Overview

Dataset statistics

Number of variables23
Number of observations100
Missing cells285
Missing cells (%)12.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.9 KiB
Average record size in memory193.3 B

Variable types

Numeric7
Categorical4
Text9
Boolean1
DateTime2

Alerts

use_at has constant value ""Constant
bizr_no is highly imbalanced (86.1%)Imbalance
fax_no has 2 (2.0%) missing valuesMissing
hmpg_url has 70 (70.0%) missing valuesMissing
map_url has 73 (73.0%) missing valuesMissing
tfcmn_tfcmn has 75 (75.0%) missing valuesMissing
charger_psitn_dept has 65 (65.0%) missing valuesMissing
fclty_grp_sn has unique valuesUnique
fclty_grp_nm has unique valuesUnique
charger_email_pre has unique valuesUnique
regist_dt has unique valuesUnique
updt_dt has unique valuesUnique
fax_no has 2 (2.0%) zerosZeros

Reproduction

Analysis started2023-12-10 10:11:02.365555
Analysis finished2023-12-10 10:11:03.769508
Duration1.4 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

fclty_grp_sn
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55925.98
Minimum55705
Maximum56157
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:11:04.336479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum55705
5-th percentile55776.95
Q155807.75
median55850
Q356062.5
95-th percentile56133.15
Maximum56157
Range452
Interquartile range (IQR)254.75

Descriptive statistics

Standard deviation137.02164
Coefficient of variation (CV)0.0024500534
Kurtosis-1.5632349
Mean55925.98
Median Absolute Deviation (MAD)72.5
Skewness0.27674662
Sum5592598
Variance18774.929
MonotonicityNot monotonic
2023-12-10T19:11:04.682214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56157 1
 
1.0%
55823 1
 
1.0%
55810 1
 
1.0%
55831 1
 
1.0%
55813 1
 
1.0%
55829 1
 
1.0%
55821 1
 
1.0%
55815 1
 
1.0%
55816 1
 
1.0%
55817 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
55705 1
1.0%
55707 1
1.0%
55717 1
1.0%
55774 1
1.0%
55776 1
1.0%
55777 1
1.0%
55778 1
1.0%
55779 1
1.0%
55780 1
1.0%
55784 1
1.0%
ValueCountFrequency (%)
56157 1
1.0%
56147 1
1.0%
56145 1
1.0%
56138 1
1.0%
56136 1
1.0%
56133 1
1.0%
56131 1
1.0%
56128 1
1.0%
56122 1
1.0%
56118 1
1.0%

area_code
Real number (ℝ)

Distinct18
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20008.81
Minimum20001
Maximum20018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:11:04.887747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001
5-th percentile20001
Q120004
median20010
Q320013
95-th percentile20016.05
Maximum20018
Range17
Interquartile range (IQR)9

Descriptive statistics

Standard deviation5.0546408
Coefficient of variation (CV)0.00025262076
Kurtosis-1.1445794
Mean20008.81
Median Absolute Deviation (MAD)4
Skewness-0.15887058
Sum2000881
Variance25.549394
MonotonicityNot monotonic
2023-12-10T19:11:05.103658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
20010 14
14.0%
20001 13
13.0%
20008 8
 
8.0%
20003 7
 
7.0%
20013 7
 
7.0%
20014 7
 
7.0%
20012 6
 
6.0%
20011 5
 
5.0%
20015 5
 
5.0%
20002 4
 
4.0%
Other values (8) 24
24.0%
ValueCountFrequency (%)
20001 13
13.0%
20002 4
 
4.0%
20003 7
7.0%
20004 3
 
3.0%
20005 3
 
3.0%
20006 2
 
2.0%
20007 4
 
4.0%
20008 8
8.0%
20009 3
 
3.0%
20010 14
14.0%
ValueCountFrequency (%)
20018 1
 
1.0%
20017 4
 
4.0%
20016 4
 
4.0%
20015 5
 
5.0%
20014 7
7.0%
20013 7
7.0%
20012 6
6.0%
20011 5
 
5.0%
20010 14
14.0%
20009 3
 
3.0%

area_code_nm
Categorical

Distinct18
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
충청북도
14 
서울특별시
13 
경기도
대구광역시
전라남도
Other values (13)
51 

Length

Max length9
Median length7
Mean length4.54
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row대구광역시
2nd row충청북도
3rd row강원도(강릉분소)
4th row부산광역시
5th row경상북도

Common Values

ValueCountFrequency (%)
충청북도 14
14.0%
서울특별시 13
13.0%
경기도 8
 
8.0%
대구광역시 7
 
7.0%
전라남도 7
 
7.0%
경상북도 7
 
7.0%
전라북도 6
 
6.0%
충청남도 5
 
5.0%
경상남도 5
 
5.0%
부산광역시 4
 
4.0%
Other values (8) 24
24.0%

Length

2023-12-10T19:11:05.354624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충청북도 14
14.0%
서울특별시 13
13.0%
경기도 8
 
8.0%
대구광역시 7
 
7.0%
전라남도 7
 
7.0%
경상북도 7
 
7.0%
전라북도 6
 
6.0%
충청남도 5
 
5.0%
경상남도 5
 
5.0%
세종특별자치시 4
 
4.0%
Other values (8) 24
24.0%

fclty_grp_nm
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:11:05.806538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length11.74
Min length2

Characters and Unicode

Total characters1174
Distinct characters220
Distinct categories8 ?
Distinct scripts3 ?
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 row청소년자원봉사학교 Just Do-vol
2nd row의림유치원
3rd row양양군도시재생지원센터
4th row박재혁의사기념사업회
5th row경주시청소년방과후아카데미
ValueCountFrequency (%)
민주평화통일자문회의 13
 
9.5%
청소년자원봉사학교 1
 
0.7%
세종특별자치시청소년지원센터 1
 
0.7%
사)청소년문화예술센터 1
 
0.7%
한국나눔연맹(보라매천사무료급식소 1
 
0.7%
나눠dream센터 1
 
0.7%
썬해피누리 1
 
0.7%
한국나눔연맹(대구천사무료급식소 1
 
0.7%
한국나눔연맹(부평천사무료급식소 1
 
0.7%
달성군학교밖청소년지원센터 1
 
0.7%
Other values (115) 115
83.9%
2023-12-10T19:11:06.508933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50
 
4.3%
44
 
3.7%
43
 
3.7%
39
 
3.3%
37
 
3.2%
34
 
2.9%
31
 
2.6%
29
 
2.5%
22
 
1.9%
21
 
1.8%
Other values (210) 824
70.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1083
92.2%
Space Separator 37
 
3.2%
Close Punctuation 16
 
1.4%
Open Punctuation 16
 
1.4%
Decimal Number 7
 
0.6%
Lowercase Letter 7
 
0.6%
Uppercase Letter 7
 
0.6%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
50
 
4.6%
44
 
4.1%
43
 
4.0%
39
 
3.6%
34
 
3.1%
31
 
2.9%
29
 
2.7%
22
 
2.0%
21
 
1.9%
20
 
1.8%
Other values (190) 750
69.3%
Lowercase Letter
ValueCountFrequency (%)
o 2
28.6%
u 1
14.3%
v 1
14.3%
s 1
14.3%
t 1
14.3%
l 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
D 2
28.6%
R 1
14.3%
M 1
14.3%
A 1
14.3%
E 1
14.3%
J 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 3
42.9%
0 2
28.6%
7 1
 
14.3%
1 1
 
14.3%
Space Separator
ValueCountFrequency (%)
37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1083
92.2%
Common 77
 
6.6%
Latin 14
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
50
 
4.6%
44
 
4.1%
43
 
4.0%
39
 
3.6%
34
 
3.1%
31
 
2.9%
29
 
2.7%
22
 
2.0%
21
 
1.9%
20
 
1.8%
Other values (190) 750
69.3%
Latin
ValueCountFrequency (%)
o 2
14.3%
D 2
14.3%
R 1
7.1%
M 1
7.1%
A 1
7.1%
E 1
7.1%
J 1
7.1%
u 1
7.1%
v 1
7.1%
s 1
7.1%
Other values (2) 2
14.3%
Common
ValueCountFrequency (%)
37
48.1%
) 16
20.8%
( 16
20.8%
2 3
 
3.9%
0 2
 
2.6%
7 1
 
1.3%
1 1
 
1.3%
- 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1083
92.2%
ASCII 91
 
7.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
50
 
4.6%
44
 
4.1%
43
 
4.0%
39
 
3.6%
34
 
3.1%
31
 
2.9%
29
 
2.7%
22
 
2.0%
21
 
1.9%
20
 
1.8%
Other values (190) 750
69.3%
ASCII
ValueCountFrequency (%)
37
40.7%
) 16
17.6%
( 16
17.6%
2 3
 
3.3%
o 2
 
2.2%
D 2
 
2.2%
0 2
 
2.2%
R 1
 
1.1%
7 1
 
1.1%
M 1
 
1.1%
Other values (10) 10
 
11.0%

cl_code
Real number (ℝ)

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95003.83
Minimum95001
Maximum95008
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:11:06.743952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum95001
5-th percentile95001
Q195002
median95002
Q395008
95-th percentile95008
Maximum95008
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.8071158
Coefficient of variation (CV)2.9547396 × 10-5
Kurtosis-1.3159326
Mean95003.83
Median Absolute Deviation (MAD)1
Skewness0.7061061
Sum9500383
Variance7.879899
MonotonicityNot monotonic
2023-12-10T19:11:06.967699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
95002 39
39.0%
95008 29
29.0%
95001 16
16.0%
95003 11
 
11.0%
95004 3
 
3.0%
95006 2
 
2.0%
ValueCountFrequency (%)
95001 16
16.0%
95002 39
39.0%
95003 11
 
11.0%
95004 3
 
3.0%
95006 2
 
2.0%
95008 29
29.0%
ValueCountFrequency (%)
95008 29
29.0%
95006 2
 
2.0%
95004 3
 
3.0%
95003 11
 
11.0%
95002 39
39.0%
95001 16
16.0%

cl_code_nm
Categorical

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
청소년기관 및 단체
39 
기타시설 및 단체
29 
관공서
16 
사회복지기관 및 시설
11 
문화.예술시설 및 단체
 
3

Length

Max length12
Median length11
Mean length8.8
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row청소년기관 및 단체
2nd row관공서
3rd row기타시설 및 단체
4th row기타시설 및 단체
5th row청소년기관 및 단체

Common Values

ValueCountFrequency (%)
청소년기관 및 단체 39
39.0%
기타시설 및 단체 29
29.0%
관공서 16
16.0%
사회복지기관 및 시설 11
 
11.0%
문화.예술시설 및 단체 3
 
3.0%
의료,보호시설 및 단체 2
 
2.0%

Length

2023-12-10T19:11:07.271550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:11:07.584782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
84
31.3%
단체 73
27.2%
청소년기관 39
14.6%
기타시설 29
 
10.8%
관공서 16
 
6.0%
사회복지기관 11
 
4.1%
시설 11
 
4.1%
문화.예술시설 3
 
1.1%
의료,보호시설 2
 
0.7%

bizr_no
Categorical

IMBALANCE 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
96 
4118304252
 
1
5388200291
 
1
4148300032
 
1
2238300305
 
1

Length

Max length10
Median length4
Mean length4.24
Min length4

Unique

Unique4 ?
Unique (%)4.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 96
96.0%
4118304252 1
 
1.0%
5388200291 1
 
1.0%
4148300032 1
 
1.0%
2238300305 1
 
1.0%

Length

2023-12-10T19:11:07.925003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:11:08.126812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 96
96.0%
4118304252 1
 
1.0%
5388200291 1
 
1.0%
4148300032 1
 
1.0%
2238300305 1
 
1.0%

tel_no
Real number (ℝ)

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.9107705 × 108
Minimum4230152
Maximum7.0420366 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:11:08.372461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4230152
5-th percentile27431082
Q14.1692265 × 108
median5.2271061 × 108
Q36.1689871 × 108
95-th percentile1.0818629 × 109
Maximum7.0420366 × 109
Range7.0378064 × 109
Interquartile range (IQR)1.9997606 × 108

Descriptive statistics

Standard deviation7.0311979 × 108
Coefficient of variation (CV)1.1895569
Kurtosis73.022803
Mean5.9107705 × 108
Median Absolute Deviation (MAD)1.03155 × 108
Skewness7.94695
Sum5.9107705 × 1010
Variance4.9437744 × 1017
MonotonicityNot monotonic
2023-12-10T19:11:08.637728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
536596214 2
 
2.0%
448681318 1
 
1.0%
547870924 1
 
1.0%
639046540 1
 
1.0%
611111111 1
 
1.0%
1067040041 1
 
1.0%
322622004 1
 
1.0%
536141389 1
 
1.0%
1022300028 1
 
1.0%
1074550031 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
4230152 1
1.0%
23892090 1
1.0%
25047701 1
1.0%
27300715 1
1.0%
27371103 1
1.0%
27434239 1
1.0%
27962278 1
1.0%
29981318 1
1.0%
221162178 1
1.0%
234869543 1
1.0%
ValueCountFrequency (%)
7042036601 1
1.0%
1095820039 1
1.0%
1086016186 1
1.0%
1084970048 1
1.0%
1084633448 1
1.0%
1081717123 1
1.0%
1079421350 1
1.0%
1074550031 1
1.0%
1067040041 1
1.0%
1065310038 1
1.0%

fax_no
Real number (ℝ)

MISSING  ZEROS 

Distinct96
Distinct (%)98.0%
Missing2
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean9.5848185 × 108
Minimum0
Maximum3.0309501 × 1010
Zeros2
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:11:08.900060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile24860918
Q13.3462444 × 108
median4.8098268 × 108
Q35.9952304 × 108
95-th percentile3.4594947 × 109
Maximum3.0309501 × 1010
Range3.0309501 × 1010
Interquartile range (IQR)2.6489861 × 108

Descriptive statistics

Standard deviation3.148173 × 109
Coefficient of variation (CV)3.284541
Kurtosis79.89484
Mean9.5848185 × 108
Median Absolute Deviation (MAD)1.3446825 × 108
Skewness8.6178955
Sum9.3931221 × 1010
Variance9.910993 × 1018
MonotonicityNot monotonic
2023-12-10T19:11:09.224938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
536596219 2
 
2.0%
0 2
 
2.0%
518520114 1
 
1.0%
624181040 1
 
1.0%
27371109 1
 
1.0%
547872352 1
 
1.0%
5040426540 1
 
1.0%
5042078602 1
 
1.0%
532183004 1
 
1.0%
322623004 1
 
1.0%
Other values (86) 86
86.0%
(Missing) 2
 
2.0%
ValueCountFrequency (%)
0 2
2.0%
4230152 1
1.0%
5353533 1
1.0%
23892090 1
1.0%
25031888 1
1.0%
27371109 1
1.0%
28789339 1
1.0%
29981319 1
1.0%
221164869 1
1.0%
233251318 1
1.0%
ValueCountFrequency (%)
30309500560 1
1.0%
5043624239 1
1.0%
5042078602 1
1.0%
5040557578 1
1.0%
5040426540 1
1.0%
3180506688 1
1.0%
1079421350 1
1.0%
647827908 1
1.0%
647673457 1
1.0%
647603543 1
1.0%

hmpg_url
Text

MISSING 

Distinct29
Distinct (%)96.7%
Missing70
Missing (%)70.0%
Memory size932.0 B
2023-12-10T19:11:09.586216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length33.5
Mean length25.4
Min length15

Characters and Unicode

Total characters762
Distinct characters40
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)93.3%

Sample

1st rowhttp://pjh1895.or.kr
2nd rowhttps://youth.gyeongju.go.kr/index.jsp
3rd rowhttp://kskid.kr
4th rowhttp://makey.kr
5th rowhttp://www.cyyc.co.kr/
ValueCountFrequency (%)
https://www.nuac.go.kr 2
 
6.7%
http://seocho.seocholib.or.kr 1
 
3.3%
http://www.1004n.co.kr 1
 
3.3%
https://cafe.naver.com/daesoyouth 1
 
3.3%
http://manhae2003.dongguk.edu 1
 
3.3%
http://usepa..x-y.net 1
 
3.3%
http://www.hopenews.or.kr 1
 
3.3%
https://www.kohom.or.kr/moffice/0602003/index.do 1
 
3.3%
https://www.meetup.or.kr 1
 
3.3%
https://fowi.or.kr 1
 
3.3%
Other values (19) 19
63.3%
2023-12-10T19:11:10.433020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 81
 
10.6%
. 74
 
9.7%
t 71
 
9.3%
w 48
 
6.3%
h 44
 
5.8%
o 44
 
5.8%
p 38
 
5.0%
r 38
 
5.0%
k 31
 
4.1%
: 30
 
3.9%
Other values (30) 263
34.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 538
70.6%
Other Punctuation 185
 
24.3%
Decimal Number 35
 
4.6%
Other Letter 3
 
0.4%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 71
13.2%
w 48
 
8.9%
h 44
 
8.2%
o 44
 
8.2%
p 38
 
7.1%
r 38
 
7.1%
k 31
 
5.8%
s 28
 
5.2%
e 26
 
4.8%
c 25
 
4.6%
Other values (14) 145
27.0%
Decimal Number
ValueCountFrequency (%)
0 9
25.7%
1 8
22.9%
3 5
14.3%
8 5
14.3%
2 3
 
8.6%
4 2
 
5.7%
5 1
 
2.9%
6 1
 
2.9%
9 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
/ 81
43.8%
. 74
40.0%
: 30
 
16.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 538
70.6%
Common 221
29.0%
Hangul 3
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 71
13.2%
w 48
 
8.9%
h 44
 
8.2%
o 44
 
8.2%
p 38
 
7.1%
r 38
 
7.1%
k 31
 
5.8%
s 28
 
5.2%
e 26
 
4.8%
c 25
 
4.6%
Other values (14) 145
27.0%
Common
ValueCountFrequency (%)
/ 81
36.7%
. 74
33.5%
: 30
 
13.6%
0 9
 
4.1%
1 8
 
3.6%
3 5
 
2.3%
8 5
 
2.3%
2 3
 
1.4%
4 2
 
0.9%
5 1
 
0.5%
Other values (3) 3
 
1.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 759
99.6%
Hangul 3
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 81
 
10.7%
. 74
 
9.7%
t 71
 
9.4%
w 48
 
6.3%
h 44
 
5.8%
o 44
 
5.8%
p 38
 
5.0%
r 38
 
5.0%
k 31
 
4.1%
: 30
 
4.0%
Other values (27) 260
34.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

zip_no
Real number (ℝ)

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34589.53
Minimum1699
Maximum63584
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:11:10.681935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1699
5-th percentile3190.85
Q124627.75
median33166
Q348182
95-th percentile61221.5
Maximum63584
Range61885
Interquartile range (IQR)23554.25

Descriptive statistics

Standard deviation17847
Coefficient of variation (CV)0.51596538
Kurtosis-0.90431323
Mean34589.53
Median Absolute Deviation (MAD)12844.5
Skewness-0.15903188
Sum3458953
Variance3.1851541 × 108
MonotonicityNot monotonic
2023-12-10T19:11:11.043182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41934 2
 
2.0%
63584 2
 
2.0%
38637 1
 
1.0%
54828 1
 
1.0%
59220 1
 
1.0%
41791 1
 
1.0%
21389 1
 
1.0%
42985 1
 
1.0%
7302 1
 
1.0%
3193 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
1699 1
1.0%
1882 1
1.0%
2163 1
1.0%
2557 1
1.0%
3150 1
1.0%
3193 1
1.0%
3371 1
1.0%
5514 1
1.0%
6629 1
1.0%
7302 1
1.0%
ValueCountFrequency (%)
63584 2
2.0%
63331 1
1.0%
63246 1
1.0%
62238 1
1.0%
61168 1
1.0%
61030 1
1.0%
59693 1
1.0%
59226 1
1.0%
59220 1
1.0%
58639 1
1.0%
Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:11:11.875635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length35
Mean length24.52
Min length17

Characters and Unicode

Total characters2452
Distinct characters224
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)96.0%

Sample

1st row대구광역시 중구 중앙대로81길 66-5 (종로1가)
2nd row충청북도 제천시 용두대로7길 13 (하소동)
3rd row강원도 양양군 양양읍 남문1길 15
4th row부산광역시 부산진구 서면로 9 (부전동)
5th row경상북도 경주시 알천북로 131 (황성동)
ValueCountFrequency (%)
충청북도 14
 
2.7%
서울특별시 13
 
2.5%
경기도 8
 
1.5%
경상북도 7
 
1.3%
전라남도 7
 
1.3%
대구광역시 7
 
1.3%
전라북도 6
 
1.1%
중앙로 5
 
1.0%
경상남도 5
 
1.0%
충청남도 5
 
1.0%
Other values (372) 446
85.3%
2023-12-10T19:11:12.701467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
423
 
17.3%
89
 
3.6%
79
 
3.2%
1 78
 
3.2%
77
 
3.1%
( 66
 
2.7%
) 66
 
2.7%
61
 
2.5%
59
 
2.4%
2 45
 
1.8%
Other values (214) 1409
57.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1549
63.2%
Space Separator 423
 
17.3%
Decimal Number 323
 
13.2%
Open Punctuation 66
 
2.7%
Close Punctuation 66
 
2.7%
Dash Punctuation 14
 
0.6%
Other Punctuation 11
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
89
 
5.7%
79
 
5.1%
77
 
5.0%
61
 
3.9%
59
 
3.8%
35
 
2.3%
34
 
2.2%
34
 
2.2%
30
 
1.9%
30
 
1.9%
Other values (199) 1021
65.9%
Decimal Number
ValueCountFrequency (%)
1 78
24.1%
2 45
13.9%
3 32
9.9%
5 31
 
9.6%
6 29
 
9.0%
7 25
 
7.7%
9 24
 
7.4%
0 21
 
6.5%
8 21
 
6.5%
4 17
 
5.3%
Space Separator
ValueCountFrequency (%)
423
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Close Punctuation
ValueCountFrequency (%)
) 66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1549
63.2%
Common 903
36.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
89
 
5.7%
79
 
5.1%
77
 
5.0%
61
 
3.9%
59
 
3.8%
35
 
2.3%
34
 
2.2%
34
 
2.2%
30
 
1.9%
30
 
1.9%
Other values (199) 1021
65.9%
Common
ValueCountFrequency (%)
423
46.8%
1 78
 
8.6%
( 66
 
7.3%
) 66
 
7.3%
2 45
 
5.0%
3 32
 
3.5%
5 31
 
3.4%
6 29
 
3.2%
7 25
 
2.8%
9 24
 
2.7%
Other values (5) 84
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1549
63.2%
ASCII 903
36.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
423
46.8%
1 78
 
8.6%
( 66
 
7.3%
) 66
 
7.3%
2 45
 
5.0%
3 32
 
3.5%
5 31
 
3.4%
6 29
 
3.2%
7 25
 
2.8%
9 24
 
2.7%
Other values (5) 84
 
9.3%
Hangul
ValueCountFrequency (%)
89
 
5.7%
79
 
5.1%
77
 
5.0%
61
 
3.9%
59
 
3.8%
35
 
2.3%
34
 
2.2%
34
 
2.2%
30
 
1.9%
30
 
1.9%
Other values (199) 1021
65.9%
Distinct95
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:11:13.150695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length18
Mean length9.95
Min length2

Characters and Unicode

Total characters995
Distinct characters199
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)91.0%

Sample

1st row1층 청소년활동진흥센터
2nd row의림유치원 교무실
3rd row양양시장공영주차장 2층
4th row603 (부전동, 철산빌딩)
5th row2층 청소년방과후아카데미
ValueCountFrequency (%)
2층 11
 
6.5%
1층 10
 
5.9%
3층 7
 
4.1%
민주평통 5
 
3.0%
천사무료급식소 5
 
3.0%
청소년활동진흥센터 3
 
1.8%
상가 2
 
1.2%
6층 2
 
1.2%
4층 2
 
1.2%
관리사무소2층 2
 
1.2%
Other values (120) 120
71.0%
2023-12-10T19:11:13.896110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
69
 
6.9%
43
 
4.3%
40
 
4.0%
38
 
3.8%
1 27
 
2.7%
26
 
2.6%
2 22
 
2.2%
20
 
2.0%
19
 
1.9%
19
 
1.9%
Other values (189) 672
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 808
81.2%
Decimal Number 98
 
9.8%
Space Separator 69
 
6.9%
Other Punctuation 6
 
0.6%
Close Punctuation 5
 
0.5%
Open Punctuation 5
 
0.5%
Dash Punctuation 3
 
0.3%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
43
 
5.3%
40
 
5.0%
38
 
4.7%
26
 
3.2%
20
 
2.5%
19
 
2.4%
19
 
2.4%
19
 
2.4%
18
 
2.2%
16
 
2.0%
Other values (173) 550
68.1%
Decimal Number
ValueCountFrequency (%)
1 27
27.6%
2 22
22.4%
3 12
12.2%
0 11
11.2%
4 9
 
9.2%
7 6
 
6.1%
6 6
 
6.1%
5 4
 
4.1%
9 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 4
66.7%
/ 2
33.3%
Space Separator
ValueCountFrequency (%)
69
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 808
81.2%
Common 187
 
18.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
43
 
5.3%
40
 
5.0%
38
 
4.7%
26
 
3.2%
20
 
2.5%
19
 
2.4%
19
 
2.4%
19
 
2.4%
18
 
2.2%
16
 
2.0%
Other values (173) 550
68.1%
Common
ValueCountFrequency (%)
69
36.9%
1 27
 
14.4%
2 22
 
11.8%
3 12
 
6.4%
0 11
 
5.9%
4 9
 
4.8%
7 6
 
3.2%
6 6
 
3.2%
) 5
 
2.7%
( 5
 
2.7%
Other values (6) 15
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 808
81.2%
ASCII 187
 
18.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
69
36.9%
1 27
 
14.4%
2 22
 
11.8%
3 12
 
6.4%
0 11
 
5.9%
4 9
 
4.8%
7 6
 
3.2%
6 6
 
3.2%
) 5
 
2.7%
( 5
 
2.7%
Other values (6) 15
 
8.0%
Hangul
ValueCountFrequency (%)
43
 
5.3%
40
 
5.0%
38
 
4.7%
26
 
3.2%
20
 
2.5%
19
 
2.4%
19
 
2.4%
19
 
2.4%
18
 
2.2%
16
 
2.0%
Other values (173) 550
68.1%

map_url
Text

MISSING 

Distinct27
Distinct (%)100.0%
Missing73
Missing (%)73.0%
Memory size932.0 B
2023-12-10T19:11:14.439163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length21
Mean length18.074074
Min length4

Characters and Unicode

Total characters488
Distinct characters156
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row강원도 양양군 양양읍 남문1길 15
2nd row서구 큰마을 아파트내
3rd row아름초 등학교 건너편 우미린 상가
4th row인천광역시 강화군 강화읍 향나무길22번길 20
5th row경기도 화성시 병점중앙로 195 3층 화성시청소년놀터
ValueCountFrequency (%)
2층 4
 
3.6%
3
 
2.7%
3층 3
 
2.7%
강원도 1
 
0.9%
서울 1
 
0.9%
논공읍 1
 
0.9%
달성군 1
 
0.9%
대구광역시 1
 
0.9%
천사무료급식소 1
 
0.9%
1층 1
 
0.9%
Other values (93) 93
84.5%
2023-12-10T19:11:15.172688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
84
 
17.2%
2 18
 
3.7%
1 14
 
2.9%
11
 
2.3%
11
 
2.3%
10
 
2.0%
8
 
1.6%
8
 
1.6%
7
 
1.4%
7
 
1.4%
Other values (146) 310
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 331
67.8%
Space Separator 84
 
17.2%
Decimal Number 58
 
11.9%
Other Punctuation 6
 
1.2%
Close Punctuation 3
 
0.6%
Dash Punctuation 3
 
0.6%
Open Punctuation 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11
 
3.3%
11
 
3.3%
10
 
3.0%
8
 
2.4%
8
 
2.4%
7
 
2.1%
7
 
2.1%
6
 
1.8%
6
 
1.8%
6
 
1.8%
Other values (130) 251
75.8%
Decimal Number
ValueCountFrequency (%)
2 18
31.0%
1 14
24.1%
3 6
 
10.3%
0 5
 
8.6%
5 4
 
6.9%
8 3
 
5.2%
7 3
 
5.2%
6 2
 
3.4%
9 2
 
3.4%
4 1
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 4
66.7%
' 2
33.3%
Space Separator
ValueCountFrequency (%)
84
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 331
67.8%
Common 157
32.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11
 
3.3%
11
 
3.3%
10
 
3.0%
8
 
2.4%
8
 
2.4%
7
 
2.1%
7
 
2.1%
6
 
1.8%
6
 
1.8%
6
 
1.8%
Other values (130) 251
75.8%
Common
ValueCountFrequency (%)
84
53.5%
2 18
 
11.5%
1 14
 
8.9%
3 6
 
3.8%
0 5
 
3.2%
, 4
 
2.5%
5 4
 
2.5%
8 3
 
1.9%
) 3
 
1.9%
- 3
 
1.9%
Other values (6) 13
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 331
67.8%
ASCII 157
32.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
84
53.5%
2 18
 
11.5%
1 14
 
8.9%
3 6
 
3.8%
0 5
 
3.2%
, 4
 
2.5%
5 4
 
2.5%
8 3
 
1.9%
) 3
 
1.9%
- 3
 
1.9%
Other values (6) 13
 
8.3%
Hangul
ValueCountFrequency (%)
11
 
3.3%
11
 
3.3%
10
 
3.0%
8
 
2.4%
8
 
2.4%
7
 
2.1%
7
 
2.1%
6
 
1.8%
6
 
1.8%
6
 
1.8%
Other values (130) 251
75.8%

tfcmn_tfcmn
Text

MISSING 

Distinct25
Distinct (%)100.0%
Missing75
Missing (%)75.0%
Memory size932.0 B
2023-12-10T19:11:15.866959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length241
Median length42
Mean length52.48
Min length2

Characters and Unicode

Total characters1312
Distinct characters176
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row양양시외버스터미널 근처
2nd rowo 칠곡초등학교 건너 730, 북구1, 칠곡2, 칠곡4, 칠곡5 o 교동초등학교 건너 칠곡4 o 칠곡초등학교 앞 527,730, 급행3, 북구1, 칠곡2, 칠곡3, 칠곡4, 칠곡5 o 교동초등학교 앞 칠곡4
3rd row지하철 이용 1호선 종각 2번출구 나오셔서 약600m 5호선 광화문역 2번 출구 나와서 종로구청방향 약700m
4th row보은군청
5th row영동군청 3층
ValueCountFrequency (%)
21
 
7.9%
하차 9
 
3.4%
9
 
3.4%
버스 5
 
1.9%
당정골정류장 4
 
1.5%
o 4
 
1.5%
도보 4
 
1.5%
칠곡4 4
 
1.5%
지하철 3
 
1.1%
3
 
1.1%
Other values (180) 199
75.1%
2023-12-10T19:11:16.834577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
256
 
19.5%
, 64
 
4.9%
1 60
 
4.6%
0 44
 
3.4%
30
 
2.3%
3 26
 
2.0%
- 24
 
1.8%
2 24
 
1.8%
4 23
 
1.8%
22
 
1.7%
Other values (166) 739
56.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 648
49.4%
Space Separator 256
 
19.5%
Decimal Number 244
 
18.6%
Other Punctuation 84
 
6.4%
Dash Punctuation 24
 
1.8%
Close Punctuation 21
 
1.6%
Open Punctuation 19
 
1.4%
Math Symbol 9
 
0.7%
Lowercase Letter 7
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
30
 
4.6%
22
 
3.4%
21
 
3.2%
21
 
3.2%
19
 
2.9%
17
 
2.6%
16
 
2.5%
14
 
2.2%
13
 
2.0%
13
 
2.0%
Other values (145) 462
71.3%
Decimal Number
ValueCountFrequency (%)
1 60
24.6%
0 44
18.0%
3 26
10.7%
2 24
 
9.8%
4 23
 
9.4%
7 17
 
7.0%
5 16
 
6.6%
6 14
 
5.7%
9 13
 
5.3%
8 7
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 64
76.2%
: 14
 
16.7%
. 5
 
6.0%
/ 1
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
o 4
57.1%
m 3
42.9%
Space Separator
ValueCountFrequency (%)
256
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Math Symbol
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 657
50.1%
Hangul 648
49.4%
Latin 7
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
30
 
4.6%
22
 
3.4%
21
 
3.2%
21
 
3.2%
19
 
2.9%
17
 
2.6%
16
 
2.5%
14
 
2.2%
13
 
2.0%
13
 
2.0%
Other values (145) 462
71.3%
Common
ValueCountFrequency (%)
256
39.0%
, 64
 
9.7%
1 60
 
9.1%
0 44
 
6.7%
3 26
 
4.0%
- 24
 
3.7%
2 24
 
3.7%
4 23
 
3.5%
) 21
 
3.2%
( 19
 
2.9%
Other values (9) 96
 
14.6%
Latin
ValueCountFrequency (%)
o 4
57.1%
m 3
42.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 655
49.9%
Hangul 648
49.4%
Arrows 9
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
256
39.1%
, 64
 
9.8%
1 60
 
9.2%
0 44
 
6.7%
3 26
 
4.0%
- 24
 
3.7%
2 24
 
3.7%
4 23
 
3.5%
) 21
 
3.2%
( 19
 
2.9%
Other values (10) 94
 
14.4%
Hangul
ValueCountFrequency (%)
30
 
4.6%
22
 
3.4%
21
 
3.2%
21
 
3.2%
19
 
2.9%
17
 
2.6%
16
 
2.5%
14
 
2.2%
13
 
2.0%
13
 
2.0%
Other values (145) 462
71.3%
Arrows
ValueCountFrequency (%)
9
100.0%

charger_psitn_dept
Text

MISSING 

Distinct34
Distinct (%)97.1%
Missing65
Missing (%)65.0%
Memory size932.0 B
2023-12-10T19:11:17.279964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length6.7142857
Min length2

Characters and Unicode

Total characters235
Distinct characters94
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)94.3%

Sample

1st row활동협력팀
2nd row양양군청 도시계획과 소속 직영
3rd row사무국
4th row교무팀
5th row청소년활동팀
ValueCountFrequency (%)
사무처 2
 
4.5%
정책기획부 1
 
2.3%
산림교육팀 1
 
2.3%
ㅇㄹ 1
 
2.3%
재단사무국 1
 
2.3%
전시체험팀 1
 
2.3%
미트업 1
 
2.3%
센터 1
 
2.3%
청소년지도사 1
 
2.3%
아산시청소년재단 1
 
2.3%
Other values (33) 33
75.0%
2023-12-10T19:11:18.143337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
 
7.2%
14
 
6.0%
13
 
5.5%
9
 
3.8%
8
 
3.4%
8
 
3.4%
7
 
3.0%
5
 
2.1%
5
 
2.1%
4
 
1.7%
Other values (84) 145
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 224
95.3%
Space Separator 9
 
3.8%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
17
 
7.6%
14
 
6.2%
13
 
5.8%
8
 
3.6%
8
 
3.6%
7
 
3.1%
5
 
2.2%
5
 
2.2%
4
 
1.8%
4
 
1.8%
Other values (81) 139
62.1%
Space Separator
ValueCountFrequency (%)
9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 224
95.3%
Common 11
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
17
 
7.6%
14
 
6.2%
13
 
5.8%
8
 
3.6%
8
 
3.6%
7
 
3.1%
5
 
2.2%
5
 
2.2%
4
 
1.8%
4
 
1.8%
Other values (81) 139
62.1%
Common
ValueCountFrequency (%)
9
81.8%
( 1
 
9.1%
) 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 222
94.5%
ASCII 11
 
4.7%
Compat Jamo 2
 
0.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
17
 
7.7%
14
 
6.3%
13
 
5.9%
8
 
3.6%
8
 
3.6%
7
 
3.2%
5
 
2.3%
5
 
2.3%
4
 
1.8%
4
 
1.8%
Other values (79) 137
61.7%
ASCII
ValueCountFrequency (%)
9
81.8%
( 1
 
9.1%
) 1
 
9.1%
Compat Jamo
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:11:18.636517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length10.21
Min length7

Characters and Unicode

Total characters1021
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

Unique98 ?
Unique (%)98.0%

Sample

1st row0536596214
2nd row0432206821
3rd row0336716900
4th row0515252114
5th row0547602233
ValueCountFrequency (%)
0536596214 2
 
2.0%
0319669677 1
 
1.0%
0639046540 1
 
1.0%
01026408602 1
 
1.0%
01067040041 1
 
1.0%
0322622004 1
 
1.0%
0536141389 1
 
1.0%
0262672004 1
 
1.0%
01074550031 1
 
1.0%
01065310038 1
 
1.0%
Other values (89) 89
89.0%
2023-12-10T19:11:19.585186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 211
20.7%
3 112
11.0%
4 105
10.3%
2 102
10.0%
1 100
9.8%
6 91
8.9%
7 86
8.4%
5 84
 
8.2%
8 64
 
6.3%
9 56
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1011
99.0%
Dash Punctuation 10
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 211
20.9%
3 112
11.1%
4 105
10.4%
2 102
10.1%
1 100
9.9%
6 91
9.0%
7 86
8.5%
5 84
 
8.3%
8 64
 
6.3%
9 56
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1021
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 211
20.7%
3 112
11.0%
4 105
10.3%
2 102
10.0%
1 100
9.8%
6 91
8.9%
7 86
8.4%
5 84
 
8.2%
8 64
 
6.3%
9 56
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1021
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 211
20.7%
3 112
11.0%
4 105
10.3%
2 102
10.0%
1 100
9.8%
6 91
8.9%
7 86
8.4%
5 84
 
8.2%
8 64
 
6.3%
9 56
 
5.5%

charger_email_pre
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:11:20.049685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19.5
Mean length12.43
Min length3

Characters and Unicode

Total characters1243
Distinct characters42
Distinct categories6 ?
Distinct scripts3 ?
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 rowzero-limit@nate.com
2nd rowleeyejin0129
3rd rowyyursc
4th rowparkjh1895
5th rowehdgus1203@korea.kr
ValueCountFrequency (%)
zero-limit@nate.com 1
 
1.0%
dlekdud010@gbe.kr 1
 
1.0%
6540park 1
 
1.0%
lyjlc31 1
 
1.0%
1004ngo 1
 
1.0%
1004ngobp 1
 
1.0%
kimty53@hanmail.net 1
 
1.0%
1004ngoydp 1
 
1.0%
ngo1004ngo 1
 
1.0%
1004ngogj@naver.com 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:11:20.804959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 84
 
6.8%
n 72
 
5.8%
a 71
 
5.7%
e 61
 
4.9%
0 60
 
4.8%
k 58
 
4.7%
r 58
 
4.7%
1 53
 
4.3%
. 53
 
4.3%
m 49
 
3.9%
Other values (32) 624
50.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 866
69.7%
Decimal Number 275
 
22.1%
Other Punctuation 94
 
7.6%
Other Letter 4
 
0.3%
Dash Punctuation 2
 
0.2%
Connector Punctuation 2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 84
 
9.7%
n 72
 
8.3%
a 71
 
8.2%
e 61
 
7.0%
k 58
 
6.7%
r 58
 
6.7%
m 49
 
5.7%
c 44
 
5.1%
l 43
 
5.0%
i 39
 
4.5%
Other values (14) 287
33.1%
Decimal Number
ValueCountFrequency (%)
0 60
21.8%
1 53
19.3%
3 36
13.1%
4 26
9.5%
2 20
 
7.3%
8 19
 
6.9%
6 17
 
6.2%
9 17
 
6.2%
5 17
 
6.2%
7 10
 
3.6%
Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 53
56.4%
@ 41
43.6%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 866
69.7%
Common 373
30.0%
Hangul 4
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 84
 
9.7%
n 72
 
8.3%
a 71
 
8.2%
e 61
 
7.0%
k 58
 
6.7%
r 58
 
6.7%
m 49
 
5.7%
c 44
 
5.1%
l 43
 
5.0%
i 39
 
4.5%
Other values (14) 287
33.1%
Common
ValueCountFrequency (%)
0 60
16.1%
1 53
14.2%
. 53
14.2%
@ 41
11.0%
3 36
9.7%
4 26
7.0%
2 20
 
5.4%
8 19
 
5.1%
6 17
 
4.6%
9 17
 
4.6%
Other values (4) 31
8.3%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1239
99.7%
Hangul 4
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 84
 
6.8%
n 72
 
5.8%
a 71
 
5.7%
e 61
 
4.9%
0 60
 
4.8%
k 58
 
4.7%
r 58
 
4.7%
1 53
 
4.3%
. 53
 
4.3%
m 49
 
4.0%
Other values (28) 620
50.0%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

charger_email_code
Real number (ℝ)

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37425.52
Minimum37005
Maximum37999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:11:21.037570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37005
5-th percentile37005
Q137005
median37020
Q337999
95-th percentile37999
Maximum37999
Range994
Interquartile range (IQR)994

Descriptive statistics

Standard deviation490.49522
Coefficient of variation (CV)0.013105903
Kurtosis-1.9304579
Mean37425.52
Median Absolute Deviation (MAD)15
Skewness0.3288019
Sum3742552
Variance240585.57
MonotonicityNot monotonic
2023-12-10T19:11:21.307224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
37999 42
42.0%
37005 29
29.0%
37020 14
 
14.0%
37007 5
 
5.0%
37008 4
 
4.0%
37013 3
 
3.0%
37021 3
 
3.0%
ValueCountFrequency (%)
37005 29
29.0%
37007 5
 
5.0%
37008 4
 
4.0%
37013 3
 
3.0%
37020 14
 
14.0%
37021 3
 
3.0%
37999 42
42.0%
ValueCountFrequency (%)
37999 42
42.0%
37021 3
 
3.0%
37020 14
 
14.0%
37013 3
 
3.0%
37008 4
 
4.0%
37007 5
 
5.0%
37005 29
29.0%
Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
직접입력
42 
naver.com
29 
hanmail.net
14 
daum.net
nate.com
 
4
Other values (2)

Length

Max length11
Median length9
Mean length7.06
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row직접입력
2nd rownaver.com
3rd rowgmail.com
4th rownaver.com
5th row직접입력

Common Values

ValueCountFrequency (%)
직접입력 42
42.0%
naver.com 29
29.0%
hanmail.net 14
 
14.0%
daum.net 5
 
5.0%
nate.com 4
 
4.0%
gmail.com 3
 
3.0%
korea.kr 3
 
3.0%

Length

2023-12-10T19:11:21.618229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:11:21.848236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
직접입력 42
42.0%
naver.com 29
29.0%
hanmail.net 14
 
14.0%
daum.net 5
 
5.0%
nate.com 4
 
4.0%
gmail.com 3
 
3.0%
korea.kr 3
 
3.0%

use_at
Boolean

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
True
100 
ValueCountFrequency (%)
True 100
100.0%
2023-12-10T19:11:22.034153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

regist_dt
Date

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2020-01-03 04:56:57
Maximum2021-04-24 02:31:24
2023-12-10T19:11:22.208720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:11:22.450614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

updt_dt
Date

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2020-01-10 12:57:57
Maximum2021-04-29 10:03:11
2023-12-10T19:11:23.057545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:11:23.381752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Sample

fclty_grp_snarea_codearea_code_nmfclty_grp_nmcl_codecl_code_nmbizr_notel_nofax_nohmpg_urlzip_noadres_preadres_rrmap_urltfcmn_tfcmncharger_psitn_deptcharger_tlphon_nocharger_email_precharger_email_codecharger_email_code_nmuse_atregist_dtupdt_dt
05615720003대구광역시청소년자원봉사학교 Just Do-vol95002청소년기관 및 단체<NA>536596214536596219<NA>41934대구광역시 중구 중앙대로81길 66-5 (종로1가)1층 청소년활동진흥센터<NA><NA><NA>0536596214zero-limit@nate.com37999직접입력Y2021-04-24 02:31:24.02021-04-24 02:33:18.0
15571720010충청북도의림유치원95001관공서<NA>436456586436466295<NA>27187충청북도 제천시 용두대로7길 13 (하소동)의림유치원 교무실<NA><NA>활동협력팀0432206821leeyejin012937005naver.comY2020-01-08 11:52:07.02021-03-08 12:50:57.0
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