Overview

Dataset statistics

Number of variables21
Number of observations220
Missing cells246
Missing cells (%)5.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory38.2 KiB
Average record size in memory177.6 B

Variable types

Numeric7
Text8
Categorical5
Unsupported1

Dataset

Description국가 수문기상 공동활용 재난안전 시스템 내 국토교통부 국토지리정보원 공간정보공동활용시스템 내 배수펌프장 테이블 입니다.
Author국토교통부 국토지리정보원
URLhttps://www.data.go.kr/data/15123121/fileData.do

Alerts

에프17 has constant value ""Constant
심볼코드 has constant value ""Constant
설치자 has a high cardinality: 51 distinct valuesHigh cardinality
처리능력 has 5 (2.3%) missing valuesMissing
펌프시설규모 has 5 (2.3%) missing valuesMissing
계획년도 has 7 (3.2%) missing valuesMissing
관리자 has 4 (1.8%) missing valuesMissing
하천명 has 5 (2.3%) missing valuesMissing
널값 has 220 (100.0%) missing valuesMissing
공간정보일렬번호 has unique valuesUnique
널값 is an unsupported type, check if it needs cleaning or further analysisUnsupported
배수면적 has 6 (2.7%) zerosZeros
유수지용량 has 58 (26.4%) zerosZeros

Reproduction

Analysis started2023-12-12 21:59:22.908321
Analysis finished2023-12-12 21:59:23.367694
Duration0.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공간정보일렬번호
Real number (ℝ)

UNIQUE 

Distinct220
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean110.5
Minimum1
Maximum220
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T06:59:23.428425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.95
Q155.75
median110.5
Q3165.25
95-th percentile209.05
Maximum220
Range219
Interquartile range (IQR)109.5

Descriptive statistics

Standard deviation63.652704
Coefficient of variation (CV)0.57604257
Kurtosis-1.2
Mean110.5
Median Absolute Deviation (MAD)55
Skewness0
Sum24310
Variance4051.6667
MonotonicityNot monotonic
2023-12-13T06:59:23.558133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
152 1
 
0.5%
141 1
 
0.5%
142 1
 
0.5%
143 1
 
0.5%
144 1
 
0.5%
145 1
 
0.5%
146 1
 
0.5%
147 1
 
0.5%
148 1
 
0.5%
Other values (210) 210
95.5%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
220 1
0.5%
219 1
0.5%
218 1
0.5%
217 1
0.5%
216 1
0.5%
215 1
0.5%
214 1
0.5%
213 1
0.5%
212 1
0.5%
211 1
0.5%

행정구역아이디
Real number (ℝ)

Distinct166
Distinct (%)75.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8344493 × 109
Minimum1.1170117 × 109
Maximum4.885037 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T06:59:23.669658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1170117 × 109
5-th percentile1.1198608 × 109
Q11.1462608 × 109
median4.1203601 × 109
Q34.148025 × 109
95-th percentile4.5257397 × 109
Maximum4.885037 × 109
Range3.7680253 × 109
Interquartile range (IQR)3.0017642 × 109

Descriptive statistics

Standard deviation1.5206578 × 109
Coefficient of variation (CV)0.53649143
Kurtosis-1.9053709
Mean2.8344493 × 109
Median Absolute Deviation (MAD)6.0467193 × 108
Skewness-0.17188105
Sum6.2357885 × 1011
Variance2.3124001 × 1018
MonotonicityNot monotonic
2023-12-13T06:59:24.065663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4148025021 7
 
3.2%
4121010100 4
 
1.8%
1153010200 4
 
1.8%
1120011800 4
 
1.8%
4136011000 3
 
1.4%
4148010100 3
 
1.4%
4125011200 3
 
1.4%
1117012800 3
 
1.4%
4183025021 3
 
1.4%
1123010900 2
 
0.9%
Other values (156) 184
83.6%
ValueCountFrequency (%)
1117011700 1
 
0.5%
1117011800 1
 
0.5%
1117012200 1
 
0.5%
1117012400 1
 
0.5%
1117012800 3
1.4%
1117013100 1
 
0.5%
1117013200 1
 
0.5%
1117013300 1
 
0.5%
1117013600 1
 
0.5%
1120010600 1
 
0.5%
ValueCountFrequency (%)
4885037021 1
0.5%
4885033026 1
0.5%
4885033025 1
0.5%
4885025024 1
0.5%
4885025021 1
0.5%
4728031028 1
0.5%
4725032034 1
0.5%
4725032022 1
0.5%
4672037000 2
0.9%
4672033000 1
0.5%

상세주소
Text

Distinct219
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-13T06:59:24.376721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length19.336364
Min length16

Characters and Unicode

Total characters4254
Distinct characters189
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique218 ?
Unique (%)99.1%

Sample

1st row경상남도 하동군 진교면 진교리 302-153
2nd row경상남도 하동군 하동읍 신기리 418-3
3rd row경상남도 하동군 적량면 고절리 1173
4th row경상남도 하동군 하동읍 읍내리 1563-8
5th row경상남도 하동군 적량면 동산리 184-2
ValueCountFrequency (%)
서울특별시 96
 
10.2%
경기도 90
 
9.6%
파주시 20
 
2.1%
성동구 12
 
1.3%
용산구 11
 
1.2%
동대문구 10
 
1.1%
마포구 10
 
1.1%
문산읍 9
 
1.0%
동두천시 8
 
0.9%
김포시 8
 
0.9%
Other values (475) 667
70.9%
2023-12-13T06:59:24.783892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
791
 
18.6%
동 207
 
4.9%
시 191
 
4.5%
1 179
 
4.2%
- 164
 
3.9%
구 133
 
3.1%
도 123
 
2.9%
서 111
 
2.6%
2 108
 
2.5%
3 107
 
2.5%
Other values (179) 2140
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2429
57.1%
Decimal Number 869
 
20.4%
Space Separator 791
 
18.6%
Dash Punctuation 164
 
3.9%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 207
 
8.5%
시 191
 
7.9%
구 133
 
5.5%
도 123
 
5.1%
서 111
 
4.6%
경 103
 
4.2%
특 96
 
4.0%
별 96
 
4.0%
울 96
 
4.0%
기 93
 
3.8%
Other values (166) 1180
48.6%
Decimal Number
ValueCountFrequency (%)
1 179
20.6%
2 108
12.4%
3 107
12.3%
5 96
11.0%
4 93
10.7%
7 59
 
6.8%
8 59
 
6.8%
9 57
 
6.6%
6 56
 
6.4%
0 55
 
6.3%
Space Separator
ValueCountFrequency (%)
791
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 164
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2429
57.1%
Common 1825
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 207
 
8.5%
시 191
 
7.9%
구 133
 
5.5%
도 123
 
5.1%
서 111
 
4.6%
경 103
 
4.2%
특 96
 
4.0%
별 96
 
4.0%
울 96
 
4.0%
기 93
 
3.8%
Other values (166) 1180
48.6%
Common
ValueCountFrequency (%)
791
43.3%
1 179
 
9.8%
- 164
 
9.0%
2 108
 
5.9%
3 107
 
5.9%
5 96
 
5.3%
4 93
 
5.1%
7 59
 
3.2%
8 59
 
3.2%
9 57
 
3.1%
Other values (3) 112
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2429
57.1%
ASCII 1825
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
791
43.3%
1 179
 
9.8%
- 164
 
9.0%
2 108
 
5.9%
3 107
 
5.9%
5 96
 
5.3%
4 93
 
5.1%
7 59
 
3.2%
8 59
 
3.2%
9 57
 
3.1%
Other values (3) 112
 
6.1%
Hangul
ValueCountFrequency (%)
동 207
 
8.5%
시 191
 
7.9%
구 133
 
5.5%
도 123
 
5.1%
서 111
 
4.6%
경 103
 
4.2%
특 96
 
4.0%
별 96
 
4.0%
울 96
 
4.0%
기 93
 
3.8%
Other values (166) 1180
48.6%

펌프장명
Text

Distinct219
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-13T06:59:25.003295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length7
Mean length7.5909091
Min length5

Characters and Unicode

Total characters1670
Distinct characters170
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique218 ?
Unique (%)99.1%

Sample

1st row진교시가지배수장
2nd row신기배수장
3rd row중도들배수장
4th row동해량배수장
5th row동산배수장
ValueCountFrequency (%)
배수펌프장 4
 
1.8%
송정빗물펌프장 2
 
0.9%
성산빗물펌프장 1
 
0.4%
도농제2배수펌프장 1
 
0.4%
가운배수펌프장 1
 
0.4%
용두2빗물펌프장 1
 
0.4%
마곡빗물펌프장 1
 
0.4%
토평빗물펌프장 1
 
0.4%
증산빗물펌프장 1
 
0.4%
면목빗물펌프장 1
 
0.4%
Other values (212) 212
93.8%
2023-12-13T06:59:25.310931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 229
13.7%
펌 213
12.8%
프 213
12.8%
빗 116
 
6.9%
물 116
 
6.9%
수 91
 
5.4%
배 88
 
5.3%
2 25
 
1.5%
산 24
 
1.4%
1 24
 
1.4%
Other values (160) 531
31.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1591
95.3%
Decimal Number 69
 
4.1%
Space Separator 7
 
0.4%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 229
14.4%
펌 213
13.4%
프 213
13.4%
빗 116
 
7.3%
물 116
 
7.3%
수 91
 
5.7%
배 88
 
5.5%
산 24
 
1.5%
동 20
 
1.3%
이 15
 
0.9%
Other values (153) 466
29.3%
Decimal Number
ValueCountFrequency (%)
2 25
36.2%
1 24
34.8%
3 10
 
14.5%
4 9
 
13.0%
5 1
 
1.4%
Space Separator
ValueCountFrequency (%)
7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1591
95.3%
Common 79
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 229
14.4%
펌 213
13.4%
프 213
13.4%
빗 116
 
7.3%
물 116
 
7.3%
수 91
 
5.7%
배 88
 
5.5%
산 24
 
1.5%
동 20
 
1.3%
이 15
 
0.9%
Other values (153) 466
29.3%
Common
ValueCountFrequency (%)
2 25
31.6%
1 24
30.4%
3 10
 
12.7%
4 9
 
11.4%
7
 
8.9%
- 3
 
3.8%
5 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1591
95.3%
ASCII 79
 
4.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 229
14.4%
펌 213
13.4%
프 213
13.4%
빗 116
 
7.3%
물 116
 
7.3%
수 91
 
5.7%
배 88
 
5.5%
산 24
 
1.5%
동 20
 
1.3%
이 15
 
0.9%
Other values (153) 466
29.3%
ASCII
ValueCountFrequency (%)
2 25
31.6%
1 24
30.4%
3 10
 
12.7%
4 9
 
11.4%
7
 
8.9%
- 3
 
3.8%
5 1
 
1.3%

펌프장구분명
Categorical

Distinct50
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
도시침수방지
108 
<NA>
53 
농업기반공사
 
4
농경지(0)ha가옥(1,200)호인구(4,200)명
 
4
고성군
 
3
Other values (45)
48 

Length

Max length35
Median length6
Mean length9.05
Min length3

Unique

Unique42 ?
Unique (%)19.1%

Sample

1st row도시침수방지
2nd row농업기반공사
3rd row하동군
4th row도시침수방지
5th row하동군

Common Values

ValueCountFrequency (%)
도시침수방지 108
49.1%
<NA> 53
24.1%
농업기반공사 4
 
1.8%
농경지(0)ha가옥(1,200)호인구(4,200)명 4
 
1.8%
고성군 3
 
1.4%
상주시 2
 
0.9%
농경지(1)ha가옥(1,500)호인구(4,500)명 2
 
0.9%
하동군 2
 
0.9%
농경지24ha가옥8호 1
 
0.5%
농경지(0)ha가옥(758)호인구(2,150)명 1
 
0.5%
Other values (40) 40
 
18.2%

Length

2023-12-13T06:59:25.432401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도시침수방지 108
49.1%
na 53
24.1%
농업기반공사 4
 
1.8%
농경지(0)ha가옥(1,200)호인구(4,200)명 4
 
1.8%
고성군 3
 
1.4%
상주시 2
 
0.9%
농경지(1)ha가옥(1,500)호인구(4,500)명 2
 
0.9%
하동군 2
 
0.9%
농경지(1,230)ha가옥(20,000)호인구(100,000)명 1
 
0.5%
농경지(0)ha가옥(90)호인구(360)명 1
 
0.5%
Other values (40) 40
 
18.2%

배수면적
Real number (ℝ)

ZEROS 

Distinct179
Distinct (%)81.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1717002.2
Minimum0
Maximum72140000
Zeros6
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T06:59:25.542566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.92
Q168.625
median371.35
Q3250000
95-th percentile6944500
Maximum72140000
Range72140000
Interquartile range (IQR)249931.38

Descriptive statistics

Standard deviation7702913.6
Coefficient of variation (CV)4.4862573
Kurtosis57.418771
Mean1717002.2
Median Absolute Deviation (MAD)362.15
Skewness7.2331129
Sum3.7774048 × 108
Variance5.9334879 × 1013
MonotonicityNot monotonic
2023-12-13T06:59:25.662477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
577200.0 7
 
3.2%
0.0 6
 
2.7%
200000.0 4
 
1.8%
687000.0 4
 
1.8%
250.0 3
 
1.4%
39.0 2
 
0.9%
370000.0 2
 
0.9%
1034000.0 2
 
0.9%
250000.0 2
 
0.9%
121.0 2
 
0.9%
Other values (169) 186
84.5%
ValueCountFrequency (%)
0.0 6
2.7%
1.0 1
 
0.5%
2.4 1
 
0.5%
2.7 1
 
0.5%
3.0 1
 
0.5%
4.4 1
 
0.5%
6.0 1
 
0.5%
6.21 1
 
0.5%
8.0 1
 
0.5%
9.0 1
 
0.5%
ValueCountFrequency (%)
72140000.0 1
0.5%
66340000.0 1
0.5%
38160000.0 1
0.5%
36300000.0 1
0.5%
17150000.0 1
0.5%
17000000.0 1
0.5%
10314000.0 1
0.5%
8100000.0 1
0.5%
7700000.0 2
0.9%
7600000.0 1
0.5%

처리능력
Text

MISSING 

Distinct187
Distinct (%)87.0%
Missing5
Missing (%)2.3%
Memory size1.8 KiB
2023-12-13T06:59:25.882122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length11.502326
Min length2

Characters and Unicode

Total characters2473
Distinct characters24
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique169 ?
Unique (%)78.6%

Sample

1st row총390㎥/분, 130㎥/분×3대
2nd row총 276㎥/분,138㎥/분X2대
3rd row총24㎥/분, 12㎥/분x2대
4th row총138㎥/분, 46㎥/분×3대
5th row총52㎥/분, 52㎥/분x1대
ValueCountFrequency (%)
570(95x6 8
 
2.2%
180x3 5
 
1.4%
142/분x3 4
 
1.1%
120/분x2 4
 
1.1%
70/분x1 4
 
1.1%
30x1 4
 
1.1%
총736/분 4
 
1.1%
30/분x2 3
 
0.8%
20/분x2 3
 
0.8%
30/분x1 3
 
0.8%
Other values (269) 314
88.2%
2023-12-13T06:59:26.261108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 316
12.8%
X 262
10.6%
1 217
 
8.8%
2 201
 
8.1%
175
 
7.1%
/ 172
 
7.0%
분 166
 
6.7%
3 165
 
6.7%
5 136
 
5.5%
4 91
 
3.7%
Other values (14) 572
23.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1398
56.5%
Other Punctuation 274
 
11.1%
Uppercase Letter 262
 
10.6%
Other Letter 247
 
10.0%
Space Separator 175
 
7.1%
Other Symbol 35
 
1.4%
Close Punctuation 33
 
1.3%
Open Punctuation 33
 
1.3%
Math Symbol 11
 
0.4%
Lowercase Letter 5
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 316
22.6%
1 217
15.5%
2 201
14.4%
3 165
11.8%
5 136
9.7%
4 91
 
6.5%
6 79
 
5.7%
8 68
 
4.9%
7 63
 
4.5%
9 62
 
4.4%
Other Punctuation
ValueCountFrequency (%)
/ 172
62.8%
, 76
27.7%
? 21
 
7.7%
. 5
 
1.8%
Other Letter
ValueCountFrequency (%)
분 166
67.2%
총 59
 
23.9%
대 22
 
8.9%
Uppercase Letter
ValueCountFrequency (%)
X 262
100.0%
Space Separator
ValueCountFrequency (%)
175
100.0%
Other Symbol
ValueCountFrequency (%)
㎥ 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Math Symbol
ValueCountFrequency (%)
× 11
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1959
79.2%
Latin 267
 
10.8%
Hangul 247
 
10.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 316
16.1%
1 217
11.1%
2 201
10.3%
175
8.9%
/ 172
8.8%
3 165
8.4%
5 136
6.9%
4 91
 
4.6%
6 79
 
4.0%
, 76
 
3.9%
Other values (9) 331
16.9%
Hangul
ValueCountFrequency (%)
분 166
67.2%
총 59
 
23.9%
대 22
 
8.9%
Latin
ValueCountFrequency (%)
X 262
98.1%
x 5
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2180
88.2%
Hangul 247
 
10.0%
CJK Compat 35
 
1.4%
None 11
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 316
14.5%
X 262
12.0%
1 217
10.0%
2 201
9.2%
175
8.0%
/ 172
7.9%
3 165
7.6%
5 136
 
6.2%
4 91
 
4.2%
6 79
 
3.6%
Other values (9) 366
16.8%
Hangul
ValueCountFrequency (%)
분 166
67.2%
총 59
 
23.9%
대 22
 
8.9%
CJK Compat
ValueCountFrequency (%)
㎥ 35
100.0%
None
ValueCountFrequency (%)
× 11
100.0%

모터시설규모
Text

Distinct191
Distinct (%)86.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-13T06:59:26.479393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length10.645455
Min length4

Characters and Unicode

Total characters2342
Distinct characters37
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique173 ?
Unique (%)78.6%

Sample

1st row300HP×1대200HP×2대
2nd row500HPX2대
3rd row25HPx2대
4th row150HP×3대
5th row167HPx1대175HPx1대
ValueCountFrequency (%)
× 36
 
7.1%
3 36
 
7.1%
2 25
 
4.9%
4 16
 
3.2%
1 14
 
2.8%
총3 12
 
2.4%
5 10
 
2.0%
450 10
 
2.0%
총4 8
 
1.6%
총2 8
 
1.6%
Other values (205) 331
65.4%
2023-12-13T06:59:26.833117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 449
19.2%
292
12.5%
5 174
 
7.4%
2 169
 
7.2%
1 144
 
6.1%
3 142
 
6.1%
/ 111
 
4.7%
? 105
 
4.5%
4 91
 
3.9%
, 75
 
3.2%
Other values (27) 590
25.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1346
57.5%
Space Separator 292
 
12.5%
Other Punctuation 291
 
12.4%
Uppercase Letter 128
 
5.5%
Other Letter 123
 
5.3%
Math Symbol 69
 
2.9%
Close Punctuation 36
 
1.5%
Open Punctuation 36
 
1.5%
Lowercase Letter 18
 
0.8%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 449
33.4%
5 174
 
12.9%
2 169
 
12.6%
1 144
 
10.7%
3 142
 
10.5%
4 91
 
6.8%
6 72
 
5.3%
7 53
 
3.9%
8 36
 
2.7%
9 16
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
p 8
44.4%
x 3
 
16.7%
a 2
 
11.1%
n 2
 
11.1%
b 1
 
5.6%
h 1
 
5.6%
e 1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
X 55
43.0%
H 35
27.3%
P 28
21.9%
E 7
 
5.5%
J 2
 
1.6%
F 1
 
0.8%
Other Letter
ValueCountFrequency (%)
총 53
43.1%
수 35
28.5%
대 32
26.0%
년 1
 
0.8%
증 1
 
0.8%
설 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
/ 111
38.1%
? 105
36.1%
, 75
25.8%
Space Separator
ValueCountFrequency (%)
292
100.0%
Math Symbol
ValueCountFrequency (%)
× 69
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2073
88.5%
Latin 146
 
6.2%
Hangul 123
 
5.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 449
21.7%
292
14.1%
5 174
 
8.4%
2 169
 
8.2%
1 144
 
6.9%
3 142
 
6.8%
/ 111
 
5.4%
? 105
 
5.1%
4 91
 
4.4%
, 75
 
3.6%
Other values (8) 321
15.5%
Latin
ValueCountFrequency (%)
X 55
37.7%
H 35
24.0%
P 28
19.2%
p 8
 
5.5%
E 7
 
4.8%
x 3
 
2.1%
J 2
 
1.4%
a 2
 
1.4%
n 2
 
1.4%
b 1
 
0.7%
Other values (3) 3
 
2.1%
Hangul
ValueCountFrequency (%)
총 53
43.1%
수 35
28.5%
대 32
26.0%
년 1
 
0.8%
증 1
 
0.8%
설 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2150
91.8%
Hangul 123
 
5.3%
None 69
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 449
20.9%
292
13.6%
5 174
 
8.1%
2 169
 
7.9%
1 144
 
6.7%
3 142
 
6.6%
/ 111
 
5.2%
? 105
 
4.9%
4 91
 
4.2%
, 75
 
3.5%
Other values (20) 398
18.5%
None
ValueCountFrequency (%)
× 69
100.0%
Hangul
ValueCountFrequency (%)
총 53
43.1%
수 35
28.5%
대 32
26.0%
년 1
 
0.8%
증 1
 
0.8%
설 1
 
0.8%

펌프시설규모
Text

MISSING 

Distinct150
Distinct (%)69.8%
Missing5
Missing (%)2.3%
Memory size1.8 KiB
2023-12-13T06:59:27.028388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length9.655814
Min length3

Characters and Unicode

Total characters2076
Distinct characters22
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)55.8%

Sample

1st row1,200mm×1대
2nd row1000MMX2대
3rd row300MMx2대
4th row600mm×3대
5th row700MMx1대350MMx1대
ValueCountFrequency (%)
1,500 23
 
6.9%
1,200 16
 
4.8%
1,000 16
 
4.8%
총3 13
 
3.9%
총2 11
 
3.3%
900 10
 
3.0%
총4 9
 
2.7%
900x6 7
 
2.1%
1,100 7
 
2.1%
총6 7
 
2.1%
Other values (134) 214
64.3%
2023-12-13T06:59:27.353211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 620
29.9%
1 239
 
11.5%
, 177
 
8.5%
? 151
 
7.3%
/ 119
 
5.7%
118
 
5.7%
2 107
 
5.2%
5 103
 
5.0%
3 70
 
3.4%
총 52
 
2.5%
Other values (12) 320
15.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1323
63.7%
Other Punctuation 447
 
21.5%
Space Separator 118
 
5.7%
Other Letter 80
 
3.9%
Uppercase Letter 54
 
2.6%
Lowercase Letter 47
 
2.3%
Math Symbol 5
 
0.2%
Other Symbol 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 620
46.9%
1 239
 
18.1%
2 107
 
8.1%
5 103
 
7.8%
3 70
 
5.3%
4 44
 
3.3%
8 43
 
3.3%
6 42
 
3.2%
7 28
 
2.1%
9 27
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 177
39.6%
? 151
33.8%
/ 119
26.6%
Other Letter
ValueCountFrequency (%)
총 52
65.0%
대 28
35.0%
Uppercase Letter
ValueCountFrequency (%)
X 46
85.2%
M 8
 
14.8%
Lowercase Letter
ValueCountFrequency (%)
m 44
93.6%
x 3
 
6.4%
Space Separator
ValueCountFrequency (%)
118
100.0%
Math Symbol
ValueCountFrequency (%)
× 5
100.0%
Other Symbol
ValueCountFrequency (%)
㎜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1895
91.3%
Latin 101
 
4.9%
Hangul 80
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 620
32.7%
1 239
 
12.6%
, 177
 
9.3%
? 151
 
8.0%
/ 119
 
6.3%
118
 
6.2%
2 107
 
5.6%
5 103
 
5.4%
3 70
 
3.7%
4 44
 
2.3%
Other values (6) 147
 
7.8%
Latin
ValueCountFrequency (%)
X 46
45.5%
m 44
43.6%
M 8
 
7.9%
x 3
 
3.0%
Hangul
ValueCountFrequency (%)
총 52
65.0%
대 28
35.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1989
95.8%
Hangul 80
 
3.9%
None 5
 
0.2%
CJK Compat 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 620
31.2%
1 239
 
12.0%
, 177
 
8.9%
? 151
 
7.6%
/ 119
 
6.0%
118
 
5.9%
2 107
 
5.4%
5 103
 
5.2%
3 70
 
3.5%
X 46
 
2.3%
Other values (8) 239
 
12.0%
Hangul
ValueCountFrequency (%)
총 52
65.0%
대 28
35.0%
None
ValueCountFrequency (%)
× 5
100.0%
CJK Compat
ValueCountFrequency (%)
㎜ 2
100.0%

계획년도
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)3.3%
Missing7
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean16.28169
Minimum2
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T06:59:27.466021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q110
median10
Q320
95-th percentile38
Maximum50
Range48
Interquartile range (IQR)10

Descriptive statistics

Standard deviation10.649896
Coefficient of variation (CV)0.65410258
Kurtosis2.8055674
Mean16.28169
Median Absolute Deviation (MAD)5
Skewness1.6813966
Sum3468
Variance113.42028
MonotonicityNot monotonic
2023-12-13T06:59:27.581874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
10 105
47.7%
20 55
25.0%
30 22
 
10.0%
5 18
 
8.2%
50 11
 
5.0%
16 1
 
0.5%
2 1
 
0.5%
(Missing) 7
 
3.2%
ValueCountFrequency (%)
2 1
 
0.5%
5 18
 
8.2%
10 105
47.7%
16 1
 
0.5%
20 55
25.0%
30 22
 
10.0%
50 11
 
5.0%
ValueCountFrequency (%)
50 11
 
5.0%
30 22
 
10.0%
20 55
25.0%
16 1
 
0.5%
10 105
47.7%
5 18
 
8.2%
2 1
 
0.5%

설치년도
Categorical

Distinct40
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2000
21 
1993
19 
1
17 
2002
14 
1992
 
13
Other values (35)
136 

Length

Max length4
Median length4
Mean length3.7454545
Min length1

Unique

Unique10 ?
Unique (%)4.5%

Sample

1st row1991
2nd row2001
3rd row1999
4th row1990
5th row1995

Common Values

ValueCountFrequency (%)
2000 21
 
9.5%
1993 19
 
8.6%
1 17
 
7.7%
2002 14
 
6.4%
1992 13
 
5.9%
1989 10
 
4.5%
2003 10
 
4.5%
2001 9
 
4.1%
1990 8
 
3.6%
1985 7
 
3.2%
Other values (30) 92
41.8%

Length

2023-12-13T06:59:27.725021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2000 21
 
9.5%
1993 19
 
8.6%
1 17
 
7.7%
2002 14
 
6.4%
1992 13
 
5.9%
1989 10
 
4.5%
2003 10
 
4.5%
2001 9
 
4.1%
1990 8
 
3.6%
1985 7
 
3.2%
Other values (30) 92
41.8%

관리자
Text

MISSING 

Distinct58
Distinct (%)26.9%
Missing4
Missing (%)1.8%
Memory size1.8 KiB
2023-12-13T06:59:27.932167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.5231481
Min length1

Characters and Unicode

Total characters977
Distinct characters74
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)9.3%

Sample

1st row하동군수
2nd row농기공위탁
3rd row하동군수
4th row하동군수
5th row하동군수
ValueCountFrequency (%)
파주시장 19
 
8.8%
동대문구청 13
 
6.0%
용산구청장 11
 
5.1%
마포구청장 10
 
4.6%
성동구청장 9
 
4.2%
동두천시장 8
 
3.7%
영등포구청 8
 
3.7%
김포시장 7
 
3.2%
고양시장 7
 
3.2%
구로구청장 6
 
2.8%
Other values (48) 118
54.6%
2023-12-13T06:59:28.320070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 152
15.6%
구 112
 
11.5%
청 102
 
10.4%
시 83
 
8.5%
동 44
 
4.5%
주 33
 
3.4%
파 25
 
2.6%
포 25
 
2.6%
양 20
 
2.0%
수 19
 
1.9%
Other values (64) 362
37.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 973
99.6%
Other Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 152
15.6%
구 112
 
11.5%
청 102
 
10.5%
시 83
 
8.5%
동 44
 
4.5%
주 33
 
3.4%
파 25
 
2.6%
포 25
 
2.6%
양 20
 
2.1%
수 19
 
2.0%
Other values (62) 358
36.8%
Other Punctuation
ValueCountFrequency (%)
〃 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 973
99.6%
Common 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 152
15.6%
구 112
 
11.5%
청 102
 
10.5%
시 83
 
8.5%
동 44
 
4.5%
주 33
 
3.4%
파 25
 
2.6%
포 25
 
2.6%
양 20
 
2.1%
수 19
 
2.0%
Other values (62) 358
36.8%
Common
ValueCountFrequency (%)
〃 2
50.0%
( 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 973
99.6%
None 2
 
0.2%
ASCII 2
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 152
15.6%
구 112
 
11.5%
청 102
 
10.5%
시 83
 
8.5%
동 44
 
4.5%
주 33
 
3.4%
파 25
 
2.6%
포 25
 
2.6%
양 20
 
2.1%
수 19
 
2.0%
Other values (62) 358
36.8%
None
ValueCountFrequency (%)
〃 2
100.0%
ASCII
ValueCountFrequency (%)
( 2
100.0%

설치자
Categorical

HIGH CARDINALITY 

Distinct51
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
서울시장
52 
파주시장
19 
용산구청장
 
11
서울특별시
 
9
동두천시장
 
8
Other values (46)
121 

Length

Max length5
Median length4
Mean length4.2909091
Min length1

Unique

Unique17 ?
Unique (%)7.7%

Sample

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

Common Values

ValueCountFrequency (%)
서울시장 52
23.6%
파주시장 19
 
8.6%
용산구청장 11
 
5.0%
서울특별시 9
 
4.1%
동두천시장 8
 
3.6%
구로구청장 8
 
3.6%
남양주시장 7
 
3.2%
양평군수 7
 
3.2%
김포시장 7
 
3.2%
하동군수 5
 
2.3%
Other values (41) 87
39.5%

Length

2023-12-13T06:59:28.449939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울시장 52
23.6%
파주시장 19
 
8.6%
용산구청장 11
 
5.0%
서울특별시 9
 
4.1%
동두천시장 8
 
3.6%
구로구청장 8
 
3.6%
남양주시장 7
 
3.2%
양평군수 7
 
3.2%
김포시장 7
 
3.2%
하동군수 5
 
2.3%
Other values (41) 87
39.5%

하천명
Text

MISSING 

Distinct71
Distinct (%)33.0%
Missing5
Missing (%)2.3%
Memory size1.8 KiB
2023-12-13T06:59:28.701818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.627907
Min length1

Characters and Unicode

Total characters1640
Distinct characters98
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)16.3%

Sample

1st row관곡천(지방2급)
2nd row섬진강(국가)
3rd row횡천천(지방2급)
4th row섬진강(국가)
5th row횡천천(지방2급)
ValueCountFrequency (%)
한강(국가 35
 
16.3%
중랑천(국가 17
 
7.9%
안양천(국가 15
 
7.0%
왕숙천(지방2급 10
 
4.7%
문산천(국가하천 9
 
4.2%
남한강(국가 8
 
3.7%
신천(지방2급 8
 
3.7%
도림천(지방2급 6
 
2.8%
성내천(지방2급 4
 
1.9%
계양천(지방2급하천 4
 
1.9%
Other values (61) 99
46.0%
2023-12-13T06:59:29.113761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 205
12.5%
) 205
12.5%
천 184
11.2%
국 101
 
6.2%
가 100
 
6.1%
지 99
 
6.0%
방 98
 
6.0%
2 94
 
5.7%
급 92
 
5.6%
강 47
 
2.9%
Other values (88) 415
25.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1130
68.9%
Open Punctuation 205
 
12.5%
Close Punctuation 205
 
12.5%
Decimal Number 99
 
6.0%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 184
16.3%
국 101
 
8.9%
가 100
 
8.8%
지 99
 
8.8%
방 98
 
8.7%
급 92
 
8.1%
강 47
 
4.2%
한 43
 
3.8%
하 25
 
2.2%
양 23
 
2.0%
Other values (83) 318
28.1%
Decimal Number
ValueCountFrequency (%)
2 94
94.9%
1 5
 
5.1%
Open Punctuation
ValueCountFrequency (%)
( 205
100.0%
Close Punctuation
ValueCountFrequency (%)
) 205
100.0%
Other Punctuation
ValueCountFrequency (%)
〃 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1130
68.9%
Common 510
31.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 184
16.3%
국 101
 
8.9%
가 100
 
8.8%
지 99
 
8.8%
방 98
 
8.7%
급 92
 
8.1%
강 47
 
4.2%
한 43
 
3.8%
하 25
 
2.2%
양 23
 
2.0%
Other values (83) 318
28.1%
Common
ValueCountFrequency (%)
( 205
40.2%
) 205
40.2%
2 94
18.4%
1 5
 
1.0%
〃 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1130
68.9%
ASCII 509
31.0%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 205
40.3%
) 205
40.3%
2 94
18.5%
1 5
 
1.0%
Hangul
ValueCountFrequency (%)
천 184
16.3%
국 101
 
8.9%
가 100
 
8.8%
지 99
 
8.8%
방 98
 
8.7%
급 92
 
8.1%
강 47
 
4.2%
한 43
 
3.8%
하 25
 
2.2%
양 23
 
2.0%
Other values (83) 318
28.1%
None
ValueCountFrequency (%)
〃 1
100.0%

유수지용량
Real number (ℝ)

ZEROS 

Distinct132
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61770.209
Minimum0
Maximum4238000
Zeros58
Zeros (%)26.4%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T06:59:29.293543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4250
Q330000
95-th percentile170400
Maximum4238000
Range4238000
Interquartile range (IQR)30000

Descriptive statistics

Standard deviation331958.34
Coefficient of variation (CV)5.3740847
Kurtosis124.87604
Mean61770.209
Median Absolute Deviation (MAD)4250
Skewness10.700695
Sum13589446
Variance1.1019634 × 1011
MonotonicityNot monotonic
2023-12-13T06:59:29.433793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 58
26.4%
12000 9
 
4.1%
4500 4
 
1.8%
7325 4
 
1.8%
8000 3
 
1.4%
20800 2
 
0.9%
1344 2
 
0.9%
31800 2
 
0.9%
2250 2
 
0.9%
123000 2
 
0.9%
Other values (122) 132
60.0%
ValueCountFrequency (%)
0 58
26.4%
36 1
 
0.5%
53 1
 
0.5%
63 1
 
0.5%
67 1
 
0.5%
96 1
 
0.5%
105 1
 
0.5%
136 1
 
0.5%
150 1
 
0.5%
190 1
 
0.5%
ValueCountFrequency (%)
4238000 1
0.5%
2332000 1
0.5%
700000 1
0.5%
551000 1
0.5%
323040 1
0.5%
300000 1
0.5%
261000 1
0.5%
238000 1
0.5%
237000 1
0.5%
235000 1
0.5%

에프17
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
1
220 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 220
100.0%

Length

2023-12-13T06:59:29.595345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:59:29.688632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 220
100.0%

좌표X
Real number (ℝ)

Distinct217
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean205899.24
Minimum167759
Maximum348439
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T06:59:29.814315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum167759
5-th percentile176024.5
Q1188118.75
median199784.5
Q3207184.25
95-th percentile279108.2
Maximum348439
Range180680
Interquartile range (IQR)19065.5

Descriptive statistics

Standard deviation32220.489
Coefficient of variation (CV)0.15648668
Kurtosis5.8688722
Mean205899.24
Median Absolute Deviation (MAD)10544
Skewness2.322838
Sum45297833
Variance1.0381599 × 109
MonotonicityNot monotonic
2023-12-13T06:59:29.955240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
325243 2
 
0.9%
213063 2
 
0.9%
181147 2
 
0.9%
282646 1
 
0.5%
205961 1
 
0.5%
188136 1
 
0.5%
202925 1
 
0.5%
185544 1
 
0.5%
212723 1
 
0.5%
191365 1
 
0.5%
Other values (207) 207
94.1%
ValueCountFrequency (%)
167759 1
0.5%
168330 1
0.5%
169828 1
0.5%
170088 1
0.5%
170506 1
0.5%
170722 1
0.5%
171373 1
0.5%
171983 1
0.5%
172851 1
0.5%
173649 1
0.5%
ValueCountFrequency (%)
348439 1
0.5%
343773 1
0.5%
325385 1
0.5%
325243 2
0.9%
315703 1
0.5%
309547 1
0.5%
305799 1
0.5%
282646 1
0.5%
279909 1
0.5%
279853 1
0.5%

좌표Y
Real number (ℝ)

Distinct216
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean438123.08
Minimum169913
Maximum548665
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T06:59:30.117837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum169913
5-th percentile330957.1
Q1442809.5
median448886
Q3456859.25
95-th percentile489526
Maximum548665
Range378752
Interquartile range (IQR)14049.75

Descriptive statistics

Standard deviation60936.921
Coefficient of variation (CV)0.13908631
Kurtosis10.281466
Mean438123.08
Median Absolute Deviation (MAD)6853
Skewness-3.0160512
Sum96387078
Variance3.7133083 × 109
MonotonicityNot monotonic
2023-12-13T06:59:30.252518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
541182 2
 
0.9%
198950 2
 
0.9%
483795 2
 
0.9%
447768 2
 
0.9%
169913 1
 
0.5%
454601 1
 
0.5%
452521 1
 
0.5%
452684 1
 
0.5%
452696 1
 
0.5%
452790 1
 
0.5%
Other values (206) 206
93.6%
ValueCountFrequency (%)
169913 1
0.5%
173700 1
0.5%
173770 1
0.5%
174926 1
0.5%
175545 1
0.5%
183112 1
0.5%
198950 2
0.9%
243690 1
0.5%
246481 1
0.5%
328299 1
0.5%
ValueCountFrequency (%)
548665 1
0.5%
541182 2
0.9%
523149 1
0.5%
512921 1
0.5%
505801 1
0.5%
496457 1
0.5%
495063 1
0.5%
491102 1
0.5%
490632 1
0.5%
489849 1
0.5%

심볼코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
poi_08
220 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowpoi_08
2nd rowpoi_08
3rd rowpoi_08
4th rowpoi_08
5th rowpoi_08

Common Values

ValueCountFrequency (%)
poi_08 220
100.0%

Length

2023-12-13T06:59:30.388428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:59:30.487117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
poi_08 220
100.0%

널값
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing220
Missing (%)100.0%
Memory size2.1 KiB

지오메트리
Text

Distinct217
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-13T06:59:30.728198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length42
Mean length42
Min length42

Characters and Unicode

Total characters9240
Distinct characters16
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

Unique214 ?
Unique (%)97.3%

Sample

1st row01010000005621500AD3F95F406E71758B2C834140
2nd row010100000018C24D47D4F05F40B8FB96B8AA874140
3rd row0101000000422E9CA9E9F15F4073F26FDCBB874140
4th row0101000000859308723CEF5F408102FBE019894140
5th row01010000007FF2A081B9F15F40433E6FBAC8894140
ValueCountFrequency (%)
0101000000aeb325fac90d6040d9587c6cb82e4340 2
 
0.9%
0101000000b04d6eaf0ec95f4038f5c39518a54140 2
 
0.9%
0101000000afb4909627b25f4025c9fa8ca3ed4240 2
 
0.9%
0101000000f634bce10a16604089f16c567c054340 1
 
0.5%
0101000000a3ec6dc473c95f40eb307c2181cd4240 1
 
0.5%
0101000000b5439ac16ab25f4075743f287dcd4240 1
 
0.5%
01010000005621500ad3f95f406e71758b2c834140 1
 
0.5%
0101000000fd2e8a7c83c95f403a492c7fdbcb4240 1
 
0.5%
0101000000e197ac54afb95f40ffaa0af17bc94240 1
 
0.5%
010100000057ba7b2445b75f4055f4247a96c94240 1
 
0.5%
Other values (207) 207
94.1%
2023-12-13T06:59:31.076827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2468
26.7%
4 982
 
10.6%
1 757
 
8.2%
F 529
 
5.7%
5 525
 
5.7%
2 509
 
5.5%
C 493
 
5.3%
B 435
 
4.7%
D 352
 
3.8%
3 333
 
3.6%
Other values (6) 1857
20.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6817
73.8%
Uppercase Letter 2423
 
26.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2468
36.2%
4 982
 
14.4%
1 757
 
11.1%
5 525
 
7.7%
2 509
 
7.5%
3 333
 
4.9%
9 330
 
4.8%
7 314
 
4.6%
8 302
 
4.4%
6 297
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
F 529
21.8%
C 493
20.3%
B 435
18.0%
D 352
14.5%
A 322
13.3%
E 292
12.1%

Most occurring scripts

ValueCountFrequency (%)
Common 6817
73.8%
Latin 2423
 
26.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2468
36.2%
4 982
 
14.4%
1 757
 
11.1%
5 525
 
7.7%
2 509
 
7.5%
3 333
 
4.9%
9 330
 
4.8%
7 314
 
4.6%
8 302
 
4.4%
6 297
 
4.4%
Latin
ValueCountFrequency (%)
F 529
21.8%
C 493
20.3%
B 435
18.0%
D 352
14.5%
A 322
13.3%
E 292
12.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9240
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2468
26.7%
4 982
 
10.6%
1 757
 
8.2%
F 529
 
5.7%
5 525
 
5.7%
2 509
 
5.5%
C 493
 
5.3%
B 435
 
4.7%
D 352
 
3.8%
3 333
 
3.6%
Other values (6) 1857
20.1%

Sample

공간정보일렬번호행정구역아이디상세주소펌프장명펌프장구분명배수면적처리능력모터시설규모펌프시설규모계획년도설치년도관리자설치자하천명유수지용량에프17좌표X좌표Y심볼코드널값지오메트리
014885037021경상남도 하동군 진교면 진교리 302-153진교시가지배수장도시침수방지39.0총390㎥/분, 130㎥/분×3대300HP×1대200HP×2대1,200mm×1대501991하동군수하동군수관곡천(지방2급)45001282646169913poi_08<NA>01010000005621500AD3F95F406E71758B2C834140
124885025024경상남도 하동군 하동읍 신기리 418-3신기배수장농업기반공사675.0총 276㎥/분,138㎥/분X2대500HPX2대1000MMX2대202001농기공위탁하동군수섬진강(국가)01269789173700poi_08<NA>010100000018C24D47D4F05F40B8FB96B8AA874140
234885033026경상남도 하동군 적량면 고절리 1173중도들배수장하동군130.0총24㎥/분, 12㎥/분x2대25HPx2대300MMx2대101999하동군수하동군수횡천천(지방2급)01271333173770poi_08<NA>0101000000422E9CA9E9F15F4073F26FDCBB874140
344885025021경상남도 하동군 하동읍 읍내리 1563-8동해량배수장도시침수방지10.0총138㎥/분, 46㎥/분×3대150HP×3대600mm×3대501990하동군수하동군수섬진강(국가)01267509174926poi_08<NA>0101000000859308723CEF5F408102FBE019894140
454885033025경상남도 하동군 적량면 동산리 184-2동산배수장하동군85.0총52㎥/분, 52㎥/분x1대167HPx1대175HPx1대700MMx1대350MMx1대201995하동군수하동군수횡천천(지방2급)01271051175545poi_08<NA>01010000007FF2A081B9F15F40433E6FBAC8894140
564672033000전라남도 곡성 석곡 석곡 159-2석곡배수펌프장도시침수방지3.012㎥/분X1대Feb-35300/1101987곡성군수곡성군수보성강(국가)45001222242183112poi_08<NA>0101000000AC9E7CEE7CCF5F40596E848ACD924140
674672037000전라남도 곡성 옥과 리문 155-13리문배수펌프장도시침수방지6.015㎥/분X1대Jan-35400/1101993〃〃옥과천(지방2급)50001213063198950poi_08<NA>0101000000B04D6EAF0EC95F4038F5C39518A54140
784672037000전라남도 곡성 옥과 무림 165무림배수펌프장도시침수방지31.015㎥/분X1대15/130/2300/3102001〃〃〃45001213063198950poi_08<NA>0101000000B04D6EAF0EC95F4038F5C39518A54140
894518025021전라북도 정읍시 신태인 화봉리 531-1신태인신시가지배수펌프장농업기반공사1323.0총1020㎥/분204㎥/분×5대220hp×5대1300㎜×5대201984직접관리농업기반공동진강(국가)2350001189424243690poi_08<NA>0101000000E72BC36D63B85F40405E07F6B6D84140
9104518040028전라북도 정읍시 감곡면 화봉리 531-1화봉배수장시군구200.0276㎥/분92㎥/분×3대125Hp×3대900mm/3대201998정읍시장정읍시장감곡천19411194091246481poi_08<NA>0101000000C4E77BE1AFBB5F403382AC82F0DB4140
공간정보일렬번호행정구역아이디상세주소펌프장명펌프장구분명배수면적처리능력모터시설규모펌프시설규모계획년도설치년도관리자설치자하천명유수지용량에프17좌표X좌표Y심볼코드널값지오메트리
2102114125011200경기도 동두천시 상패동 1-15상패1빗물펌프장농경지(0)ha가옥(50)호인구(235)명17100.0총25/분 15/분X1 10/분X1총2 40/1 30/1총2 15/1 10/151동두천시장동두천시장신천(지방2급)1051204539490632poi_08<NA>0101000000751CA13F2BC35F40E4CB84098CF54240
2112124125010600경기도 동두천시 보산동 459-44보산1빗물펌프장농경지(0)ha가옥(150)호인구(560)명32900.0총20/분 10/분X2총2 25/2총2 10/251동두천시장동두천시장신천(지방2급)3681204863491102poi_08<NA>0101000000F63A9CAB67C35F40E0974BBC16F64240
2122134125011000경기도 동두천시 하봉암동 324-1소요2빗물펌프장농경지(0)ha가옥(100)호인구(384)명33700.0총45/분 30/분X1 15/분X1총2 60/1 40/1총2 30/1 15/151동두천시장동두천시장신천(지방2급)531205339495063poi_08<NA>01010000004AE5DBD7C0C35F40B71CD900A8FA4240
2132144125011000경기도 동두천시 하봉암동 92-25소요3빗물펌프장농경지(0)ha가옥(140)호인구(361)명130200.0총90/분 50/분X1 20/분X2총3 100/1 50/2총3 50/1 20/251동두천시장동두천시장신천(지방2급)961205603496457poi_08<NA>010100000034F7873CF2C35F4060AD837B43FC4240
2142154283032042강원도 양양군 손양면 상운리 94-3상운배수펌프장양양군63.48114㎥/분x2대 18㎥/분x2대175Hp/2대 30Hp/2대<NA>201997양양군수양양군수여운포천(소하천)48001348439505801poi_08<NA>0101000000F634BCE10A16604089F16C567C054340
2152164283025029강원도 양양군 양양읍 조산리 383조산빗물펌프장농업기반공사147.2960㎥/분200Hp/5대1200mm/5대201992농업기반공농업기반공양양남대천(지방1)13531343773512921poi_08<NA>0101000000EDF8B9566314604082214504CA0D4340
2162174278025922강원도 철원군 동송읍 오덕리 949-12오덕 배수펌프장철원군658.042㎥/분80HP×6대250㎜/6대202002철원군수철원군수대교천(지방2)22501219622523149poi_08<NA>0101000000C117723134CE5F40D93ED6CE041B4340
2172184282025000강원도 고성군 간성읍 동호 13동호1배수펌프장고성군45.672㎥/분50Hp/2대550mm/2대501999고성군수고성군수남천(지방2)2301325243541182poi_08<NA>0101000000AEB325FAC90D6040D9587C6CB82E4340
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2192204282025300강원도 고성군 거진읍 송죽 33송죽배수펌프장고성군38.072㎥/분50Hp/2대850mm/2대501984고성군수고성군수북천(지방2)1901325385548665poi_08<NA>010100000006B5C931E20D6040D261EE0358374340