 
0.2%
13.06 1
 
0.2%
13.14 1
 
0.2%
ValueCountFrequency (%)
1418.0 1
0.2%
1180.0 1
0.2%
1094.0 1
0.2%
906.0 1
0.2%
879.0 1
0.2%
838.0 1
0.2%
821.0 1
0.2%
820.0 1
0.2%
807.0 1
0.2%
731.0 1
0.2%

수도사용실적금액
Real number (ℝ)

ZEROS 

Distinct357
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean164804.6
Minimum0
Maximum4030100
Zeros112
Zeros (%)22.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T09:14:55.122812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13892.5
median54209.5
Q3140358
95-th percentile381402.5
Maximum4030100
Range4030100
Interquartile range (IQR)136465.5

Descriptive statistics

Standard deviation432672.2
Coefficient of variation (CV)2.6253647
Kurtosis31.836573
Mean164804.6
Median Absolute Deviation (MAD)54209.5
Skewness5.3694635
Sum82402302
Variance1.8720523 × 1011
MonotonicityNot monotonic
2023-12-13T09:14:55.236358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 112
 
22.4%
2000 9
 
1.8%
25264 3
 
0.6%
35816 3
 
0.6%
33609 3
 
0.6%
328150 3
 
0.6%
49710 2
 
0.4%
187800 2
 
0.4%
52084 2
 
0.4%
236950 2
 
0.4%
Other values (347) 359
71.8%
ValueCountFrequency (%)
0 112
22.4%
1855 1
 
0.2%
2000 9
 
1.8%
3640 2
 
0.4%
3870 1
 
0.2%
3900 1
 
0.2%
3950 1
 
0.2%
10275 1
 
0.2%
13200 1
 
0.2%
19333 1
 
0.2%
ValueCountFrequency (%)
4030100 1
0.2%
3337730 1
0.2%
3087550 1
0.2%
2540640 1
0.2%
2462090 1
0.2%
2341140 1
0.2%
2293370 1
0.2%
2288820 1
0.2%
2252640 1
0.2%
2031550 1
0.2%

차량유류사용실적용량
Real number (ℝ)

ZEROS 

Distinct256
Distinct (%)51.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean781.11604
Minimum0
Maximum102443
Zeros196
Zeros (%)39.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T09:14:55.378859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median44.135
Q388.025
95-th percentile147.625
Maximum102443
Range102443
Interquartile range (IQR)88.025

Descriptive statistics

Standard deviation7807.4978
Coefficient of variation (CV)9.9953111
Kurtosis134.9704
Mean781.11604
Median Absolute Deviation (MAD)44.135
Skewness11.453802
Sum390558.02
Variance60957022
MonotonicityNot monotonic
2023-12-13T09:14:55.508295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 196
39.2%
50.0 5
 
1.0%
40.0 5
 
1.0%
45.0 5
 
1.0%
88.0 4
 
0.8%
100.0 4
 
0.8%
93.0 4
 
0.8%
48.0 4
 
0.8%
42.0 3
 
0.6%
85.0 3
 
0.6%
Other values (246) 267
53.4%
ValueCountFrequency (%)
0.0 196
39.2%
13.0 1
 
0.2%
16.28 1
 
0.2%
22.71 1
 
0.2%
25.0 1
 
0.2%
28.0 1
 
0.2%
28.18 1
 
0.2%
31.0 2
 
0.4%
31.11 1
 
0.2%
32.0 1
 
0.2%
ValueCountFrequency (%)
102443.0 1
0.2%
94074.0 1
0.2%
90774.0 1
0.2%
42354.0 1
0.2%
36631.0 1
0.2%
323.0 1
0.2%
288.68 1
0.2%
237.26 1
0.2%
225.05 1
0.2%
204.71 1
0.2%

차량유류사용실적금액
Real number (ℝ)

ZEROS 

Distinct158
Distinct (%)31.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74647.962
Minimum0
Maximum358000
Zeros175
Zeros (%)35.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T09:14:55.606574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median68000
Q3130000
95-th percentile196150
Maximum358000
Range358000
Interquartile range (IQR)130000

Descriptive statistics

Standard deviation71210.123
Coefficient of variation (CV)0.95394598
Kurtosis0.26051885
Mean74647.962
Median Absolute Deviation (MAD)68000
Skewness0.757248
Sum37323981
Variance5.0708817 × 109
MonotonicityNot monotonic
2023-12-13T09:14:55.712698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 175
35.0%
70000 21
 
4.2%
60000 15
 
3.0%
50000 10
 
2.0%
120000 9
 
1.8%
130000 8
 
1.6%
66000 7
 
1.4%
68000 7
 
1.4%
140000 7
 
1.4%
80000 7
 
1.4%
Other values (148) 234
46.8%
ValueCountFrequency (%)
0 175
35.0%
13304 1
 
0.2%
27973 1
 
0.2%
30000 1
 
0.2%
35420 1
 
0.2%
36761 1
 
0.2%
40000 1
 
0.2%
44000 1
 
0.2%
44051 1
 
0.2%
46368 1
 
0.2%
ValueCountFrequency (%)
358000 1
0.2%
330000 1
0.2%
321000 1
0.2%
302000 1
0.2%
288000 1
0.2%
280000 1
0.2%
261000 1
0.2%
253000 1
0.2%
239000 2
0.4%
231000 2
0.4%

교육실시일자
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
254 
00:00.0
246 

Length

Max length26
Median length26
Mean length16.652
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0001-01-01 00:00:00.000000
2nd row0001-01-01 00:00:00.000000
3rd row0001-01-01 00:00:00.000000
4th row0001-01-01 00:00:00.000000
5th row0001-01-01 00:00:00.000000

Common Values

ValueCountFrequency (%)
0001-01-01 00:00:00.000000 254
50.8%
00:00.0 246
49.2%

Length

2023-12-13T09:14:55.813631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:14:55.886953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 254
33.7%
00:00:00.000000 254
33.7%
00:00.0 246
32.6%

교육강사직원번호
Categorical

Distinct45
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
257 
4175
 
13
5749
 
13
5845
 
11
2529
 
10
Other values (40)
196 

Length

Max length5
Median length4
Mean length4.018
Min length4

Unique

Unique7 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 257
51.4%
4175 13
 
2.6%
5749 13
 
2.6%
5845 11
 
2.2%
2529 10
 
2.0%
5557 9
 
1.8%
5725 9
 
1.8%
9A054 9
 
1.8%
4548 8
 
1.6%
5239 8
 
1.6%
Other values (35) 153
30.6%

Length

2023-12-13T09:14:55.962764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 257
51.4%
5749 13
 
2.6%
4175 13
 
2.6%
5845 11
 
2.2%
2529 10
 
2.0%
5557 9
 
1.8%
5725 9
 
1.8%
9a054 9
 
1.8%
6054 8
 
1.6%
5239 8
 
1.6%
Other values (35) 153
30.6%

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
500 
ValueCountFrequency (%)
False 500
100.0%
2023-12-13T09:14:56.029669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최종수정수
Real number (ℝ)

Distinct50
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.488
Minimum2
Maximum63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T09:14:56.109293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q17
median13
Q322
95-th percentile42.15
Maximum63
Range61
Interquartile range (IQR)15

Descriptive statistics

Standard deviation13.006313
Coefficient of variation (CV)0.78883511
Kurtosis2.9153036
Mean16.488
Median Absolute Deviation (MAD)7
Skewness1.6318062
Sum8244
Variance169.16418
MonotonicityNot monotonic
2023-12-13T09:14:56.213364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 33
 
6.6%
4 30
 
6.0%
11 28
 
5.6%
7 25
 
5.0%
5 23
 
4.6%
3 21
 
4.2%
8 20
 
4.0%
17 19
 
3.8%
6 19
 
3.8%
12 17
 
3.4%
Other values (40) 265
53.0%
ValueCountFrequency (%)
2 15
3.0%
3 21
4.2%
4 30
6.0%
5 23
4.6%
6 19
3.8%
7 25
5.0%
8 20
4.0%
9 33
6.6%
10 13
 
2.6%
11 28
5.6%
ValueCountFrequency (%)
63 1
 
0.2%
62 2
 
0.4%
61 4
0.8%
60 3
0.6%
59 3
0.6%
58 5
1.0%
57 2
 
0.4%
56 1
 
0.2%
53 1
 
0.2%
47 2
 
0.4%

처리시각
Text

Distinct84
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T09:14:56.393585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3500
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)5.8%

Sample

1st row07:40.8
2nd row07:40.8
3rd row07:40.8
4th row07:40.8
5th row07:40.8
ValueCountFrequency (%)
04:28.3 12
 
2.4%
29:46.1 12
 
2.4%
45:26.3 12
 
2.4%
55:17.5 12
 
2.4%
42:19.1 12
 
2.4%
55:24.1 12
 
2.4%
31:56.0 12
 
2.4%
57:03.2 12
 
2.4%
11:22.4 12
 
2.4%
51:23.2 12
 
2.4%
Other values (74) 380
76.0%
2023-12-13T09:14:56.656918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
1 379
10.8%
2 364
10.4%
3 328
9.4%
5 322
9.2%
0 302
8.6%
4 300
8.6%
6 164
 
4.7%
7 144
 
4.1%
Other values (2) 197
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2500
71.4%
Other Punctuation 1000
 
28.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 379
15.2%
2 364
14.6%
3 328
13.1%
5 322
12.9%
0 302
12.1%
4 300
12.0%
6 164
6.6%
7 144
 
5.8%
8 113
 
4.5%
9 84
 
3.4%
Other Punctuation
ValueCountFrequency (%)
: 500
50.0%
. 500
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
1 379
10.8%
2 364
10.4%
3 328
9.4%
5 322
9.2%
0 302
8.6%
4 300
8.6%
6 164
 
4.7%
7 144
 
4.1%
Other values (2) 197
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
1 379
10.8%
2 364
10.4%
3 328
9.4%
5 322
9.2%
0 302
8.6%
4 300
8.6%
6 164
 
4.7%
7 144
 
4.1%
Other values (2) 197
 
5.6%

처리직원번호
Categorical

Distinct44
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
5239
45 
9A053
 
22
9A071
 
22
9A015
 
22
9A011
 
21
Other values (39)
368 

Length

Max length5
Median length4
Mean length4.454
Min length4

Unique

Unique3 ?
Unique (%)0.6%

Sample

1st row3191
2nd row3191
3rd row3191
4th row3191
5th row3191

Common Values

ValueCountFrequency (%)
5239 45
 
9.0%
9A053 22
 
4.4%
9A071 22
 
4.4%
9A015 22
 
4.4%
9A011 21
 
4.2%
9A017 21
 
4.2%
9A042 20
 
4.0%
9A043 20
 
4.0%
5942 19
 
3.8%
5463 18
 
3.6%
Other values (34) 270
54.0%

Length

2023-12-13T09:14:56.759298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5239 45
 
9.0%
9a053 22
 
4.4%
9a071 22
 
4.4%
9a015 22
 
4.4%
9a011 21
 
4.2%
9a017 21
 
4.2%
9a042 20
 
4.0%
9a043 20
 
4.0%
5942 19
 
3.8%
5463 18
 
3.6%
Other values (34) 270
54.0%

최초처리시각
Text

Distinct382
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T09:14:57.058732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3500
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique336 ?
Unique (%)67.2%

Sample

1st row07:31.6
2nd row07:37.7
3rd row45:03.8
4th row42:06.2
5th row07:07.2
ValueCountFrequency (%)
23:26.6 12
 
2.4%
08:52.1 12
 
2.4%
12:53.5 12
 
2.4%
45:16.0 12
 
2.4%
04:50.7 11
 
2.2%
45:56.0 7
 
1.4%
34:37.6 6
 
1.2%
56:21.9 5
 
1.0%
39:10.6 4
 
0.8%
51:56.7 4
 
0.8%
Other values (372) 415
83.0%
2023-12-13T09:14:57.475314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
5 378
10.8%
2 325
9.3%
0 313
8.9%
3 303
8.7%
1 299
8.5%
4 277
7.9%
6 184
 
5.3%
7 157
 
4.5%
Other values (2) 264
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2500
71.4%
Other Punctuation 1000
 
28.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 378
15.1%
2 325
13.0%
0 313
12.5%
3 303
12.1%
1 299
12.0%
4 277
11.1%
6 184
7.4%
7 157
6.3%
9 141
 
5.6%
8 123
 
4.9%
Other Punctuation
ValueCountFrequency (%)
: 500
50.0%
. 500
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
5 378
10.8%
2 325
9.3%
0 313
8.9%
3 303
8.7%
1 299
8.5%
4 277
7.9%
6 184
 
5.3%
7 157
 
4.5%
Other values (2) 264
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
5 378
10.8%
2 325
9.3%
0 313
8.9%
3 303
8.7%
1 299
8.5%
4 277
7.9%
6 184
 
5.3%
7 157
 
4.5%
Other values (2) 264
7.5%

최초처리직원번호
Text

Distinct61
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T09:14:57.663779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.494
Min length4

Characters and Unicode

Total characters2247
Distinct characters11
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

Unique11 ?
Unique (%)2.2%

Sample

1st row3191
2nd row3191
3rd row3191
4th row3191
5th row3191
ValueCountFrequency (%)
9a053 22
 
4.4%
9a015 22
 
4.4%
9a071 22
 
4.4%
9a017 21
 
4.2%
9a011 21
 
4.2%
9a039 20
 
4.0%
9a042 20
 
4.0%
9a043 20
 
4.0%
5942 18
 
3.6%
5239 15
 
3.0%
Other values (51) 299
59.8%
2023-12-13T09:14:57.972553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 413
18.4%
0 354
15.8%
5 263
11.7%
A 247
11.0%
1 201
8.9%
4 171
7.6%
3 152
 
6.8%
6 122
 
5.4%
2 115
 
5.1%
8 108
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2000
89.0%
Uppercase Letter 247
 
11.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 413
20.6%
0 354
17.7%
5 263
13.2%
1 201
10.1%
4 171
8.6%
3 152
 
7.6%
6 122
 
6.1%
2 115
 
5.8%
8 108
 
5.4%
7 101
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
A 247
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2000
89.0%
Latin 247
 
11.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 413
20.6%
0 354
17.7%
5 263
13.2%
1 201
10.1%
4 171
8.6%
3 152
 
7.6%
6 122
 
6.1%
2 115
 
5.8%
8 108
 
5.4%
7 101
 
5.1%
Latin
ValueCountFrequency (%)
A 247
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2247
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 413
18.4%
0 354
15.8%
5 263
11.7%
A 247
11.0%
1 201
8.9%
4 171
7.6%
3 152
 
6.8%
6 122
 
5.4%
2 115
 
5.1%
8 108
 
4.8%

Sample

에너지절약추진계획실적ID추진년도추진월단독소유건물여부담당자직원번호전력한도배분용량전력사용계획용량전력사용실적용량전력사용실적금액유류한도배분용량유류사용계획용량유류사용실적용량유류사용실적금액가스한도배분용량가스사용계획용량가스사용실적용량가스사용실적금액수도한도배분용량수도사용계획용량수도사용실적용량수도사용실적금액차량유류사용실적용량차량유류사용실적금액교육실시일자교육강사직원번호삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
09dlF8OGYBk20216N31910012477.022959500000000.0000147.01921600.000001-01-01 00:00:00.000000<NA>N1307:40.8319107:31.63191
19dnSYKi9h020219N3191000.000000000.0000145.01897400.000001-01-01 00:00:00.000000<NA>N307:40.8319107:37.73191
29djoIuIV3Z20213N31910015185.020934500000000.0000250.03166900.000001-01-01 00:00:00.000000<NA>N2007:40.8319145:03.83191
39dmmoaw3zN20217N31910018257.028957200000000.0000276.03481200.000001-01-01 00:00:00.000000<NA>N907:40.8319142:06.23191
49dixu6JDmb20212N31910017160.024985800000000.0000255.03227300.000001-01-01 00:00:00.000000<NA>N2407:40.8319107:07.23191
59dj3Ive5gE20214N31910012729.019098500000000.0000243.03082200.000001-01-01 00:00:00.000000<NA>N2007:40.8319138:41.23191
69dkP8b35rM20215N31910011165.018991300000000.0000212.02707500.000001-01-01 00:00:00.000000<NA>N1607:40.8319131:08.53191
79dnfe4uqJ020218N31910015137.024344800000000.0000406.05201200.000001-01-01 00:00:00.000000<NA>N507:40.8319110:04.63191
89dhTEr0xSb20211N31910020517.030057500000000.0000258.03263500.000001-01-01 00:00:00.000000<NA>N2507:40.8319122:57.33191
99dhc12N5af202110N2529000.000000000.00000.000.0000:00.02529N5338:43.4252956:21.92529
에너지절약추진계획실적ID추진년도추진월단독소유건물여부담당자직원번호전력한도배분용량전력사용계획용량전력사용실적용량전력사용실적금액유류한도배분용량유류사용계획용량유류사용실적용량유류사용실적금액가스한도배분용량가스사용계획용량가스사용실적용량가스사용실적금액수도한도배분용량수도사용계획용량수도사용실적용량수도사용실적금액차량유류사용실적용량차량유류사용실적금액교육실시일자교육강사직원번호삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
4909ddt29YmIj20208N4548004180.09652800000000.000048.01078300.000001-01-01 00:00:00.000000<NA>N1229:46.19A07132:29.59A071
4919dbUGVmBgG20206N4548004129.09002700000000.000056.0732800.000001-01-01 00:00:00.000000<NA>N1729:46.19A07125:55.99A071
4929c8c8BSTtC20201N540200994.02292770000000.0309270000.021305108.217700000:00.05402N2314:50.19A05834:25.65402
4939dbQemsnH620205N575600922.02073150000000.053263000.02305775.371080000001-01-01 00:00:00.000000<NA>N1114:50.19A05803:07.49A058
4949c9Aen5oZ620202N5756001048.02269110000000.0275798000.02428466.451100000001-01-01 00:00:00.000000<NA>N1514:50.19A05809:38.59A058
4959ddym0pFuA20207N5756001017.02413400000000.0154339000.02785448.71700000001-01-01 00:00:00.000000<NA>N914:50.19A05842:11.99A058
4969deOcOqlZ320209N575600799.01567810000000.099267000.06125448.37700000001-01-01 00:00:00.000000<NA>N514:50.19A05846:51.89A058
4979dd5666AwV20208N575600873.01825190000000.0159022000.04136484.461260000001-01-01 00:00:00.000000<NA>N614:50.19A05806:20.59A058
4989dg5HqoSbe202012N5756001078.02312990000000.0366033000.01933394074.01370000001-01-01 00:00:00.000000<NA>N214:50.19A05814:50.19A058
4999da0n9r6El20204N575600895.01798820000000.051242000.023398109.661610000001-01-01 00:00:00.000000<NA>N1214:50.19A05805:44.49A058