Overview

Dataset statistics

Number of variables26
Number of observations100
Missing cells100
Missing cells (%)3.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.5 KiB
Average record size in memory220.3 B

Variable types

Text7
Categorical10
Numeric8
Unsupported1

Alerts

lclas has constant value ""Constant
lst_updt_dt has constant value ""Constant
data_orgn has constant value ""Constant
FILE_NAME has constant value ""Constant
base_ymd has constant value ""Constant
mlsfc is highly imbalanced (85.9%)Imbalance
cmptnc_plcstn has 100 (100.0%) missing valuesMissing
id has unique valuesUnique
rdnm_addr has unique valuesUnique
zip_cd has unique valuesUnique
grid_cd has unique valuesUnique
x_cd has unique valuesUnique
y_cd has unique valuesUnique
x_utmk_cd has unique valuesUnique
y_utmk_cd has unique valuesUnique
telno has unique valuesUnique
cmptnc_plcstn is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 09:41:23.887131
Analysis finished2023-12-10 09:41:24.639934
Duration0.75 seconds
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
2023-12-10T18:41:24.913722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters1600
Distinct characters14
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 rowKC484PC19N000001
2nd rowKC484PC19N001228
3rd rowKC484PC19N002484
4th rowKC484PC19N002288
5th rowKC484PC19N002289
ValueCountFrequency (%)
kc484pc19n000001 1
 
1.0%
kc484pc19n002348 1
 
1.0%
kc484pc19n002359 1
 
1.0%
kc484pc19n002358 1
 
1.0%
kc484pc19n002357 1
 
1.0%
kc484pc19n002356 1
 
1.0%
kc484pc19n002355 1
 
1.0%
kc484pc19n002354 1
 
1.0%
kc484pc19n002353 1
 
1.0%
kc484pc19n002352 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:41:25.982848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 223
13.9%
4 221
13.8%
C 200
12.5%
2 132
8.2%
1 122
7.6%
8 120
7.5%
9 120
7.5%
3 104
6.5%
K 100
6.2%
P 100
6.2%
Other values (4) 158
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1100
68.8%
Uppercase Letter 500
31.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 223
20.3%
4 221
20.1%
2 132
12.0%
1 122
11.1%
8 120
10.9%
9 120
10.9%
3 104
9.5%
5 20
 
1.8%
7 19
 
1.7%
6 19
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
C 200
40.0%
K 100
20.0%
P 100
20.0%
N 100
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1100
68.8%
Latin 500
31.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 223
20.3%
4 221
20.1%
2 132
12.0%
1 122
11.1%
8 120
10.9%
9 120
10.9%
3 104
9.5%
5 20
 
1.8%
7 19
 
1.7%
6 19
 
1.7%
Latin
ValueCountFrequency (%)
C 200
40.0%
K 100
20.0%
P 100
20.0%
N 100
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 223
13.9%
4 221
13.8%
C 200
12.5%
2 132
8.2%
1 122
7.6%
8 120
7.5%
9 120
7.5%
3 104
6.5%
K 100
6.2%
P 100
6.2%
Other values (4) 158
9.9%

lclas
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안전시설 100
100.0%

Length

2023-12-10T18:41:26.232502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:41:26.389788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안전시설 100
100.0%

mlsfc
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경찰
98 
소방
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row소방
2nd row소방
3rd row경찰
4th row경찰
5th row경찰

Common Values

ValueCountFrequency (%)
경찰 98
98.0%
소방 2
 
2.0%

Length

2023-12-10T18:41:26.523508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:41:26.692110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경찰 98
98.0%
소방 2
 
2.0%

fclt_name
Text

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:41:27.092853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length5.24
Min length5

Characters and Unicode

Total characters524
Distinct characters114
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

Unique97 ?
Unique (%)97.0%

Sample

1st row세종로119안전센터
2nd row창녕소방서
3rd row선유도파출소
4th row금왕지구대
5th row대소파출소
ValueCountFrequency (%)
중앙지구대 3
 
3.0%
병천동면파출소 1
 
1.0%
양촌파출소 1
 
1.0%
상월파출소 1
 
1.0%
연무지구대 1
 
1.0%
강경지구대 1
 
1.0%
논산지구대 1
 
1.0%
계룡지구대 1
 
1.0%
팔봉파출소 1
 
1.0%
부석파출소 1
 
1.0%
Other values (88) 88
88.0%
2023-12-10T18:41:27.883122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 75
 
14.3%
파 73
 
13.9%
출 73
 
13.9%
대 29
 
5.5%
구 26
 
5.0%
지 25
 
4.8%
산 12
 
2.3%
성 11
 
2.1%
천 6
 
1.1%
신 6
 
1.1%
Other values (104) 188
35.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 521
99.4%
Decimal Number 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 75
14.4%
파 73
 
14.0%
출 73
 
14.0%
대 29
 
5.6%
구 26
 
5.0%
지 25
 
4.8%
산 12
 
2.3%
성 11
 
2.1%
천 6
 
1.2%
신 6
 
1.2%
Other values (102) 185
35.5%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
9 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 521
99.4%
Common 3
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 75
14.4%
파 73
 
14.0%
출 73
 
14.0%
대 29
 
5.6%
구 26
 
5.0%
지 25
 
4.8%
산 12
 
2.3%
성 11
 
2.1%
천 6
 
1.2%
신 6
 
1.2%
Other values (102) 185
35.5%
Common
ValueCountFrequency (%)
1 2
66.7%
9 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 521
99.4%
ASCII 3
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 75
14.4%
파 73
 
14.0%
출 73
 
14.0%
대 29
 
5.6%
구 26
 
5.0%
지 25
 
4.8%
산 12
 
2.3%
성 11
 
2.1%
천 6
 
1.2%
신 6
 
1.2%
Other values (102) 185
35.5%
ASCII
ValueCountFrequency (%)
1 2
66.7%
9 1
33.3%

ctprvn_nm
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
충청남도
55 
충청북도
42 
서울특별시
 
1
경상남도
 
1
전라북도
 
1

Length

Max length5
Median length4
Mean length4.01
Min length4

Unique

Unique3 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청남도 55
55.0%
충청북도 42
42.0%
서울특별시 1
 
1.0%
경상남도 1
 
1.0%
전라북도 1
 
1.0%

Length

2023-12-10T18:41:28.196539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:41:28.391166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 55
55.0%
충청북도 42
42.0%
서울특별시 1
 
1.0%
경상남도 1
 
1.0%
전라북도 1
 
1.0%

sgnr_nm
Categorical

Distinct19
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
아산시
11 
천안시 동남구
10 
공주시
8 
옥천군
7 
천안시 서북구
7 
Other values (14)
57 

Length

Max length7
Median length3
Mean length3.68
Min length3

Unique

Unique5 ?
Unique (%)5.0%

Sample

1st row종로구
2nd row창녕군
3rd row군산시
4th row음성군
5th row음성군

Common Values

ValueCountFrequency (%)
아산시 11
11.0%
천안시 동남구 10
 
10.0%
공주시 8
 
8.0%
옥천군 7
 
7.0%
천안시 서북구 7
 
7.0%
서산시 7
 
7.0%
괴산군 6
 
6.0%
보은군 6
 
6.0%
논산시 6
 
6.0%
영동군 6
 
6.0%
Other values (9) 26
26.0%

Length

2023-12-10T18:41:28.627968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
천안시 17
14.5%
아산시 11
 
9.4%
동남구 10
 
8.5%
공주시 8
 
6.8%
옥천군 7
 
6.0%
서북구 7
 
6.0%
서산시 7
 
6.0%
논산시 6
 
5.1%
음성군 6
 
5.1%
영동군 6
 
5.1%
Other values (10) 32
27.4%

legaldong_cd
Real number (ℝ)

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3721943 × 109
Minimum1.1110124 × 109
Maximum4.874036 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:41:28.875767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110124 × 109
5-th percentile4.3720383 × 109
Q14.3750365 × 109
median4.4131285 × 109
Q34.4200148 × 109
95-th percentile4.4230341 × 109
Maximum4.874036 × 109
Range3.7630236 × 109
Interquartile range (IQR)44978280

Descriptive statistics

Standard deviation3.3365927 × 108
Coefficient of variation (CV)0.076313917
Kurtosis94.905885
Mean4.3721943 × 109
Median Absolute Deviation (MAD)9896656.5
Skewness-9.5866699
Sum4.3721943 × 1011
Variance1.1132851 × 1017
MonotonicityNot monotonic
2023-12-10T18:41:29.129399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4413110700 2
 
2.0%
1111012400 1
 
1.0%
4421010500 1
 
1.0%
4423039021 1
 
1.0%
4423034021 1
 
1.0%
4423025331 1
 
1.0%
4423025029 1
 
1.0%
4423010200 1
 
1.0%
4425031521 1
 
1.0%
4421033028 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
1111012400 1
1.0%
4372025031 1
1.0%
4372031527 1
1.0%
4372033021 1
1.0%
4372035021 1
1.0%
4372038521 1
1.0%
4372039024 1
1.0%
4373025022 1
1.0%
4373031021 1
1.0%
4373033022 1
1.0%
ValueCountFrequency (%)
4874036025 1
1.0%
4513039024 1
1.0%
4425031521 1
1.0%
4423039021 1
1.0%
4423036026 1
1.0%
4423034021 1
1.0%
4423025331 1
1.0%
4423025029 1
1.0%
4423010200 1
1.0%
4421039025 1
1.0%

legalemd_nm
Text

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:41:29.646344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.02
Min length3

Characters and Unicode

Total characters302
Distinct characters108
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)94.0%

Sample

1st row수송동
2nd row대지면
3rd row옥도면
4th row금왕읍
5th row대소면
ValueCountFrequency (%)
맹동면 2
 
2.0%
원성동 2
 
2.0%
배방읍 2
 
2.0%
유구읍 1
 
1.0%
해미면 1
 
1.0%
잠홍동 1
 
1.0%
연무읍 1
 
1.0%
강경읍 1
 
1.0%
반월동 1
 
1.0%
엄사면 1
 
1.0%
Other values (87) 87
87.0%
2023-12-10T18:41:30.496924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
면 61
 
20.2%
동 25
 
8.3%
읍 19
 
6.3%
성 9
 
3.0%
산 9
 
3.0%
천 7
 
2.3%
신 6
 
2.0%
대 5
 
1.7%
청 4
 
1.3%
원 4
 
1.3%
Other values (98) 153
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 302
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 61
 
20.2%
동 25
 
8.3%
읍 19
 
6.3%
성 9
 
3.0%
산 9
 
3.0%
천 7
 
2.3%
신 6
 
2.0%
대 5
 
1.7%
청 4
 
1.3%
원 4
 
1.3%
Other values (98) 153
50.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 302
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 61
 
20.2%
동 25
 
8.3%
읍 19
 
6.3%
성 9
 
3.0%
산 9
 
3.0%
천 7
 
2.3%
신 6
 
2.0%
대 5
 
1.7%
청 4
 
1.3%
원 4
 
1.3%
Other values (98) 153
50.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 302
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
면 61
 
20.2%
동 25
 
8.3%
읍 19
 
6.3%
성 9
 
3.0%
산 9
 
3.0%
천 7
 
2.3%
신 6
 
2.0%
대 5
 
1.7%
청 4
 
1.3%
원 4
 
1.3%
Other values (98) 153
50.7%

adstrd_cd
Real number (ℝ)

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3722032 × 109
Minimum1.1110615 × 109
Maximum4.874036 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:41:30.857787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110615 × 109
5-th percentile4.3720383 × 109
Q14.3750365 × 109
median4.413155 × 109
Q34.4200272 × 109
95-th percentile4.4230362 × 109
Maximum4.874036 × 109
Range3.7629745 × 109
Interquartile range (IQR)44990725

Descriptive statistics

Standard deviation3.3365554 × 108
Coefficient of variation (CV)0.076312908
Kurtosis94.905438
Mean4.3722032 × 109
Median Absolute Deviation (MAD)9874650
Skewness-9.5866373
Sum4.3722032 × 1011
Variance1.1132602 × 1017
MonotonicityNot monotonic
2023-12-10T18:41:31.137960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4377033000 2
 
2.0%
4413154000 2
 
2.0%
4420025300 2
 
2.0%
1111061500 1
 
1.0%
4421039000 1
 
1.0%
4423034000 1
 
1.0%
4423025300 1
 
1.0%
4423025000 1
 
1.0%
4423051000 1
 
1.0%
4425031500 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
1111061500 1
1.0%
4372025000 1
1.0%
4372031500 1
1.0%
4372033000 1
1.0%
4372035000 1
1.0%
4372038500 1
1.0%
4372039000 1
1.0%
4373025000 1
1.0%
4373031000 1
1.0%
4373033000 1
1.0%
ValueCountFrequency (%)
4874036000 1
1.0%
4513039000 1
1.0%
4425031500 1
1.0%
4423051000 1
1.0%
4423039000 1
1.0%
4423036000 1
1.0%
4423034000 1
1.0%
4423025300 1
1.0%
4423025000 1
1.0%
4421052500 1
1.0%

adstrd_nm
Text

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:41:31.663756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length3.2
Min length3

Characters and Unicode

Total characters320
Distinct characters108
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

Unique94 ?
Unique (%)94.0%

Sample

1st row종로1.2.3.4가동
2nd row대지면
3rd row옥도면
4th row금왕읍
5th row대소면
ValueCountFrequency (%)
맹동면 2
 
2.0%
원성2동 2
 
2.0%
배방읍 2
 
2.0%
유구읍 1
 
1.0%
해미면 1
 
1.0%
동문1동 1
 
1.0%
연무읍 1
 
1.0%
강경읍 1
 
1.0%
취암동 1
 
1.0%
엄사면 1
 
1.0%
Other values (87) 87
87.0%
2023-12-10T18:41:32.372119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
면 61
 
19.1%
동 25
 
7.8%
읍 19
 
5.9%
성 12
 
3.8%
산 9
 
2.8%
천 8
 
2.5%
대 6
 
1.9%
양 5
 
1.6%
신 5
 
1.6%
이 4
 
1.2%
Other values (98) 166
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 303
94.7%
Decimal Number 14
 
4.4%
Other Punctuation 3
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 61
20.1%
동 25
 
8.3%
읍 19
 
6.3%
성 12
 
4.0%
산 9
 
3.0%
천 8
 
2.6%
대 6
 
2.0%
양 5
 
1.7%
신 5
 
1.7%
이 4
 
1.3%
Other values (92) 149
49.2%
Decimal Number
ValueCountFrequency (%)
3 4
28.6%
2 4
28.6%
1 3
21.4%
5 2
14.3%
4 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 303
94.7%
Common 17
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 61
20.1%
동 25
 
8.3%
읍 19
 
6.3%
성 12
 
4.0%
산 9
 
3.0%
천 8
 
2.6%
대 6
 
2.0%
양 5
 
1.7%
신 5
 
1.7%
이 4
 
1.3%
Other values (92) 149
49.2%
Common
ValueCountFrequency (%)
3 4
23.5%
2 4
23.5%
1 3
17.6%
. 3
17.6%
5 2
11.8%
4 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 303
94.7%
ASCII 17
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
면 61
20.1%
동 25
 
8.3%
읍 19
 
6.3%
성 12
 
4.0%
산 9
 
3.0%
천 8
 
2.6%
대 6
 
2.0%
양 5
 
1.7%
신 5
 
1.7%
이 4
 
1.3%
Other values (92) 149
49.2%
ASCII
ValueCountFrequency (%)
3 4
23.5%
2 4
23.5%
1 3
17.6%
. 3
17.6%
5 2
11.8%
4 1
 
5.9%

rdnmaddr_cd
Real number (ℝ)

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3722029 × 1011
Minimum1.111041 × 1011
Maximum4.8740334 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:41:32.643360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111041 × 1011
5-th percentile4.3720324 × 1011
Q14.3750454 × 1011
median4.4131455 × 1011
Q34.4200325 × 1011
95-th percentile4.4230332 × 1011
Maximum4.8740334 × 1011
Range3.7629924 × 1011
Interquartile range (IQR)4.4987177 × 109

Descriptive statistics

Standard deviation3.3365745 × 1010
Coefficient of variation (CV)0.076313349
Kurtosis94.905623
Mean4.3722029 × 1011
Median Absolute Deviation (MAD)9.8870777 × 108
Skewness-9.5866522
Sum4.3722029 × 1013
Variance1.1132729 × 1021
MonotonicityNot monotonic
2023-12-10T18:41:33.015085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441313249055 2
 
2.0%
111104100312 1
 
1.0%
442103254210 1
 
1.0%
442303255041 1
 
1.0%
442303255015 1
 
1.0%
442304565593 1
 
1.0%
442303255043 1
 
1.0%
442303255038 1
 
1.0%
442503000095 1
 
1.0%
442103254159 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
111104100312 1
1.0%
437203240090 1
1.0%
437203241003 1
1.0%
437203241010 1
1.0%
437203241025 1
1.0%
437203241038 1
1.0%
437204523150 1
1.0%
437303000091 1
1.0%
437303014028 1
1.0%
437303242033 1
1.0%
ValueCountFrequency (%)
487403341033 1
1.0%
451304604573 1
1.0%
442503000095 1
1.0%
442304565593 1
1.0%
442304565462 1
1.0%
442303255043 1
1.0%
442303255041 1
1.0%
442303255038 1
1.0%
442303255015 1
1.0%
442104562697 1
1.0%

rdnm_addr
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:41:33.614095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length20.43
Min length15

Characters and Unicode

Total characters2043
Distinct characters174
Distinct categories6 ?
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 row서울특별시 종로구 종로1길 28 (수송동)
2nd row경남 창녕군 대지면 우포2로 1097
3rd row전라북도 군산시 옥도면 선유북길 70-2
4th row충청북도 음성군 금왕읍 금석로 73
5th row충청북도 음성군 대소면 오산로 43
ValueCountFrequency (%)
충청남도 55
 
11.1%
충청북도 42
 
8.5%
천안시 17
 
3.4%
아산시 11
 
2.2%
동남구 10
 
2.0%
공주시 8
 
1.6%
옥천군 7
 
1.4%
서산시 7
 
1.4%
서북구 7
 
1.4%
영동군 6
 
1.2%
Other values (277) 325
65.7%
2023-12-10T18:41:34.322255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
395
19.3%
청 103
 
5.0%
도 102
 
5.0%
충 101
 
4.9%
로 73
 
3.6%
남 71
 
3.5%
1 66
 
3.2%
면 60
 
2.9%
시 59
 
2.9%
북 55
 
2.7%
Other values (164) 958
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1344
65.8%
Space Separator 395
 
19.3%
Decimal Number 295
 
14.4%
Dash Punctuation 7
 
0.3%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 103
 
7.7%
도 102
 
7.6%
충 101
 
7.5%
로 73
 
5.4%
남 71
 
5.3%
면 60
 
4.5%
시 59
 
4.4%
북 55
 
4.1%
산 53
 
3.9%
군 45
 
3.3%
Other values (150) 622
46.3%
Decimal Number
ValueCountFrequency (%)
1 66
22.4%
2 40
13.6%
3 35
11.9%
4 29
9.8%
5 24
 
8.1%
8 23
 
7.8%
0 23
 
7.8%
7 22
 
7.5%
6 19
 
6.4%
9 14
 
4.7%
Space Separator
ValueCountFrequency (%)
395
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1344
65.8%
Common 699
34.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 103
 
7.7%
도 102
 
7.6%
충 101
 
7.5%
로 73
 
5.4%
남 71
 
5.3%
면 60
 
4.5%
시 59
 
4.4%
북 55
 
4.1%
산 53
 
3.9%
군 45
 
3.3%
Other values (150) 622
46.3%
Common
ValueCountFrequency (%)
395
56.5%
1 66
 
9.4%
2 40
 
5.7%
3 35
 
5.0%
4 29
 
4.1%
5 24
 
3.4%
8 23
 
3.3%
0 23
 
3.3%
7 22
 
3.1%
6 19
 
2.7%
Other values (4) 23
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1344
65.8%
ASCII 699
34.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
395
56.5%
1 66
 
9.4%
2 40
 
5.7%
3 35
 
5.0%
4 29
 
4.1%
5 24
 
3.4%
8 23
 
3.3%
0 23
 
3.3%
7 22
 
3.1%
6 19
 
2.7%
Other values (4) 23
 
3.3%
Hangul
ValueCountFrequency (%)
청 103
 
7.7%
도 102
 
7.6%
충 101
 
7.5%
로 73
 
5.4%
남 71
 
5.3%
면 60
 
4.5%
시 59
 
4.4%
북 55
 
4.1%
산 53
 
3.9%
군 45
 
3.3%
Other values (150) 622
46.3%

zip_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30533.58
Minimum3153
Maximum54000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:41:34.671347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3153
5-th percentile27026.7
Q128906
median31149.5
Q331968
95-th percentile33415.1
Maximum54000
Range50847
Interquartile range (IQR)3062

Descriptive statistics

Standard deviation4576.8487
Coefficient of variation (CV)0.14989558
Kurtosis21.881491
Mean30533.58
Median Absolute Deviation (MAD)1928
Skewness-0.018353104
Sum3053358
Variance20947544
MonotonicityNot monotonic
2023-12-10T18:41:35.108293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3153 1
 
1.0%
32002 1
 
1.0%
33022 1
 
1.0%
32904 1
 
1.0%
33007 1
 
1.0%
32939 1
 
1.0%
32951 1
 
1.0%
32823 1
 
1.0%
31924 1
 
1.0%
32019 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
3153 1
1.0%
27005 1
1.0%
27012 1
1.0%
27018 1
1.0%
27021 1
1.0%
27027 1
1.0%
27603 1
1.0%
27636 1
1.0%
27649 1
1.0%
27668 1
1.0%
ValueCountFrequency (%)
54000 1
1.0%
50319 1
1.0%
33512 1
1.0%
33488 1
1.0%
33436 1
1.0%
33414 1
1.0%
33402 1
1.0%
33022 1
1.0%
33007 1
1.0%
32951 1
1.0%

grid_cd
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:41:35.758434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters800
Distinct characters16
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

Unique100 ?
Unique (%)100.0%

Sample

1st row다사539527
2nd row라마887287
3rd row다마230703
4th row다바986854
5th row라바003914
ValueCountFrequency (%)
다사539527 1
 
1.0%
다바060645 1
 
1.0%
다마765932 1
 
1.0%
다바678108 1
 
1.0%
다마638922 1
 
1.0%
다마563953 1
 
1.0%
다바626009 1
 
1.0%
다바769094 1
 
1.0%
나바973689 1
 
1.0%
다바011580 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:41:36.688378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 90
11.2%
바 89
11.1%
7 76
9.5%
2 63
7.9%
다 61
7.6%
1 59
7.4%
0 58
7.2%
5 54
 
6.8%
8 54
 
6.8%
9 53
 
6.6%
Other values (6) 143
17.9%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 90
15.0%
7 76
12.7%
2 63
10.5%
1 59
9.8%
0 58
9.7%
5 54
9.0%
8 54
9.0%
9 53
8.8%
3 51
8.5%
4 42
7.0%
Other Letter
ValueCountFrequency (%)
바 89
44.5%
다 61
30.5%
라 38
19.0%
마 9
 
4.5%
사 2
 
1.0%
나 1
 
0.5%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
6 90
15.0%
7 76
12.7%
2 63
10.5%
1 59
9.8%
0 58
9.7%
5 54
9.0%
8 54
9.0%
9 53
8.8%
3 51
8.5%
4 42
7.0%
Hangul
ValueCountFrequency (%)
바 89
44.5%
다 61
30.5%
라 38
19.0%
마 9
 
4.5%
사 2
 
1.0%
나 1
 
0.5%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 90
15.0%
7 76
12.7%
2 63
10.5%
1 59
9.8%
0 58
9.7%
5 54
9.0%
8 54
9.0%
9 53
8.8%
3 51
8.5%
4 42
7.0%
Hangul
ValueCountFrequency (%)
바 89
44.5%
다 61
30.5%
라 38
19.0%
마 9
 
4.5%
사 2
 
1.0%
나 1
 
0.5%

x_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.633844
Minimum35.550496
Maximum37.572773
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:41:37.017235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.550496
5-th percentile36.14648
Q136.362351
median36.772483
Q336.846464
95-th percentile37.021485
Maximum37.572773
Range2.022277
Interquartile range (IQR)0.48411275

Descriptive statistics

Standard deviation0.31939212
Coefficient of variation (CV)0.0087184986
Kurtosis0.6442564
Mean36.633844
Median Absolute Deviation (MAD)0.179224
Skewness-0.52299116
Sum3663.3844
Variance0.10201132
MonotonicityNot monotonic
2023-12-10T18:41:37.313970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.572773 1
 
1.0%
36.789618 1
 
1.0%
36.136387 1
 
1.0%
36.294275 1
 
1.0%
36.126804 1
 
1.0%
36.154202 1
 
1.0%
36.204736 1
 
1.0%
36.281999 1
 
1.0%
36.813022 1
 
1.0%
36.715415 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
35.550496 1
1.0%
35.813492 1
1.0%
36.099135 1
1.0%
36.126804 1
1.0%
36.136387 1
1.0%
36.147011 1
1.0%
36.149814 1
1.0%
36.154202 1
1.0%
36.172497 1
1.0%
36.204736 1
1.0%
ValueCountFrequency (%)
37.572773 1
1.0%
37.118932 1
1.0%
37.079467 1
1.0%
37.032607 1
1.0%
37.026688 1
1.0%
37.021211 1
1.0%
36.991772 1
1.0%
36.989716 1
1.0%
36.980179 1
1.0%
36.967393 1
1.0%

y_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.31389
Minimum126.34896
Maximum128.48335
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:41:37.680321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.34896
5-th percentile126.46039
Q1127.05093
median127.21403
Q3127.64546
95-th percentile128.30336
Maximum128.48335
Range2.134398
Interquartile range (IQR)0.594531

Descriptive statistics

Standard deviation0.49002739
Coefficient of variation (CV)0.0038489705
Kurtosis-0.091645019
Mean127.31389
Median Absolute Deviation (MAD)0.3146715
Skewness0.19349571
Sum12731.389
Variance0.24012684
MonotonicityNot monotonic
2023-12-10T18:41:37.945916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.978863 1
 
1.0%
126.481301 1
 
1.0%
127.239051 1
 
1.0%
127.141509 1
 
1.0%
127.098499 1
 
1.0%
127.014893 1
 
1.0%
127.084284 1
 
1.0%
127.242794 1
 
1.0%
126.348956 1
 
1.0%
126.39302 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.348956 1
1.0%
126.39302 1
1.0%
126.414593 1
1.0%
126.434642 1
1.0%
126.447733 1
1.0%
126.461052 1
1.0%
126.481301 1
1.0%
126.514732 1
1.0%
126.527617 1
1.0%
126.550721 1
1.0%
ValueCountFrequency (%)
128.483354 1
1.0%
128.479146 1
1.0%
128.384496 1
1.0%
128.367817 1
1.0%
128.352779 1
1.0%
128.300764 1
1.0%
127.99797 1
1.0%
127.914483 1
1.0%
127.909418 1
1.0%
127.862979 1
1.0%

cmptnc_hdqrt
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
충남지방경찰청
55 
충북지방경찰청
42 
서울소방재난본부
 
1
경남소방본부
 
1
전북지방경찰청
 
1

Length

Max length8
Median length7
Mean length7
Min length6

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row서울소방재난본부
2nd row경남소방본부
3rd row전북지방경찰청
4th row충북지방경찰청
5th row충북지방경찰청

Common Values

ValueCountFrequency (%)
충남지방경찰청 55
55.0%
충북지방경찰청 42
42.0%
서울소방재난본부 1
 
1.0%
경남소방본부 1
 
1.0%
전북지방경찰청 1
 
1.0%

Length

2023-12-10T18:41:38.314703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:41:38.630885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충남지방경찰청 55
55.0%
충북지방경찰청 42
42.0%
서울소방재난본부 1
 
1.0%
경남소방본부 1
 
1.0%
전북지방경찰청 1
 
1.0%

cmptnc_dept
Categorical

Distinct17
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
아산경찰서
11 
천안동남경찰서
10 
공주경찰서
8 
옥천경찰서
7 
괴산경찰서
7 
Other values (12)
57 

Length

Max length7
Median length5
Mean length5.33
Min length4

Unique

Unique3 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
아산경찰서 11
11.0%
천안동남경찰서 10
10.0%
공주경찰서 8
 
8.0%
옥천경찰서 7
 
7.0%
괴산경찰서 7
 
7.0%
논산경찰서 7
 
7.0%
서산경찰서 7
 
7.0%
천안서북경찰서 7
 
7.0%
보은경찰서 6
 
6.0%
음성경찰서 6
 
6.0%
Other values (7) 24
24.0%

Length

2023-12-10T18:41:39.030192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아산경찰서 11
11.0%
천안동남경찰서 10
10.0%
공주경찰서 8
 
8.0%
옥천경찰서 7
 
7.0%
괴산경찰서 7
 
7.0%
논산경찰서 7
 
7.0%
서산경찰서 7
 
7.0%
천안서북경찰서 7
 
7.0%
영동경찰서 6
 
6.0%
보은경찰서 6
 
6.0%
Other values (7) 24
24.0%

cmptnc_plcstn
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

x_utmk_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean983366.78
Minimum897333
Maximum1088749
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:41:39.439740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum897333
5-th percentile907298.75
Q1959811.75
median974520
Q31012990.8
95-th percentile1071456.8
Maximum1088749
Range191416
Interquartile range (IQR)53179

Descriptive statistics

Standard deviation43813.615
Coefficient of variation (CV)0.044554703
Kurtosis-0.092886619
Mean983366.78
Median Absolute Deviation (MAD)28050.5
Skewness0.19120786
Sum98336678
Variance1.9196328 × 109
MonotonicityNot monotonic
2023-12-10T18:41:39.757251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
953982 1
 
1.0%
909111 1
 
1.0%
976523 1
 
1.0%
967811 1
 
1.0%
963873 1
 
1.0%
956365 1
 
1.0%
962630 1
 
1.0%
976902 1
 
1.0%
897333 1
 
1.0%
901139 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
897333 1
1.0%
901139 1
1.0%
901944 1
1.0%
905130 1
1.0%
906097 1
1.0%
907362 1
1.0%
909111 1
1.0%
911550 1
1.0%
912896 1
1.0%
915216 1
1.0%
ValueCountFrequency (%)
1088749 1
1.0%
1087406 1
1.0%
1078673 1
1.0%
1077237 1
1.0%
1075956 1
1.0%
1071220 1
1.0%
1044444 1
1.0%
1037287 1
1.0%
1036796 1
1.0%
1032387 1
1.0%

y_utmk_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1848567.4
Minimum1728720
Maximum1952727
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:41:40.024304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1728720
5-th percentile1794409.2
Q11818406
median1863882.5
Q31872053.5
95-th percentile1891458.7
Maximum1952727
Range224007
Interquartile range (IQR)53647.5

Descriptive statistics

Standard deviation35427.69
Coefficient of variation (CV)0.019164944
Kurtosis0.62559837
Mean1848567.4
Median Absolute Deviation (MAD)20139.5
Skewness-0.51851756
Sum1.8485674 × 108
Variance1.2551212 × 109
MonotonicityNot monotonic
2023-12-10T18:41:40.261507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1952727 1
 
1.0%
1866203 1
 
1.0%
1793292 1
 
1.0%
1810833 1
 
1.0%
1792273 1
 
1.0%
1795346 1
 
1.0%
1800922 1
 
1.0%
1809443 1
 
1.0%
1868933 1
 
1.0%
1858059 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1728720 1
1.0%
1757991 1
1.0%
1789145 1
1.0%
1792273 1
1.0%
1793292 1
1.0%
1794468 1
1.0%
1794830 1
1.0%
1795346 1
1.0%
1797303 1
1.0%
1800922 1
1.0%
ValueCountFrequency (%)
1952727 1
1.0%
1902260 1
1.0%
1898325 1
1.0%
1892974 1
1.0%
1892384 1
1.0%
1891410 1
1.0%
1888149 1
1.0%
1887918 1
1.0%
1887210 1
1.0%
1885440 1
1.0%

telno
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:41:41.062702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.99
Min length11

Characters and Unicode

Total characters1199
Distinct characters11
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

Unique100 ?
Unique (%)100.0%

Sample

1st row02-734-0119
2nd row055-259-9212
3rd row063-465-5123
4th row043-878-2112
5th row043-881-7112
ValueCountFrequency (%)
02-734-0119 1
 
1.0%
041-689-9805 1
 
1.0%
041-732-4112 1
 
1.0%
041-746-3302 1
 
1.0%
041-746-3305 1
 
1.0%
041-732-0112 1
 
1.0%
042-841-8112 1
 
1.0%
041-662-6112 1
 
1.0%
041-662-4112 1
 
1.0%
041-662-8112 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:41:41.756977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 246
20.5%
- 200
16.7%
4 150
12.5%
2 133
11.1%
0 129
10.8%
3 101
8.4%
5 71
 
5.9%
8 50
 
4.2%
7 46
 
3.8%
6 46
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 999
83.3%
Dash Punctuation 200
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 246
24.6%
4 150
15.0%
2 133
13.3%
0 129
12.9%
3 101
10.1%
5 71
 
7.1%
8 50
 
5.0%
7 46
 
4.6%
6 46
 
4.6%
9 27
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 200
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1199
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 246
20.5%
- 200
16.7%
4 150
12.5%
2 133
11.1%
0 129
10.8%
3 101
8.4%
5 71
 
5.9%
8 50
 
4.2%
7 46
 
3.8%
6 46
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1199
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 246
20.5%
- 200
16.7%
4 150
12.5%
2 133
11.1%
0 129
10.8%
3 101
8.4%
5 71
 
5.9%
8 50
 
4.2%
7 46
 
3.8%
6 46
 
3.8%

lst_updt_dt
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20191113
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20191113
2nd row20191113
3rd row20191113
4th row20191113
5th row20191113

Common Values

ValueCountFrequency (%)
20191113 100
100.0%

Length

2023-12-10T18:41:42.105213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:41:42.257092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20191113 100
100.0%

data_orgn
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
행정안전부 100
100.0%

Length

2023-12-10T18:41:42.474060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:41:42.641169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
행정안전부 100
100.0%

FILE_NAME
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC_484_DMSTC_MCST_SFFC_2019
100 

Length

Max length27
Median length27
Mean length27
Min length27

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_484_DMSTC_MCST_SFFC_2019
2nd rowKC_484_DMSTC_MCST_SFFC_2019
3rd rowKC_484_DMSTC_MCST_SFFC_2019
4th rowKC_484_DMSTC_MCST_SFFC_2019
5th rowKC_484_DMSTC_MCST_SFFC_2019

Common Values

ValueCountFrequency (%)
KC_484_DMSTC_MCST_SFFC_2019 100
100.0%

Length

2023-12-10T18:41:42.825170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:41:43.015775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_484_dmstc_mcst_sffc_2019 100
100.0%

base_ymd
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20191125
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20191125
2nd row20191125
3rd row20191125
4th row20191125
5th row20191125

Common Values

ValueCountFrequency (%)
20191125 100
100.0%

Length

2023-12-10T18:41:43.192831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:41:43.340341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20191125 100
100.0%

Sample

idlclasmlsfcfclt_namectprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrzip_cdgrid_cdx_cdy_cdcmptnc_hdqrtcmptnc_deptcmptnc_plcstnx_utmk_cdy_utmk_cdtelnolst_updt_dtdata_orgnFILE_NAMEbase_ymd
0KC484PC19N000001안전시설소방세종로119안전센터서울특별시종로구1111012400수송동1111061500종로1.2.3.4가동111104100312서울특별시 종로구 종로1길 28 (수송동)3153다사53952737.572773126.978863서울소방재난본부종로소방서<NA>953982195272702-734-011920191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
1KC484PC19N001228안전시설소방창녕소방서경상남도창녕군4874036025대지면4874036000대지면487403341033경남 창녕군 대지면 우포2로 109750319라마88728735.550496128.479146경남소방본부<NA><NA>10887491728720055-259-921220191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
2KC484PC19N002484안전시설경찰선유도파출소전라북도군산시4513039024옥도면4513039000옥도면451304604573전라북도 군산시 옥도면 선유북길 70-254000다마23070335.813492126.414593전북지방경찰청군산경찰서<NA>9019441757991063-465-512320191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
3KC484PC19N002288안전시설경찰금왕지구대충청북도음성군4377025321금왕읍4377025300금왕읍437703247002충청북도 음성군 금왕읍 금석로 7327636다바98685436.991772127.59743충북지방경찰청음성경찰서<NA>10086711888149043-878-211220191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
4KC484PC19N002289안전시설경찰대소파출소충청북도음성군4377034021대소면4377034000대소면437703247037충청북도 음성군 대소면 오산로 4327668라바00391436.967393127.484871충북지방경찰청음성경찰서<NA>9986541885440043-881-711220191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
5KC484PC19N002290안전시설경찰삼성파출소충청북도음성군4377035021삼성면4377035000삼성면437703247013충청북도 음성군 삼성면 덕정로 11127649라바05780937.021211127.504063충북지방경찰청음성경찰서<NA>10003621891410043-878-511220191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
6KC484PC19N002291안전시설경찰맹동파출소충청북도음성군4377033021맹동면4377033000맹동면437703014045충청북도 음성군 맹동면 덕금로 40827733라사12102236.926864127.564985충북지방경찰청음성경찰서<NA>10057891880946043-878-911220191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
7KC484PC19N002292안전시설경찰감곡파출소충청북도음성군4377037031감곡면4377037000감곡면437703000128충청북도 음성군 감곡면 장감로 12727603라바04178437.118932127.636413충북지방경찰청음성경찰서<NA>10121201902260043-881-211320191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
8KC484PC19N002293안전시설경찰혁신파출소충청북도음성군4377033028맹동면4377033000맹동면437703247070충청북도 음성군 맹동면 장성로 11527738라마25597336.904527127.546484충북지방경찰청음성경찰서<NA>10041421878467043-883-911220191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
9KC484PC19N002294안전시설경찰중앙지구대충청북도영동군4374025021영동읍4374025000영동읍437403243002충청북도 영동군 영동읍 계산로 6329144라바36703136.172497127.783632충북지방경찰청영동경찰서<NA>10255081797303043-745-311220191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
idlclasmlsfcfclt_namectprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrzip_cdgrid_cdx_cdy_cdcmptnc_hdqrtcmptnc_deptcmptnc_plcstnx_utmk_cdy_utmk_cdtelnolst_updt_dtdata_orgnFILE_NAMEbase_ymd
90KC484PC19N002376안전시설경찰탄천이인파출소충청남도공주시4415031021이인면4415031000이인면441504553983충청남도 공주시 이인면 은행길 3432607다바77622036.362881127.061743충남지방경찰청공주경찰서<NA>9606831818472041-857-011220191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
91KC484PC19N002377안전시설경찰반포파출소충청남도공주시4415034021반포면4415034000반포면441504553423충청남도 공주시 반포면 반포초교길 1532622다바66045836.39577127.251201충남지방경찰청공주경찰서<NA>9776901822060041-857-711220191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
92KC484PC19N002378안전시설경찰정안파출소충청남도공주시4415037021정안면4415037000정안면441504554063충청남도 공주시 정안면 정안중앙길 16932512다바67818236.609567127.120802충남지방경찰청공주경찰서<NA>9660901845814041-858-611220191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
93KC484PC19N002379안전시설경찰계룡파출소충청남도공주시4415033022계룡면4415033000계룡면441503251025충청남도 공주시 계룡면 영규대사로 49532616다바59830336.360762127.14195충남지방경찰청공주경찰서<NA>9678781818208041-857-511220191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
94KC484PC19N002380안전시설경찰우성사곡파출소충청남도공주시4415038021우성면4415038000우성면441504553289충청남도 공주시 우성면 동대리길 7532531다바11513136.470275127.052182충남지방경찰청공주경찰서<NA>9598811830389041-853-611220191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
95KC484PC19N002381안전시설경찰해수욕장지구대충청남도보령시4418011000신흑동4418056500대천5동441803252015충청남도 보령시 머드로 7033488다바19717436.311662126.514732충남지방경찰청보령경찰서<NA>9115501813152041-933-711220191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
96KC484PC19N002382안전시설경찰동대지구대충청남도보령시4418010400동대동4418053500대천3동441804556372충청남도 보령시 신설1길 5333436다바26010936.350733126.605653충남지방경찰청보령경찰서<NA>9197531817407041-931-011220191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
97KC484PC19N002383안전시설경찰미산파출소충청남도보령시4418039022미산면4418039000미산면441803252048충청남도 보령시 미산면 만수로 112933512다바12831836.293087126.676512충남지방경찰청보령경찰서<NA>9260571810956041-933-411220191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
98KC484PC19N002384안전시설경찰천북파출소충청남도보령시4418033021천북면4418033000천북면441804556712충청남도 보령시 천북면 하궁길 833402다바18224636.480537126.527617충남지방경찰청보령경찰서<NA>9128961831874041-641-911220191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125
99KC484PC19N002385안전시설경찰주포파출소충청남도보령시4418031021주포면4418031000주포면441804556229충청남도 보령시 주포면 보령읍성길 80-3233414다바18517236.415479126.588519충남지방경찰청보령경찰서<NA>9182831824603041-932-711220191113행정안전부KC_484_DMSTC_MCST_SFFC_201920191125