Overview

Dataset statistics

Number of variables28
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory238.7 B

Variable types

Text17
Numeric9
Categorical2

Dataset

Description범죄발생원표를 활용한 범죄발생 장소별, 범죄분류별 현황
Author대검찰청
URLhttps://www.data.go.kr/data/2838944/fileData.do

Alerts

2009년 has unique valuesUnique
아파트연립다세대 has unique valuesUnique
단독주택 has unique valuesUnique
노상 has unique valuesUnique
상점 has unique valuesUnique
숙박업소목욕탕 has unique valuesUnique
사무실 has unique valuesUnique
의료기관 has unique valuesUnique
기타 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:38:20.196776
Analysis finished2023-12-12 21:38:20.653466
Duration0.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

2009년
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:38:20.784640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length4
Mean length6
Min length4

Characters and Unicode

Total characters138
Distinct characters60
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

Unique23 ?
Unique (%)100.0%

Sample

1st row 절도
2nd row 장물
3rd row 손괴
4th row 살인
5th row 강도
ValueCountFrequency (%)
절도 1
 
4.3%
체포와감금 1
 
4.3%
교통사고처리특례법위반 1
 
4.3%
유기 1
 
4.3%
주거침입 1
 
4.3%
실화 1
 
4.3%
업무상과실치사상 1
 
4.3%
과실치사상 1
 
4.3%
도박과복표 1
 
4.3%
간통 1
 
4.3%
Other values (13) 13
56.5%
2023-12-13T06:38:21.121690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
33.3%
4
 
2.9%
4
 
2.9%
4
 
2.9%
3
 
2.2%
3
 
2.2%
3
 
2.2%
3
 
2.2%
3
 
2.2%
3
 
2.2%
Other values (50) 62
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92
66.7%
Space Separator 46
33.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4
 
4.3%
4
 
4.3%
4
 
4.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
2
 
2.2%
Other values (49) 60
65.2%
Space Separator
ValueCountFrequency (%)
46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92
66.7%
Common 46
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4
 
4.3%
4
 
4.3%
4
 
4.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
2
 
2.2%
Other values (49) 60
65.2%
Common
ValueCountFrequency (%)
46
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92
66.7%
ASCII 46
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46
100.0%
Hangul
ValueCountFrequency (%)
4
 
4.3%
4
 
4.3%
4
 
4.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
2
 
2.2%
Other values (49) 60
65.2%

아파트연립다세대
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2114.6957
Minimum20
Maximum22282
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T06:38:21.248419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile27.9
Q199.5
median316
Q31715.5
95-th percentile7489.1
Maximum22282
Range22262
Interquartile range (IQR)1616

Descriptive statistics

Standard deviation4801.203
Coefficient of variation (CV)2.2703991
Kurtosis15.289463
Mean2114.6957
Median Absolute Deviation (MAD)266
Skewness3.7384008
Sum48638
Variance23051551
MonotonicityNot monotonic
2023-12-13T06:38:21.372936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
22282 1
 
4.3%
62 1
 
4.3%
133 1
 
4.3%
284 1
 
4.3%
20 1
 
4.3%
1135 1
 
4.3%
188 1
 
4.3%
50 1
 
4.3%
45 1
 
4.3%
1763 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
20 1
4.3%
26 1
4.3%
45 1
4.3%
50 1
4.3%
62 1
4.3%
66 1
4.3%
133 1
4.3%
188 1
4.3%
242 1
4.3%
284 1
4.3%
ValueCountFrequency (%)
22282 1
4.3%
7705 1
4.3%
5546 1
4.3%
3120 1
4.3%
2329 1
4.3%
1763 1
4.3%
1668 1
4.3%
1135 1
4.3%
560 1
4.3%
471 1
4.3%

단독주택
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3255.8261
Minimum7
Maximum36313
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T06:38:21.495866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile16.9
Q178.5
median452
Q33111
95-th percentile8921.9
Maximum36313
Range36306
Interquartile range (IQR)3032.5

Descriptive statistics

Standard deviation7637.0779
Coefficient of variation (CV)2.3456652
Kurtosis17.56102
Mean3255.8261
Median Absolute Deviation (MAD)414
Skewness4.0213209
Sum74884
Variance58324959
MonotonicityNot monotonic
2023-12-13T06:38:21.633934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
36313 1
 
4.3%
106 1
 
4.3%
16 1
 
4.3%
7 1
 
4.3%
25 1
 
4.3%
2741 1
 
4.3%
359 1
 
4.3%
43 1
 
4.3%
59 1
 
4.3%
5440 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
7 1
4.3%
16 1
4.3%
25 1
4.3%
38 1
4.3%
43 1
4.3%
59 1
4.3%
98 1
4.3%
106 1
4.3%
303 1
4.3%
332 1
4.3%
ValueCountFrequency (%)
36313 1
4.3%
9130 1
4.3%
7049 1
4.3%
5440 1
4.3%
4064 1
4.3%
3446 1
4.3%
2776 1
4.3%
2741 1
4.3%
839 1
4.3%
744 1
4.3%
Distinct12
Distinct (%)52.2%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:38:21.767846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.0434783
Min length1

Characters and Unicode

Total characters47
Distinct characters11
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)34.8%

Sample

1st row104
2nd row -
3rd row38
4th row -
5th row1
ValueCountFrequency (%)
6
26.1%
1 4
17.4%
3 3
13.0%
104 2
 
8.7%
38 1
 
4.3%
10 1
 
4.3%
85 1
 
4.3%
51 1
 
4.3%
5 1
 
4.3%
2 1
 
4.3%
Other values (2) 2
 
8.7%
2023-12-13T06:38:22.012953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
25.5%
1 8
17.0%
- 6
12.8%
4 5
10.6%
3 4
 
8.5%
0 3
 
6.4%
5 3
 
6.4%
8 2
 
4.3%
2 2
 
4.3%
9 1
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29
61.7%
Space Separator 12
25.5%
Dash Punctuation 6
 
12.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8
27.6%
4 5
17.2%
3 4
13.8%
0 3
 
10.3%
5 3
 
10.3%
8 2
 
6.9%
2 2
 
6.9%
9 1
 
3.4%
7 1
 
3.4%
Space Separator
ValueCountFrequency (%)
12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
12
25.5%
1 8
17.0%
- 6
12.8%
4 5
10.6%
3 4
 
8.5%
0 3
 
6.4%
5 3
 
6.4%
8 2
 
4.3%
2 2
 
4.3%
9 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
25.5%
1 8
17.0%
- 6
12.8%
4 5
10.6%
3 4
 
8.5%
0 3
 
6.4%
5 3
 
6.4%
8 2
 
4.3%
2 2
 
4.3%
9 1
 
2.1%

노상
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19131.174
Minimum22
Maximum195151
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T06:38:22.144872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile36.3
Q1283.5
median587
Q321799.5
95-th percentile61496.7
Maximum195151
Range195129
Interquartile range (IQR)21516

Descriptive statistics

Standard deviation42736.828
Coefficient of variation (CV)2.2338843
Kurtosis13.860732
Mean19131.174
Median Absolute Deviation (MAD)562
Skewness3.5004358
Sum440017
Variance1.8264365 × 109
MonotonicityNot monotonic
2023-12-13T06:38:22.279190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
62288 1
 
4.3%
587 1
 
4.3%
38433 1
 
4.3%
195151 1
 
4.3%
22 1
 
4.3%
236 1
 
4.3%
164 1
 
4.3%
381 1
 
4.3%
434 1
 
4.3%
138 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
22 1
4.3%
25 1
4.3%
138 1
4.3%
164 1
4.3%
236 1
4.3%
277 1
4.3%
290 1
4.3%
302 1
4.3%
332 1
4.3%
381 1
4.3%
ValueCountFrequency (%)
195151 1
4.3%
62288 1
4.3%
54375 1
4.3%
38433 1
4.3%
34812 1
4.3%
24964 1
4.3%
18635 1
4.3%
2788 1
4.3%
2373 1
4.3%
2131 1
4.3%

상점
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1873.5652
Minimum1
Maximum31046
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T06:38:22.427867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.6
Q130.5
median120
Q31002.5
95-th percentile3065.3
Maximum31046
Range31045
Interquartile range (IQR)972

Descriptive statistics

Standard deviation6412.592
Coefficient of variation (CV)3.4226682
Kurtosis22.135891
Mean1873.5652
Median Absolute Deviation (MAD)117
Skewness4.6703552
Sum43092
Variance41121336
MonotonicityNot monotonic
2023-12-13T06:38:22.593417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
31046 1
 
4.3%
1417 1
 
4.3%
25 1
 
4.3%
86 1
 
4.3%
3 1
 
4.3%
120 1
 
4.3%
99 1
 
4.3%
57 1
 
4.3%
36 1
 
4.3%
574 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1 1
4.3%
3 1
4.3%
9 1
4.3%
12 1
4.3%
20 1
4.3%
25 1
4.3%
36 1
4.3%
57 1
4.3%
72 1
4.3%
86 1
4.3%
ValueCountFrequency (%)
31046 1
4.3%
3175 1
4.3%
2078 1
4.3%
1520 1
4.3%
1417 1
4.3%
1350 1
4.3%
655 1
4.3%
574 1
4.3%
369 1
4.3%
241 1
4.3%
Distinct20
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:38:22.785228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.826087
Min length1

Characters and Unicode

Total characters42
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)73.9%

Sample

1st row766
2nd row10
3rd row89
4th row5
5th row7
ValueCountFrequency (%)
2
 
8.7%
1 2
 
8.7%
5 2
 
8.7%
766 1
 
4.3%
75 1
 
4.3%
2 1
 
4.3%
4 1
 
4.3%
3 1
 
4.3%
9 1
 
4.3%
31 1
 
4.3%
Other values (10) 10
43.5%
2023-12-13T06:38:23.123232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7
16.7%
7 5
11.9%
6 5
11.9%
4 5
11.9%
4
9.5%
3 4
9.5%
5 3
7.1%
- 2
 
4.8%
0 2
 
4.8%
9 2
 
4.8%
Other values (2) 3
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36
85.7%
Space Separator 4
 
9.5%
Dash Punctuation 2
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7
19.4%
7 5
13.9%
6 5
13.9%
4 5
13.9%
3 4
11.1%
5 3
8.3%
0 2
 
5.6%
9 2
 
5.6%
2 2
 
5.6%
8 1
 
2.8%
Space Separator
ValueCountFrequency (%)
4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7
16.7%
7 5
11.9%
6 5
11.9%
4 5
11.9%
4
9.5%
3 4
9.5%
5 3
7.1%
- 2
 
4.8%
0 2
 
4.8%
9 2
 
4.8%
Other values (2) 3
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7
16.7%
7 5
11.9%
6 5
11.9%
4 5
11.9%
4
9.5%
3 4
9.5%
5 3
7.1%
- 2
 
4.8%
0 2
 
4.8%
9 2
 
4.8%
Other values (2) 3
7.1%
Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:38:23.335711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.6086957
Min length1

Characters and Unicode

Total characters60
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row8563
2nd row15
3rd row814
4th row42
5th row390
ValueCountFrequency (%)
8563 1
 
4.3%
57 1
 
4.3%
1
 
4.3%
3 1
 
4.3%
209 1
 
4.3%
37 1
 
4.3%
54 1
 
4.3%
21 1
 
4.3%
276 1
 
4.3%
741 1
 
4.3%
Other values (13) 13
56.5%
2023-12-13T06:38:23.681541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
18.3%
4 8
13.3%
1 7
11.7%
5 6
10.0%
3 5
8.3%
9 5
8.3%
7 5
8.3%
6 4
 
6.7%
8 3
 
5.0%
0 3
 
5.0%
Other values (2) 3
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
95.0%
Space Separator 2
 
3.3%
Dash Punctuation 1
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
19.3%
4 8
14.0%
1 7
12.3%
5 6
10.5%
3 5
8.8%
9 5
8.8%
7 5
8.8%
6 4
 
7.0%
8 3
 
5.3%
0 3
 
5.3%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
18.3%
4 8
13.3%
1 7
11.7%
5 6
10.0%
3 5
8.3%
9 5
8.3%
7 5
8.3%
6 4
 
6.7%
8 3
 
5.0%
0 3
 
5.0%
Other values (2) 3
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
18.3%
4 8
13.3%
1 7
11.7%
5 6
10.0%
3 5
8.3%
9 5
8.3%
7 5
8.3%
6 4
 
6.7%
8 3
 
5.0%
0 3
 
5.0%
Other values (2) 3
 
5.0%
Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:38:23.889353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.826087
Min length1

Characters and Unicode

Total characters65
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)91.3%

Sample

1st row15217
2nd row25
3rd row3421
4th row99
5th row454
ValueCountFrequency (%)
99 2
 
8.7%
15217 1
 
4.3%
41 1
 
4.3%
2 1
 
4.3%
1
 
4.3%
193 1
 
4.3%
59 1
 
4.3%
150 1
 
4.3%
1149 1
 
4.3%
27 1
 
4.3%
Other values (12) 12
52.2%
2023-12-13T06:38:24.227354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 10
15.4%
1 10
15.4%
5 10
15.4%
2 6
9.2%
4 6
9.2%
7 5
7.7%
0 5
7.7%
8 4
 
6.2%
3 3
 
4.6%
6 3
 
4.6%
Other values (2) 3
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
95.4%
Space Separator 2
 
3.1%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 10
16.1%
1 10
16.1%
5 10
16.1%
2 6
9.7%
4 6
9.7%
7 5
8.1%
0 5
8.1%
8 4
 
6.5%
3 3
 
4.8%
6 3
 
4.8%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 10
15.4%
1 10
15.4%
5 10
15.4%
2 6
9.2%
4 6
9.2%
7 5
7.7%
0 5
7.7%
8 4
 
6.2%
3 3
 
4.6%
6 3
 
4.6%
Other values (2) 3
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 10
15.4%
1 10
15.4%
5 10
15.4%
2 6
9.2%
4 6
9.2%
7 5
7.7%
0 5
7.7%
8 4
 
6.2%
3 3
 
4.6%
6 3
 
4.6%
Other values (2) 3
 
4.6%

사무실
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1258.6522
Minimum3
Maximum8495
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T06:38:24.396632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile6.6
Q152
median144
Q3802
95-th percentile7462.1
Maximum8495
Range8492
Interquartile range (IQR)750

Descriptive statistics

Standard deviation2420.7056
Coefficient of variation (CV)1.9232522
Kurtosis4.7950792
Mean1258.6522
Median Absolute Deviation (MAD)132
Skewness2.3445803
Sum28949
Variance5859815.6
MonotonicityNot monotonic
2023-12-13T06:38:24.557165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
7874 1
 
4.3%
144 1
 
4.3%
60 1
 
4.3%
136 1
 
4.3%
3 1
 
4.3%
287 1
 
4.3%
59 1
 
4.3%
50 1
 
4.3%
21 1
 
4.3%
8495 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
3 1
4.3%
5 1
4.3%
21 1
4.3%
38 1
4.3%
44 1
4.3%
50 1
4.3%
54 1
4.3%
59 1
4.3%
60 1
4.3%
82 1
4.3%
ValueCountFrequency (%)
8495 1
4.3%
7874 1
4.3%
3755 1
4.3%
3306 1
4.3%
2055 1
4.3%
1138 1
4.3%
466 1
4.3%
404 1
4.3%
287 1
4.3%
276 1
4.3%

공장
Text

Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:38:24.744690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.3043478
Min length1

Characters and Unicode

Total characters53
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)82.6%

Sample

1st row2820
2nd row75
3rd row136
4th row7
5th row23
ValueCountFrequency (%)
2
 
8.7%
295 2
 
8.7%
119 1
 
4.3%
2820 1
 
4.3%
37 1
 
4.3%
64 1
 
4.3%
139 1
 
4.3%
11 1
 
4.3%
46 1
 
4.3%
1 1
 
4.3%
Other values (11) 11
47.8%
2023-12-13T06:38:25.078942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 8
15.1%
1 8
15.1%
3 7
13.2%
9 6
11.3%
4
7.5%
5 4
7.5%
6 4
7.5%
4 4
7.5%
7 3
 
5.7%
- 2
 
3.8%
Other values (2) 3
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 47
88.7%
Space Separator 4
 
7.5%
Dash Punctuation 2
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 8
17.0%
1 8
17.0%
3 7
14.9%
9 6
12.8%
5 4
8.5%
6 4
8.5%
4 4
8.5%
7 3
 
6.4%
8 2
 
4.3%
0 1
 
2.1%
Space Separator
ValueCountFrequency (%)
4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 8
15.1%
1 8
15.1%
3 7
13.2%
9 6
11.3%
4
7.5%
5 4
7.5%
6 4
7.5%
4 4
7.5%
7 3
 
5.7%
- 2
 
3.8%
Other values (2) 3
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 8
15.1%
1 8
15.1%
3 7
13.2%
9 6
11.3%
4
7.5%
5 4
7.5%
6 4
7.5%
4 4
7.5%
7 3
 
5.7%
- 2
 
3.8%
Other values (2) 3
 
5.7%
Distinct19
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:38:25.225922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.3043478
Min length1

Characters and Unicode

Total characters53
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)73.9%

Sample

1st row3162
2nd row43
3rd row153
4th row -
5th row13
ValueCountFrequency (%)
4
17.4%
7 2
 
8.7%
291 1
 
4.3%
37 1
 
4.3%
22 1
 
4.3%
14 1
 
4.3%
28 1
 
4.3%
410 1
 
4.3%
9 1
 
4.3%
3 1
 
4.3%
Other values (9) 9
39.1%
2023-12-13T06:38:25.583904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
18.9%
3 9
17.0%
8
15.1%
2 6
11.3%
- 4
 
7.5%
4 4
 
7.5%
7 3
 
5.7%
8 3
 
5.7%
0 2
 
3.8%
9 2
 
3.8%
Other values (2) 2
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41
77.4%
Space Separator 8
 
15.1%
Dash Punctuation 4
 
7.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10
24.4%
3 9
22.0%
2 6
14.6%
4 4
 
9.8%
7 3
 
7.3%
8 3
 
7.3%
0 2
 
4.9%
9 2
 
4.9%
6 1
 
2.4%
5 1
 
2.4%
Space Separator
ValueCountFrequency (%)
8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 10
18.9%
3 9
17.0%
8
15.1%
2 6
11.3%
- 4
 
7.5%
4 4
 
7.5%
7 3
 
5.7%
8 3
 
5.7%
0 2
 
3.8%
9 2
 
3.8%
Other values (2) 2
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10
18.9%
3 9
17.0%
8
15.1%
2 6
11.3%
- 4
 
7.5%
4 4
 
7.5%
7 3
 
5.7%
8 3
 
5.7%
0 2
 
3.8%
9 2
 
3.8%
Other values (2) 2
 
3.8%

창고
Text

Distinct19
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:38:25.765074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.0434783
Min length1

Characters and Unicode

Total characters47
Distinct characters10
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)73.9%

Sample

1st row2185
2nd row165
3rd row53
4th row1
5th row11
ValueCountFrequency (%)
4
17.4%
1 2
 
8.7%
2 1
 
4.3%
2185 1
 
4.3%
4 1
 
4.3%
28 1
 
4.3%
78 1
 
4.3%
18 1
 
4.3%
44 1
 
4.3%
26 1
 
4.3%
Other values (9) 9
39.1%
2023-12-13T06:38:26.061706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
21.3%
8
17.0%
4 6
12.8%
- 4
 
8.5%
5 4
 
8.5%
6 4
 
8.5%
2 4
 
8.5%
8 4
 
8.5%
3 2
 
4.3%
7 1
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35
74.5%
Space Separator 8
 
17.0%
Dash Punctuation 4
 
8.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10
28.6%
4 6
17.1%
5 4
 
11.4%
6 4
 
11.4%
2 4
 
11.4%
8 4
 
11.4%
3 2
 
5.7%
7 1
 
2.9%
Space Separator
ValueCountFrequency (%)
8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 10
21.3%
8
17.0%
4 6
12.8%
- 4
 
8.5%
5 4
 
8.5%
6 4
 
8.5%
2 4
 
8.5%
8 4
 
8.5%
3 2
 
4.3%
7 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10
21.3%
8
17.0%
4 6
12.8%
- 4
 
8.5%
5 4
 
8.5%
6 4
 
8.5%
2 4
 
8.5%
8 4
 
8.5%
3 2
 
4.3%
7 1
 
2.1%
Distinct17
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:38:26.245321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2
Min length1

Characters and Unicode

Total characters46
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)52.2%

Sample

1st row587
2nd row7
3rd row99
4th row6
5th row21
ValueCountFrequency (%)
3
13.0%
2 2
 
8.7%
7 2
 
8.7%
6 2
 
8.7%
12 2
 
8.7%
319 1
 
4.3%
587 1
 
4.3%
15 1
 
4.3%
4 1
 
4.3%
3 1
 
4.3%
Other values (7) 7
30.4%
2023-12-13T06:38:26.941404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8
17.4%
2 7
15.2%
6
13.0%
7 4
8.7%
- 3
 
6.5%
6 3
 
6.5%
9 3
 
6.5%
4 3
 
6.5%
5 3
 
6.5%
3 3
 
6.5%
Other values (2) 3
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37
80.4%
Space Separator 6
 
13.0%
Dash Punctuation 3
 
6.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8
21.6%
2 7
18.9%
7 4
10.8%
6 3
 
8.1%
9 3
 
8.1%
4 3
 
8.1%
5 3
 
8.1%
3 3
 
8.1%
8 2
 
5.4%
0 1
 
2.7%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8
17.4%
2 7
15.2%
6
13.0%
7 4
8.7%
- 3
 
6.5%
6 3
 
6.5%
9 3
 
6.5%
4 3
 
6.5%
5 3
 
6.5%
3 3
 
6.5%
Other values (2) 3
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8
17.4%
2 7
15.2%
6
13.0%
7 4
8.7%
- 3
 
6.5%
6 3
 
6.5%
9 3
 
6.5%
4 3
 
6.5%
5 3
 
6.5%
3 3
 
6.5%
Other values (2) 3
 
6.5%
Distinct14
Distinct (%)60.9%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:38:27.086326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.173913
Min length1

Characters and Unicode

Total characters50
Distinct characters11
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)47.8%

Sample

1st row509
2nd row4
3rd row33
4th row1
5th row10
ValueCountFrequency (%)
7
30.4%
1 3
13.0%
4 2
 
8.7%
509 1
 
4.3%
33 1
 
4.3%
10 1
 
4.3%
820 1
 
4.3%
504 1
 
4.3%
213 1
 
4.3%
5 1
 
4.3%
Other values (4) 4
17.4%
2023-12-13T06:38:27.397209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14
28.0%
1 8
16.0%
- 7
14.0%
5 4
 
8.0%
0 4
 
8.0%
4 3
 
6.0%
3 3
 
6.0%
2 3
 
6.0%
8 2
 
4.0%
9 1
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29
58.0%
Space Separator 14
28.0%
Dash Punctuation 7
 
14.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8
27.6%
5 4
13.8%
0 4
13.8%
4 3
 
10.3%
3 3
 
10.3%
2 3
 
10.3%
8 2
 
6.9%
9 1
 
3.4%
7 1
 
3.4%
Space Separator
ValueCountFrequency (%)
14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 50
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
14
28.0%
1 8
16.0%
- 7
14.0%
5 4
 
8.0%
0 4
 
8.0%
4 3
 
6.0%
3 3
 
6.0%
2 3
 
6.0%
8 2
 
4.0%
9 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14
28.0%
1 8
16.0%
- 7
14.0%
5 4
 
8.0%
0 4
 
8.0%
4 3
 
6.0%
3 3
 
6.0%
2 3
 
6.0%
8 2
 
4.0%
9 1
 
2.0%

기타교통수단내
Real number (ℝ)

Distinct20
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean163.65217
Minimum1
Maximum1803
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T06:38:27.536757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.5
Q19
median24
Q3109
95-th percentile567.1
Maximum1803
Range1802
Interquartile range (IQR)100

Descriptive statistics

Standard deviation385.03384
Coefficient of variation (CV)2.3527572
Kurtosis16.290231
Mean163.65217
Median Absolute Deviation (MAD)18
Skewness3.8752725
Sum3764
Variance148251.06
MonotonicityNot monotonic
2023-12-13T06:38:27.667166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 2
 
8.7%
10 2
 
8.7%
8 2
 
8.7%
33 1
 
4.3%
149 1
 
4.3%
88 1
 
4.3%
6 1
 
4.3%
24 1
 
4.3%
79 1
 
4.3%
7 1
 
4.3%
Other values (10) 10
43.5%
ValueCountFrequency (%)
1 2
8.7%
6 1
4.3%
7 1
4.3%
8 2
8.7%
10 2
8.7%
12 1
4.3%
17 1
4.3%
18 1
4.3%
24 1
4.3%
29 1
4.3%
ValueCountFrequency (%)
1803 1
4.3%
592 1
4.3%
343 1
4.3%
308 1
4.3%
149 1
4.3%
116 1
4.3%
102 1
4.3%
88 1
4.3%
79 1
4.3%
33 1
4.3%
Distinct16
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:38:27.816696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2
Min length1

Characters and Unicode

Total characters46
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)56.5%

Sample

1st row714
2nd row3
3rd row50
4th row1
5th row13
ValueCountFrequency (%)
3 4
17.4%
1 3
13.0%
3
13.0%
714 1
 
4.3%
50 1
 
4.3%
13 1
 
4.3%
4 1
 
4.3%
40 1
 
4.3%
228 1
 
4.3%
210 1
 
4.3%
Other values (6) 6
26.1%
2023-12-13T06:38:28.129681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
21.7%
3 6
13.0%
6
13.0%
0 5
10.9%
4 4
 
8.7%
2 4
 
8.7%
- 3
 
6.5%
5 3
 
6.5%
7 2
 
4.3%
8 1
 
2.2%
Other values (2) 2
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37
80.4%
Space Separator 6
 
13.0%
Dash Punctuation 3
 
6.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10
27.0%
3 6
16.2%
0 5
13.5%
4 4
 
10.8%
2 4
 
10.8%
5 3
 
8.1%
7 2
 
5.4%
8 1
 
2.7%
6 1
 
2.7%
9 1
 
2.7%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 10
21.7%
3 6
13.0%
6
13.0%
0 5
10.9%
4 4
 
8.7%
2 4
 
8.7%
- 3
 
6.5%
5 3
 
6.5%
7 2
 
4.3%
8 1
 
2.2%
Other values (2) 2
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10
21.7%
3 6
13.0%
6
13.0%
0 5
10.9%
4 4
 
8.7%
2 4
 
8.7%
- 3
 
6.5%
5 3
 
6.5%
7 2
 
4.3%
8 1
 
2.2%
Other values (2) 2
 
4.3%
Distinct20
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:38:28.313867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.3043478
Min length1

Characters and Unicode

Total characters53
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)73.9%

Sample

1st row1116
2nd row11
3rd row100
4th row12
5th row68
ValueCountFrequency (%)
3 2
 
8.7%
11 2
 
8.7%
4 2
 
8.7%
1116 1
 
4.3%
196 1
 
4.3%
1
 
4.3%
20 1
 
4.3%
40 1
 
4.3%
41 1
 
4.3%
66 1
 
4.3%
Other values (10) 10
43.5%
2023-12-13T06:38:28.700385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
32.1%
6 6
 
11.3%
0 5
 
9.4%
2 5
 
9.4%
4 4
 
7.5%
8 4
 
7.5%
9 3
 
5.7%
3 2
 
3.8%
7 2
 
3.8%
5 2
 
3.8%
Other values (2) 3
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50
94.3%
Space Separator 2
 
3.8%
Dash Punctuation 1
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
34.0%
6 6
 
12.0%
0 5
 
10.0%
2 5
 
10.0%
4 4
 
8.0%
8 4
 
8.0%
9 3
 
6.0%
3 2
 
4.0%
7 2
 
4.0%
5 2
 
4.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
32.1%
6 6
 
11.3%
0 5
 
9.4%
2 5
 
9.4%
4 4
 
7.5%
8 4
 
7.5%
9 3
 
5.7%
3 2
 
3.8%
7 2
 
3.8%
5 2
 
3.8%
Other values (2) 3
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
32.1%
6 6
 
11.3%
0 5
 
9.4%
2 5
 
9.4%
4 4
 
7.5%
8 4
 
7.5%
9 3
 
5.7%
3 2
 
3.8%
7 2
 
3.8%
5 2
 
3.8%
Other values (2) 3
 
5.7%

학교
Real number (ℝ)

Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean301.69565
Minimum1
Maximum3394
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T06:38:28.849452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.1
Q18
median32
Q3143.5
95-th percentile1125.4
Maximum3394
Range3393
Interquartile range (IQR)135.5

Descriptive statistics

Standard deviation737.99134
Coefficient of variation (CV)2.4461451
Kurtosis15.104855
Mean301.69565
Median Absolute Deviation (MAD)29
Skewness3.7155233
Sum6939
Variance544631.22
MonotonicityNot monotonic
2023-12-13T06:38:29.002995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
6 2
 
8.7%
1 2
 
8.7%
3394 1
 
4.3%
3 1
 
4.3%
45 1
 
4.3%
65 1
 
4.3%
18 1
 
4.3%
17 1
 
4.3%
32 1
 
4.3%
2 1
 
4.3%
Other values (11) 11
47.8%
ValueCountFrequency (%)
1 2
8.7%
2 1
4.3%
3 1
4.3%
6 2
8.7%
10 1
4.3%
13 1
4.3%
17 1
4.3%
18 1
4.3%
21 1
4.3%
32 1
4.3%
ValueCountFrequency (%)
3394 1
4.3%
1159 1
4.3%
823 1
4.3%
596 1
4.3%
356 1
4.3%
149 1
4.3%
138 1
4.3%
65 1
4.3%
49 1
4.3%
45 1
4.3%
Distinct16
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:38:29.147480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.1304348
Min length1

Characters and Unicode

Total characters49
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)56.5%

Sample

1st row4913
2nd row52
3rd row181
4th row -
5th row33
ValueCountFrequency (%)
6
26.1%
4 2
 
8.7%
2 2
 
8.7%
4913 1
 
4.3%
52 1
 
4.3%
181 1
 
4.3%
33 1
 
4.3%
10 1
 
4.3%
9 1
 
4.3%
65 1
 
4.3%
Other values (6) 6
26.1%
2023-12-13T06:38:29.436047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
24.5%
- 6
12.2%
1 6
12.2%
3 5
10.2%
5 4
 
8.2%
7 4
 
8.2%
4 3
 
6.1%
2 3
 
6.1%
9 2
 
4.1%
8 2
 
4.1%
Other values (2) 2
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31
63.3%
Space Separator 12
 
24.5%
Dash Punctuation 6
 
12.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6
19.4%
3 5
16.1%
5 4
12.9%
7 4
12.9%
4 3
9.7%
2 3
9.7%
9 2
 
6.5%
8 2
 
6.5%
0 1
 
3.2%
6 1
 
3.2%
Space Separator
ValueCountFrequency (%)
12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 49
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
12
24.5%
- 6
12.2%
1 6
12.2%
3 5
10.2%
5 4
 
8.2%
7 4
 
8.2%
4 3
 
6.1%
2 3
 
6.1%
9 2
 
4.1%
8 2
 
4.1%
Other values (2) 2
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
24.5%
- 6
12.2%
1 6
12.2%
3 5
10.2%
5 4
 
8.2%
7 4
 
8.2%
4 3
 
6.1%
2 3
 
6.1%
9 2
 
4.1%
8 2
 
4.1%
Other values (2) 2
 
4.1%

의료기관
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean246.34783
Minimum1
Maximum2567
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T06:38:29.565018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.2
Q111.5
median27
Q3131.5
95-th percentile918.2
Maximum2567
Range2566
Interquartile range (IQR)120

Descriptive statistics

Standard deviation563.29143
Coefficient of variation (CV)2.2865695
Kurtosis13.942296
Mean246.34783
Median Absolute Deviation (MAD)18
Skewness3.5502927
Sum5666
Variance317297.24
MonotonicityNot monotonic
2023-12-13T06:38:29.703433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
2567 1
 
4.3%
5 1
 
4.3%
10 1
 
4.3%
35 1
 
4.3%
13 1
 
4.3%
36 1
 
4.3%
9 1
 
4.3%
492 1
 
4.3%
20 1
 
4.3%
12 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1 1
4.3%
3 1
4.3%
5 1
4.3%
9 1
4.3%
10 1
4.3%
11 1
4.3%
12 1
4.3%
13 1
4.3%
18 1
4.3%
20 1
4.3%
ValueCountFrequency (%)
2567 1
4.3%
945 1
4.3%
677 1
4.3%
492 1
4.3%
378 1
4.3%
169 1
4.3%
94 1
4.3%
79 1
4.3%
42 1
4.3%
36 1
4.3%
Distinct18
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:38:29.877731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length1.8695652
Min length1

Characters and Unicode

Total characters43
Distinct characters11
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)65.2%

Sample

1st row2175
2nd row2
3rd row151
4th row6
5th row38
ValueCountFrequency (%)
6 3
 
13.0%
2 3
 
13.0%
3 2
 
8.7%
1
 
4.3%
2175 1
 
4.3%
13 1
 
4.3%
4 1
 
4.3%
56 1
 
4.3%
15 1
 
4.3%
178 1
 
4.3%
Other values (8) 8
34.8%
2023-12-13T06:38:30.201902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
25.6%
2 7
16.3%
6 4
 
9.3%
3 4
 
9.3%
5 4
 
9.3%
7 3
 
7.0%
4 3
 
7.0%
8 2
 
4.7%
9 2
 
4.7%
2
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40
93.0%
Space Separator 2
 
4.7%
Dash Punctuation 1
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
27.5%
2 7
17.5%
6 4
 
10.0%
3 4
 
10.0%
5 4
 
10.0%
7 3
 
7.5%
4 3
 
7.5%
8 2
 
5.0%
9 2
 
5.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
25.6%
2 7
16.3%
6 4
 
9.3%
3 4
 
9.3%
5 4
 
9.3%
7 3
 
7.0%
4 3
 
7.0%
8 2
 
4.7%
9 2
 
4.7%
2
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
25.6%
2 7
16.3%
6 4
 
9.3%
3 4
 
9.3%
5 4
 
9.3%
7 3
 
7.0%
4 3
 
7.0%
8 2
 
4.7%
9 2
 
4.7%
2
 
4.7%

산야
Text

Distinct18
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:38:30.406023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.0869565
Min length1

Characters and Unicode

Total characters48
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)56.5%

Sample

1st row1700
2nd row15
3rd row495
4th row8
5th row11
ValueCountFrequency (%)
1 2
 
8.7%
37 2
 
8.7%
2
 
8.7%
9 2
 
8.7%
8 2
 
8.7%
144 1
 
4.3%
1700 1
 
4.3%
86 1
 
4.3%
22 1
 
4.3%
14 1
 
4.3%
Other values (8) 8
34.8%
2023-12-13T06:38:30.755129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
22.9%
2 6
12.5%
8 4
 
8.3%
3 4
 
8.3%
4
 
8.3%
4 4
 
8.3%
7 3
 
6.2%
9 3
 
6.2%
5 3
 
6.2%
0 3
 
6.2%
Other values (2) 3
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42
87.5%
Space Separator 4
 
8.3%
Dash Punctuation 2
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
26.2%
2 6
14.3%
8 4
 
9.5%
3 4
 
9.5%
4 4
 
9.5%
7 3
 
7.1%
9 3
 
7.1%
5 3
 
7.1%
0 3
 
7.1%
6 1
 
2.4%
Space Separator
ValueCountFrequency (%)
4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 48
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
22.9%
2 6
12.5%
8 4
 
8.3%
3 4
 
8.3%
4
 
8.3%
4 4
 
8.3%
7 3
 
6.2%
9 3
 
6.2%
5 3
 
6.2%
0 3
 
6.2%
Other values (2) 3
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
22.9%
2 6
12.5%
8 4
 
8.3%
3 4
 
8.3%
4
 
8.3%
4 4
 
8.3%
7 3
 
6.2%
9 3
 
6.2%
5 3
 
6.2%
0 3
 
6.2%
Other values (2) 3
 
6.2%

해상
Text

Distinct12
Distinct (%)52.2%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:38:30.893728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.2608696
Min length1

Characters and Unicode

Total characters52
Distinct characters11
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)43.5%

Sample

1st row481
2nd row -
3rd row74
4th row4
5th row -
ValueCountFrequency (%)
10
43.5%
1 3
 
13.0%
481 1
 
4.3%
74 1
 
4.3%
4 1
 
4.3%
90 1
 
4.3%
44 1
 
4.3%
7 1
 
4.3%
21 1
 
4.3%
163 1
 
4.3%
Other values (2) 2
 
8.7%
2023-12-13T06:38:31.127734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20
38.5%
- 10
19.2%
1 6
 
11.5%
4 5
 
9.6%
7 3
 
5.8%
2 2
 
3.8%
3 2
 
3.8%
8 1
 
1.9%
9 1
 
1.9%
0 1
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22
42.3%
Space Separator 20
38.5%
Dash Punctuation 10
19.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6
27.3%
4 5
22.7%
7 3
13.6%
2 2
 
9.1%
3 2
 
9.1%
8 1
 
4.5%
9 1
 
4.5%
0 1
 
4.5%
6 1
 
4.5%
Space Separator
ValueCountFrequency (%)
20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
20
38.5%
- 10
19.2%
1 6
 
11.5%
4 5
 
9.6%
7 3
 
5.8%
2 2
 
3.8%
3 2
 
3.8%
8 1
 
1.9%
9 1
 
1.9%
0 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20
38.5%
- 10
19.2%
1 6
 
11.5%
4 5
 
9.6%
7 3
 
5.8%
2 2
 
3.8%
3 2
 
3.8%
8 1
 
1.9%
9 1
 
1.9%
0 1
 
1.9%

부대
Categorical

Distinct8
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Memory size316.0 B
-
13 
1
4
46
 
1
5
 
1
Other values (3)

Length

Max length3
Median length3
Mean length2.2608696
Min length1

Unique

Unique5 ?
Unique (%)21.7%

Sample

1st row46
2nd row -
3rd row -
4th row -
5th row -

Common Values

ValueCountFrequency (%)
- 13
56.5%
1 3
 
13.0%
4 2
 
8.7%
46 1
 
4.3%
5 1
 
4.3%
24 1
 
4.3%
15 1
 
4.3%
2 1
 
4.3%

Length

2023-12-13T06:38:31.289168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:38:31.423774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13
56.5%
1 3
 
13.0%
4 2
 
8.7%
46 1
 
4.3%
5 1
 
4.3%
24 1
 
4.3%
15 1
 
4.3%
2 1
 
4.3%

구금장소
Categorical

Distinct8
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Memory size316.0 B
-
10 
2
4
5
 
1
80
 
1
Other values (3)

Length

Max length3
Median length2
Mean length2.0434783
Min length1

Unique

Unique5 ?
Unique (%)21.7%

Sample

1st row4
2nd row -
3rd row2
4th row -
5th row -

Common Values

ValueCountFrequency (%)
- 10
43.5%
2 5
21.7%
4 3
 
13.0%
5 1
 
4.3%
80 1
 
4.3%
131 1
 
4.3%
8 1
 
4.3%
13 1
 
4.3%

Length

2023-12-13T06:38:31.562829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:38:31.677737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10
43.5%
2 5
21.7%
4 3
 
13.0%
5 1
 
4.3%
80 1
 
4.3%
131 1
 
4.3%
8 1
 
4.3%
13 1
 
4.3%

공지
Text

Distinct14
Distinct (%)60.9%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:38:31.783223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.3913043
Min length1

Characters and Unicode

Total characters32
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)43.5%

Sample

1st row317
2nd row6
3rd row63
4th row2
5th row4
ValueCountFrequency (%)
1 5
21.7%
2 3
13.0%
5 3
13.0%
4 2
 
8.7%
317 1
 
4.3%
6 1
 
4.3%
63 1
 
4.3%
60 1
 
4.3%
83 1
 
4.3%
70 1
 
4.3%
Other values (4) 4
17.4%
2023-12-13T06:38:32.063003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8
25.0%
2 3
 
9.4%
5 3
 
9.4%
3 3
 
9.4%
6 3
 
9.4%
4 2
 
6.2%
7 2
 
6.2%
0 2
 
6.2%
8 2
 
6.2%
2
 
6.2%
Other values (2) 2
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29
90.6%
Space Separator 2
 
6.2%
Dash Punctuation 1
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8
27.6%
2 3
 
10.3%
5 3
 
10.3%
3 3
 
10.3%
6 3
 
10.3%
4 2
 
6.9%
7 2
 
6.9%
0 2
 
6.9%
8 2
 
6.9%
9 1
 
3.4%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8
25.0%
2 3
 
9.4%
5 3
 
9.4%
3 3
 
9.4%
6 3
 
9.4%
4 2
 
6.2%
7 2
 
6.2%
0 2
 
6.2%
8 2
 
6.2%
2
 
6.2%
Other values (2) 2
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8
25.0%
2 3
 
9.4%
5 3
 
9.4%
3 3
 
9.4%
6 3
 
9.4%
4 2
 
6.2%
7 2
 
6.2%
0 2
 
6.2%
8 2
 
6.2%
2
 
6.2%
Other values (2) 2
 
6.2%

기타
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5141.9565
Minimum19
Maximum43734
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T06:38:32.209450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile61.6
Q1362.5
median786
Q36159.5
95-th percentile15743.3
Maximum43734
Range43715
Interquartile range (IQR)5797

Descriptive statistics

Standard deviation9784.6543
Coefficient of variation (CV)1.9029049
Kurtosis11.193148
Mean5141.9565
Median Absolute Deviation (MAD)593
Skewness3.102444
Sum118265
Variance95739459
MonotonicityNot monotonic
2023-12-13T06:38:32.320534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
43734 1
 
4.3%
602 1
 
4.3%
1150 1
 
4.3%
2630 1
 
4.3%
19 1
 
4.3%
604 1
 
4.3%
415 1
 
4.3%
400 1
 
4.3%
237 1
 
4.3%
13397 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
19 1
4.3%
51 1
4.3%
157 1
4.3%
193 1
4.3%
237 1
4.3%
325 1
4.3%
400 1
4.3%
415 1
4.3%
602 1
4.3%
604 1
4.3%
ValueCountFrequency (%)
43734 1
4.3%
16004 1
4.3%
13397 1
4.3%
12589 1
4.3%
9818 1
4.3%
9497 1
4.3%
2822 1
4.3%
2630 1
4.3%
1326 1
4.3%
1150 1
4.3%

Sample

2009년아파트연립다세대단독주택고속도로노상상점시장노점숙박업소목욕탕유흥접객업소사무실공장공사장광산창고역대합실지하철기타교통수단내흥행장유원지학교금융기관의료기관종교기관산야해상부대구금장소공지기타
0절도222823631310462288310467668563152177874282031622185587509180371411163394491325672175170048146431743734
1장물62106-58714171015251447543165741231113525215---6602
2손괴232934463818635152089814342111381361535399331165010014918116915149574-2639497
3살인242332-3322054299387-161101126-23684--2193
4강도47183912131655739045419723131121102913684933183811---4893
5방화2934521302725827582291816241041121101119181-21325
6강간16682776102788369162425109427624101414882034340175138994443715552822
7폭행770591301045437531754342249126853755343324415425045922281161596659451911229024806016004
8상해5546704985348122078446169498673306582383643192133082108928235567721220344151318312589
9협박560744387912717603054041971105183283547927137182786
2009년아파트연립다세대단독주택고속도로노상상점시장노점숙박업소목욕탕유흥접객업소사무실공장공사장광산창고역대합실지하철기타교통수단내흥행장유원지학교금융기관의료기관종교기관산야해상부대구금장소공지기타
13폭력행위등처벌에관한법률위반3120406451249641350270917807820552952912613771102155908115937737817814421413709818
14간통316504-259174127441----8141-321----616
15도박과복표17635440-1385743127611498495463447-81106621712314---513397
16과실치사상455914343692115021119-121571044132-20622-121237
17업무상과실치사상5043538157354595029541018128792640172492337163425400
18실화188359116499437995913928784-241201849158627--11415
19주거침입11352741-23612022091932876414286-634652365693-42604
20유기20252223-3-3-----1--1-134----119
21교통사고처리특례법위반28479441951518675-21363722426-88919645335225-1-82630
22도로교통법위반133162743843325626606113--149-526-1019---91150