Overview

Dataset statistics

Number of variables24
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.9 KiB
Average record size in memory203.3 B

Variable types

Text7
Categorical9
Numeric8

Alerts

lclas has constant value ""Constant
mlsfc 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
oper_mby is highly imbalanced (64.2%)Imbalance
id has unique valuesUnique
fclt_name has unique valuesUnique
adstrd_cd has unique valuesUnique
adstrd_nm has unique valuesUnique
rdnmaddr_cd 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
telno has unique valuesUnique
x_utmk_cd has unique valuesUnique
y_utmk_cd has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:04:55.526117
Analysis finished2023-12-10 10:04:56.954627
Duration1.43 second
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
2023-12-10T19:04:57.305666image/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 rowKC485PC19N000001
2nd rowKC485PC19N000002
3rd rowKC485PC19N000003
4th rowKC485PC19N000004
5th rowKC485PC19N000005
ValueCountFrequency (%)
kc485pc19n000001 1
 
1.0%
kc485pc19n000063 1
 
1.0%
kc485pc19n000074 1
 
1.0%
kc485pc19n000073 1
 
1.0%
kc485pc19n000072 1
 
1.0%
kc485pc19n000071 1
 
1.0%
kc485pc19n000070 1
 
1.0%
kc485pc19n000069 1
 
1.0%
kc485pc19n000068 1
 
1.0%
kc485pc19n000067 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:04:57.964741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 419
26.2%
C 200
12.5%
1 121
 
7.6%
4 120
 
7.5%
8 120
 
7.5%
5 120
 
7.5%
9 120
 
7.5%
K 100
 
6.2%
P 100
 
6.2%
N 100
 
6.2%
Other values (4) 80
 
5.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 419
38.1%
1 121
 
11.0%
4 120
 
10.9%
8 120
 
10.9%
5 120
 
10.9%
9 120
 
10.9%
3 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
2 20
 
1.8%
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 (%)
0 419
38.1%
1 121
 
11.0%
4 120
 
10.9%
8 120
 
10.9%
5 120
 
10.9%
9 120
 
10.9%
3 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
2 20
 
1.8%
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 (%)
0 419
26.2%
C 200
12.5%
1 121
 
7.6%
4 120
 
7.5%
8 120
 
7.5%
5 120
 
7.5%
9 120
 
7.5%
K 100
 
6.2%
P 100
 
6.2%
N 100
 
6.2%
Other values (4) 80
 
5.0%

lclas
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
문화시설 100
100.0%

Length

2023-12-10T19:04:58.231567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:04:58.475682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화시설 100
100.0%

mlsfc
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
복지 100
100.0%

Length

2023-12-10T19:04:58.681810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:04:58.828113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
복지 100
100.0%

fclt_name
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:04:59.161057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length9.03
Min length6

Characters and Unicode

Total characters903
Distinct characters133
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

Unique100 ?
Unique (%)100.0%

Sample

1st row종로노인종합복지관
2nd row종로노인종합복지관 무악센터
3rd row서울노인복지센터
4th row약수노인종합복지관
5th row청구노인복지센터
ValueCountFrequency (%)
종로노인종합복지관 2
 
1.9%
동구노인복지관 2
 
1.9%
중구노인복지관 2
 
1.9%
노인복지관 2
 
1.9%
부산진구 2
 
1.9%
분관 2
 
1.9%
대치노인복지센터 1
 
0.9%
구립중앙노인종합복지관 1
 
0.9%
구립방배노인종합복지관 1
 
0.9%
구립양재노인종합복지관 1
 
0.9%
Other values (90) 90
84.9%
2023-12-10T19:04:59.854387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
복 98
 
10.9%
지 98
 
10.9%
노 72
 
8.0%
인 72
 
8.0%
관 69
 
7.6%
종 35
 
3.9%
센 35
 
3.9%
터 35
 
3.9%
합 34
 
3.8%
구 25
 
2.8%
Other values (123) 330
36.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 896
99.2%
Space Separator 6
 
0.7%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
복 98
 
10.9%
지 98
 
10.9%
노 72
 
8.0%
인 72
 
8.0%
관 69
 
7.7%
종 35
 
3.9%
센 35
 
3.9%
터 35
 
3.9%
합 34
 
3.8%
구 25
 
2.8%
Other values (121) 323
36.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 896
99.2%
Common 7
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
복 98
 
10.9%
지 98
 
10.9%
노 72
 
8.0%
인 72
 
8.0%
관 69
 
7.7%
종 35
 
3.9%
센 35
 
3.9%
터 35
 
3.9%
합 34
 
3.8%
구 25
 
2.8%
Other values (121) 323
36.0%
Common
ValueCountFrequency (%)
6
85.7%
2 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 896
99.2%
ASCII 7
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
복 98
 
10.9%
지 98
 
10.9%
노 72
 
8.0%
인 72
 
8.0%
관 69
 
7.7%
종 35
 
3.9%
센 35
 
3.9%
터 35
 
3.9%
합 34
 
3.8%
구 25
 
2.8%
Other values (121) 323
36.0%
ASCII
ValueCountFrequency (%)
6
85.7%
2 1
 
14.3%

ctprvn_nm
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
82 
부산광역시
18 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 82
82.0%
부산광역시 18
 
18.0%

Length

2023-12-10T19:05:00.149733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:05:00.329447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 82
82.0%
부산광역시 18
 
18.0%

sgnr_nm
Categorical

Distinct34
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
은평구
 
7
강남구
 
6
강서구
 
5
서대문구
 
5
중랑구
 
5
Other values (29)
72 

Length

Max length4
Median length3
Mean length3.03
Min length2

Unique

Unique8 ?
Unique (%)8.0%

Sample

1st row종로구
2nd row종로구
3rd row종로구
4th row중구
5th row중구

Common Values

ValueCountFrequency (%)
은평구 7
 
7.0%
강남구 6
 
6.0%
강서구 5
 
5.0%
서대문구 5
 
5.0%
중랑구 5
 
5.0%
성북구 5
 
5.0%
도봉구 5
 
5.0%
양천구 4
 
4.0%
마포구 4
 
4.0%
중구 4
 
4.0%
Other values (24) 50
50.0%

Length

2023-12-10T19:05:00.595720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
은평구 7
 
7.0%
강남구 6
 
6.0%
강서구 5
 
5.0%
서대문구 5
 
5.0%
중랑구 5
 
5.0%
성북구 5
 
5.0%
도봉구 5
 
5.0%
양천구 4
 
4.0%
마포구 4
 
4.0%
중구 4
 
4.0%
Other values (24) 50
50.0%

legaldong_cd
Real number (ℝ)

Distinct90
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4091661 × 109
Minimum1.1110134 × 109
Maximum2.6380101 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:05:00.835376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110134 × 109
5-th percentile1.1168611 × 109
Q11.1320106 × 109
median1.1470103 × 109
Q31.1680107 × 109
95-th percentile2.6261607 × 109
Maximum2.6380101 × 109
Range1.5269967 × 109
Interquartile range (IQR)36000150

Descriptive statistics

Standard deviation5.71572 × 108
Coefficient of variation (CV)0.40561011
Kurtosis0.87349269
Mean1.4091661 × 109
Median Absolute Deviation (MAD)17998400
Skewness1.6884356
Sum1.4091661 × 1011
Variance3.2669455 × 1017
MonotonicityNot monotonic
2023-12-10T19:05:01.088074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1150010300 4
 
4.0%
1114016200 2
 
2.0%
1154510200 2
 
2.0%
1147010300 2
 
2.0%
1132010500 2
 
2.0%
1126010100 2
 
2.0%
1126010600 2
 
2.0%
1168010100 2
 
2.0%
1165010800 1
 
1.0%
1171010400 1
 
1.0%
Other values (80) 80
80.0%
ValueCountFrequency (%)
1111013400 1
1.0%
1111016500 1
1.0%
1111018700 1
1.0%
1114016200 2
2.0%
1117010800 1
1.0%
1117013100 1
1.0%
1120010100 1
1.0%
1120010500 1
1.0%
1120010600 1
1.0%
1121510900 1
1.0%
ValueCountFrequency (%)
2638010100 1
1.0%
2635010700 1
1.0%
2635010400 1
1.0%
2632010500 1
1.0%
2629010600 1
1.0%
2626010700 1
1.0%
2623011000 1
1.0%
2623010400 1
1.0%
2623010200 1
1.0%
2620012000 1
1.0%

legalemd_nm
Text

Distinct89
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:05:01.632368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.12
Min length2

Characters and Unicode

Total characters312
Distinct characters111
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

Unique80 ?
Unique (%)80.0%

Sample

1st row이화동
2nd row무악동
3rd row경운동
4th row신당동
5th row신당동
ValueCountFrequency (%)
화곡동 4
 
4.0%
신내동 2
 
2.0%
쌍문동 2
 
2.0%
신월동 2
 
2.0%
역삼동 2
 
2.0%
독산동 2
 
2.0%
신사동 2
 
2.0%
면목동 2
 
2.0%
신당동 2
 
2.0%
봉천동 1
 
1.0%
Other values (79) 79
79.0%
2023-12-10T19:05:02.341569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 100
32.1%
신 9
 
2.9%
화 6
 
1.9%
가 6
 
1.9%
곡 5
 
1.6%
천 5
 
1.6%
대 5
 
1.6%
사 4
 
1.3%
삼 4
 
1.3%
월 4
 
1.3%
Other values (101) 164
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 308
98.7%
Decimal Number 4
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 100
32.5%
신 9
 
2.9%
화 6
 
1.9%
가 6
 
1.9%
곡 5
 
1.6%
천 5
 
1.6%
대 5
 
1.6%
사 4
 
1.3%
삼 4
 
1.3%
월 4
 
1.3%
Other values (98) 160
51.9%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
3 1
25.0%
1 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 308
98.7%
Common 4
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 100
32.5%
신 9
 
2.9%
화 6
 
1.9%
가 6
 
1.9%
곡 5
 
1.6%
천 5
 
1.6%
대 5
 
1.6%
사 4
 
1.3%
삼 4
 
1.3%
월 4
 
1.3%
Other values (98) 160
51.9%
Common
ValueCountFrequency (%)
2 2
50.0%
3 1
25.0%
1 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 308
98.7%
ASCII 4
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 100
32.5%
신 9
 
2.9%
화 6
 
1.9%
가 6
 
1.9%
곡 5
 
1.6%
천 5
 
1.6%
대 5
 
1.6%
사 4
 
1.3%
삼 4
 
1.3%
월 4
 
1.3%
Other values (98) 160
51.9%
ASCII
ValueCountFrequency (%)
2 2
50.0%
3 1
25.0%
1 1
25.0%

adstrd_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.409216 × 109
Minimum1.111057 × 109
Maximum2.638053 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:05:02.618396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111057 × 109
5-th percentile1.116906 × 109
Q11.1320625 × 109
median1.147063 × 109
Q31.1680642 × 109
95-th percentile2.6262045 × 109
Maximum2.638053 × 109
Range1.526996 × 109
Interquartile range (IQR)36001725

Descriptive statistics

Standard deviation5.7157168 × 108
Coefficient of variation (CV)0.40559552
Kurtosis0.87349281
Mean1.409216 × 109
Median Absolute Deviation (MAD)17995250
Skewness1.6884358
Sum1.409216 × 1011
Variance3.2669418 × 1017
MonotonicityNot monotonic
2023-12-10T19:05:02.867991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1111064000 1
 
1.0%
1159066000 1
 
1.0%
1168058000 1
 
1.0%
1168064000 1
 
1.0%
1168054500 1
 
1.0%
1168065000 1
 
1.0%
1168063000 1
 
1.0%
1165051000 1
 
1.0%
1165061000 1
 
1.0%
1165065100 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1111057000 1
1.0%
1111061500 1
1.0%
1111064000 1
1.0%
1114063500 1
1.0%
1114064500 1
1.0%
1117055500 1
1.0%
1117068500 1
1.0%
1120053500 1
1.0%
1120054000 1
1.0%
1120055000 1
1.0%
ValueCountFrequency (%)
2638053000 1
1.0%
2635065000 1
1.0%
2635055100 1
1.0%
2632052100 1
1.0%
2629055000 1
1.0%
2626054500 1
1.0%
2623078000 1
1.0%
2623071000 1
1.0%
2623061000 1
1.0%
2620063000 1
1.0%

adstrd_nm
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:05:03.404819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length7
Mean length4.19
Min length3

Characters and Unicode

Total characters419
Distinct characters119
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

Unique100 ?
Unique (%)100.0%

Sample

1st row이화동
2nd row무악동
3rd row종로1.2.3.4가동
4th row약수동
5th row청구동
ValueCountFrequency (%)
이화동 1
 
1.0%
영등포본동 1
 
1.0%
역삼1동 1
 
1.0%
압구정동 1
 
1.0%
역삼2동 1
 
1.0%
대치4동 1
 
1.0%
서초1동 1
 
1.0%
방배2동 1
 
1.0%
양재1동 1
 
1.0%
보라매동 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:05:04.191496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 100
23.9%
제 43
 
10.3%
1 25
 
6.0%
2 21
 
5.0%
3 8
 
1.9%
신 7
 
1.7%
화 6
 
1.4%
수 5
 
1.2%
대 5
 
1.2%
곡 5
 
1.2%
Other values (109) 194
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 350
83.5%
Decimal Number 65
 
15.5%
Other Punctuation 4
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 100
28.6%
제 43
 
12.3%
신 7
 
2.0%
화 6
 
1.7%
수 5
 
1.4%
대 5
 
1.4%
곡 5
 
1.4%
정 5
 
1.4%
월 4
 
1.1%
삼 4
 
1.1%
Other values (100) 166
47.4%
Decimal Number
ValueCountFrequency (%)
1 25
38.5%
2 21
32.3%
3 8
 
12.3%
4 4
 
6.2%
5 2
 
3.1%
6 2
 
3.1%
8 2
 
3.1%
7 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 350
83.5%
Common 69
 
16.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 100
28.6%
제 43
 
12.3%
신 7
 
2.0%
화 6
 
1.7%
수 5
 
1.4%
대 5
 
1.4%
곡 5
 
1.4%
정 5
 
1.4%
월 4
 
1.1%
삼 4
 
1.1%
Other values (100) 166
47.4%
Common
ValueCountFrequency (%)
1 25
36.2%
2 21
30.4%
3 8
 
11.6%
. 4
 
5.8%
4 4
 
5.8%
5 2
 
2.9%
6 2
 
2.9%
8 2
 
2.9%
7 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 350
83.5%
ASCII 69
 
16.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 100
28.6%
제 43
 
12.3%
신 7
 
2.0%
화 6
 
1.7%
수 5
 
1.4%
대 5
 
1.4%
곡 5
 
1.4%
정 5
 
1.4%
월 4
 
1.1%
삼 4
 
1.1%
Other values (100) 166
47.4%
ASCII
ValueCountFrequency (%)
1 25
36.2%
2 21
30.4%
3 8
 
11.6%
. 4
 
5.8%
4 4
 
5.8%
5 2
 
2.9%
6 2
 
2.9%
8 2
 
2.9%
7 1
 
1.4%

rdnmaddr_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4091935 × 1011
Minimum1.111021 × 1011
Maximum2.6380313 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:05:04.499499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111021 × 1011
5-th percentile1.1168911 × 1011
Q11.1320413 × 1011
median1.1470414 × 1011
Q31.1680417 × 1011
95-th percentile2.6261914 × 1011
Maximum2.6380313 × 1011
Range1.5270103 × 1011
Interquartile range (IQR)3.6000393 × 109

Descriptive statistics

Standard deviation5.7157183 × 1010
Coefficient of variation (CV)0.40560209
Kurtosis0.87349217
Mean1.4091935 × 1011
Median Absolute Deviation (MAD)1.8000207 × 109
Skewness1.6884354
Sum1.4091935 × 1013
Variance3.2669436 × 1021
MonotonicityNot monotonic
2023-12-10T19:05:04.800372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
111104100223 1
 
1.0%
115904157310 1
 
1.0%
116803122005 1
 
1.0%
116803122004 1
 
1.0%
116804166283 1
 
1.0%
116804166224 1
 
1.0%
116804166656 1
 
1.0%
116504163418 1
 
1.0%
116503121012 1
 
1.0%
116504163015 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
111102100001 1
1.0%
111104100223 1
1.0%
111104100479 1
1.0%
111404103074 1
1.0%
111404103303 1
1.0%
111704106039 1
1.0%
111704106389 1
1.0%
112003005009 1
1.0%
112003103002 1
1.0%
112004109297 1
1.0%
ValueCountFrequency (%)
263803134014 1
1.0%
263504199162 1
1.0%
263503133038 1
1.0%
263204196298 1
1.0%
262903131008 1
1.0%
262604190116 1
1.0%
262304187677 1
1.0%
262304187482 1
1.0%
262303129008 1
1.0%
262004184214 1
1.0%

rdnm_addr
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:05:05.359554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length29
Mean length25.41
Min length21

Characters and Unicode

Total characters2541
Distinct characters171
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

Unique100 ?
Unique (%)100.0%

Sample

1st row서울특별시 종로구 율곡로19길 17-8 (이화동)
2nd row서울특별시 종로구 통일로14길 36 (무악동)
3rd row서울특별시 종로구 삼일대로 467 (경운동)
4th row서울특별시 중구 다산로6길 11 (신당동)
5th row서울특별시 중구 청구로3길 69 (신당동)
ValueCountFrequency (%)
서울특별시 82
 
16.3%
부산광역시 18
 
3.6%
은평구 7
 
1.4%
강남구 6
 
1.2%
강서구 5
 
1.0%
중랑구 5
 
1.0%
서대문구 5
 
1.0%
도봉구 5
 
1.0%
성북구 5
 
1.0%
중구 4
 
0.8%
Other values (298) 360
71.7%
2023-12-10T19:05:06.211314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
402
 
15.8%
동 119
 
4.7%
서 106
 
4.2%
구 105
 
4.1%
시 104
 
4.1%
로 103
 
4.1%
) 100
 
3.9%
( 100
 
3.9%
1 82
 
3.2%
울 82
 
3.2%
Other values (161) 1238
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1547
60.9%
Space Separator 402
 
15.8%
Decimal Number 372
 
14.6%
Close Punctuation 100
 
3.9%
Open Punctuation 100
 
3.9%
Dash Punctuation 18
 
0.7%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 119
 
7.7%
서 106
 
6.9%
구 105
 
6.8%
시 104
 
6.7%
로 103
 
6.7%
울 82
 
5.3%
별 82
 
5.3%
특 82
 
5.3%
길 74
 
4.8%
산 32
 
2.1%
Other values (146) 658
42.5%
Decimal Number
ValueCountFrequency (%)
1 82
22.0%
2 53
14.2%
3 43
11.6%
5 38
10.2%
6 35
9.4%
4 27
 
7.3%
8 26
 
7.0%
7 24
 
6.5%
9 23
 
6.2%
0 21
 
5.6%
Space Separator
ValueCountFrequency (%)
402
100.0%
Close Punctuation
ValueCountFrequency (%)
) 100
100.0%
Open Punctuation
ValueCountFrequency (%)
( 100
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1547
60.9%
Common 994
39.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 119
 
7.7%
서 106
 
6.9%
구 105
 
6.8%
시 104
 
6.7%
로 103
 
6.7%
울 82
 
5.3%
별 82
 
5.3%
특 82
 
5.3%
길 74
 
4.8%
산 32
 
2.1%
Other values (146) 658
42.5%
Common
ValueCountFrequency (%)
402
40.4%
) 100
 
10.1%
( 100
 
10.1%
1 82
 
8.2%
2 53
 
5.3%
3 43
 
4.3%
5 38
 
3.8%
6 35
 
3.5%
4 27
 
2.7%
8 26
 
2.6%
Other values (5) 88
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1547
60.9%
ASCII 994
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
402
40.4%
) 100
 
10.1%
( 100
 
10.1%
1 82
 
8.2%
2 53
 
5.3%
3 43
 
4.3%
5 38
 
3.8%
6 35
 
3.5%
4 27
 
2.7%
8 26
 
2.6%
Other values (5) 88
 
8.9%
Hangul
ValueCountFrequency (%)
동 119
 
7.7%
서 106
 
6.9%
구 105
 
6.8%
시 104
 
6.7%
로 103
 
6.7%
울 82
 
5.3%
별 82
 
5.3%
특 82
 
5.3%
길 74
 
4.8%
산 32
 
2.1%
Other values (146) 658
42.5%

zip_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12637.69
Minimum1082
Maximum49339
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:05:06.475515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1082
5-th percentile1475.7
Q13343.75
median5459.5
Q38070.25
95-th percentile48970.25
Maximum49339
Range48257
Interquartile range (IQR)4726.5

Descriptive statistics

Standard deviation16962.803
Coefficient of variation (CV)1.3422392
Kurtosis0.79151068
Mean12637.69
Median Absolute Deviation (MAD)2340.5
Skewness1.6362054
Sum1263769
Variance2.8773668 × 108
MonotonicityNot monotonic
2023-12-10T19:05:06.768367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3100 1
 
1.0%
6953 1
 
1.0%
6085 1
 
1.0%
6143 1
 
1.0%
6019 1
 
1.0%
6228 1
 
1.0%
6196 1
 
1.0%
6633 1
 
1.0%
6677 1
 
1.0%
6741 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1082 1
1.0%
1305 1
1.0%
1314 1
1.0%
1370 1
1.0%
1394 1
1.0%
1480 1
1.0%
1748 1
1.0%
1837 1
1.0%
1884 1
1.0%
2041 1
1.0%
ValueCountFrequency (%)
49339 1
1.0%
49274 1
1.0%
49233 1
1.0%
49052 1
1.0%
49032 1
1.0%
48967 1
1.0%
48915 1
1.0%
48806 1
1.0%
48786 1
1.0%
48748 1
1.0%

grid_cd
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:05:07.320183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters800
Distinct characters14
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 row다사563531
2nd row다사521530
3rd row다사545530
4th row다사566504
5th row다사571509
ValueCountFrequency (%)
다사563531 1
 
1.0%
다사472458 1
 
1.0%
다사596457 1
 
1.0%
다사591472 1
 
1.0%
다사594440 1
 
1.0%
다사605449 1
 
1.0%
다사572437 1
 
1.0%
다사542425 1
 
1.0%
다사594427 1
 
1.0%
다사492439 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:05:08.184368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 110
13.8%
4 108
13.5%
다 82
10.2%
사 82
10.2%
6 60
7.5%
8 55
6.9%
3 50
6.2%
7 47
 
5.9%
0 44
 
5.5%
9 44
 
5.5%
Other values (4) 118
14.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 110
18.3%
4 108
18.0%
6 60
10.0%
8 55
9.2%
3 50
8.3%
7 47
7.8%
0 44
 
7.3%
9 44
 
7.3%
2 43
 
7.2%
1 39
 
6.5%
Other Letter
ValueCountFrequency (%)
다 82
41.0%
사 82
41.0%
마 18
 
9.0%
라 18
 
9.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
5 110
18.3%
4 108
18.0%
6 60
10.0%
8 55
9.2%
3 50
8.3%
7 47
7.8%
0 44
 
7.3%
9 44
 
7.3%
2 43
 
7.2%
1 39
 
6.5%
Hangul
ValueCountFrequency (%)
다 82
41.0%
사 82
41.0%
마 18
 
9.0%
라 18
 
9.0%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 110
18.3%
4 108
18.0%
6 60
10.0%
8 55
9.2%
3 50
8.3%
7 47
7.8%
0 44
 
7.3%
9 44
 
7.3%
2 43
 
7.2%
1 39
 
6.5%
Hangul
ValueCountFrequency (%)
다 82
41.0%
사 82
41.0%
마 18
 
9.0%
라 18
 
9.0%

x_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.122312
Minimum35.073125
Maximum37.682132
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:05:08.465870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.073125
5-th percentile35.107271
Q137.490685
median37.54428
Q337.587685
95-th percentile37.637016
Maximum37.682132
Range2.609007
Interquartile range (IQR)0.09700025

Descriptive statistics

Standard deviation0.93731226
Coefficient of variation (CV)0.025249296
Kurtosis0.86689565
Mean37.122312
Median Absolute Deviation (MAD)0.050017
Skewness-1.6821925
Sum3712.2312
Variance0.87855427
MonotonicityNot monotonic
2023-12-10T19:05:08.747128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.576762 1
 
1.0%
37.500447 1
 
1.0%
37.515915 1
 
1.0%
37.509761 1
 
1.0%
37.523551 1
 
1.0%
37.494558 1
 
1.0%
37.503001 1
 
1.0%
37.492325 1
 
1.0%
37.480729 1
 
1.0%
37.48298 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
35.073125 1
1.0%
35.091116 1
1.0%
35.091322 1
1.0%
35.103028 1
1.0%
35.104124 1
1.0%
35.107437 1
1.0%
35.110145 1
1.0%
35.119563 1
1.0%
35.125807 1
1.0%
35.135636 1
1.0%
ValueCountFrequency (%)
37.682132 1
1.0%
37.670578 1
1.0%
37.658932 1
1.0%
37.648263 1
1.0%
37.642789 1
1.0%
37.636712 1
1.0%
37.635688 1
1.0%
37.63208 1
1.0%
37.624865 1
1.0%
37.624263 1
1.0%

y_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.35742
Minimum126.82325
Maximum129.17875
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:05:09.150441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.82325
5-th percentile126.84884
Q1126.92594
median127.02915
Q3127.09616
95-th percentile129.06488
Maximum129.17875
Range2.355496
Interquartile range (IQR)0.17021325

Descriptive statistics

Standard deviation0.80263336
Coefficient of variation (CV)0.0063022113
Kurtosis0.82940398
Mean127.35742
Median Absolute Deviation (MAD)0.0979155
Skewness1.6570556
Sum12735.742
Variance0.64422032
MonotonicityNot monotonic
2023-12-10T19:05:09.415069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.006013 1
 
1.0%
126.929047 1
 
1.0%
127.052125 1
 
1.0%
127.043188 1
 
1.0%
127.038159 1
 
1.0%
127.04181 1
 
1.0%
127.054098 1
 
1.0%
127.016813 1
 
1.0%
126.982763 1
 
1.0%
127.040782 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.82325 1
1.0%
126.829586 1
1.0%
126.841083 1
1.0%
126.847329 1
1.0%
126.847535 1
1.0%
126.84891 1
1.0%
126.8514 1
1.0%
126.852659 1
1.0%
126.858629 1
1.0%
126.869253 1
1.0%
ValueCountFrequency (%)
129.178746 1
1.0%
129.127696 1
1.0%
129.093264 1
1.0%
129.081929 1
1.0%
129.065833 1
1.0%
129.064826 1
1.0%
129.056691 1
1.0%
129.048394 1
1.0%
129.040386 1
1.0%
129.040101 1
1.0%

oper_mby
Categorical

IMBALANCE 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
사회복지법인
84 
학교법인
 
6
지자체
 
3
재단법인
 
3
사단법인
 
2
Other values (2)
 
2

Length

Max length6
Median length6
Mean length5.64
Min length2

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row사회복지법인
2nd row사회복지법인
3rd row사회복지법인
4th row지자체
5th row지자체

Common Values

ValueCountFrequency (%)
사회복지법인 84
84.0%
학교법인 6
 
6.0%
지자체 3
 
3.0%
재단법인 3
 
3.0%
사단법인 2
 
2.0%
기타 1
 
1.0%
지방공기업 1
 
1.0%

Length

2023-12-10T19:05:09.875213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:05:10.226767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사회복지법인 84
84.0%
학교법인 6
 
6.0%
지자체 3
 
3.0%
재단법인 3
 
3.0%
사단법인 2
 
2.0%
기타 1
 
1.0%
지방공기업 1
 
1.0%

telno
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:05:10.781495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length11.49
Min length11

Characters and Unicode

Total characters1149
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row02-742-9500
2nd row02-6247-9900
3rd row02-6220-8500
4th row02-2234-3515
5th row02-2234-3517
ValueCountFrequency (%)
02-742-9500 1
 
1.0%
02-2038-8846 1
 
1.0%
02-3467-9900 1
 
1.0%
02-548-9898 1
 
1.0%
02-501-5674 1
 
1.0%
02-564-0108 1
 
1.0%
02-3474-6080 1
 
1.0%
02-581-7992 1
 
1.0%
02-578-1515 1
 
1.0%
02-888-6144 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:05:11.430968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 201
17.5%
- 200
17.4%
2 157
13.7%
4 82
7.1%
5 82
7.1%
9 81
7.0%
1 80
 
7.0%
3 78
 
6.8%
6 75
 
6.5%
8 61
 
5.3%
Other values (2) 52
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 948
82.5%
Dash Punctuation 200
 
17.4%
Math Symbol 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 201
21.2%
2 157
16.6%
4 82
8.6%
5 82
8.6%
9 81
8.5%
1 80
 
8.4%
3 78
 
8.2%
6 75
 
7.9%
8 61
 
6.4%
7 51
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 200
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1149
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 201
17.5%
- 200
17.4%
2 157
13.7%
4 82
7.1%
5 82
7.1%
9 81
7.0%
1 80
 
7.0%
3 78
 
6.8%
6 75
 
6.5%
8 61
 
5.3%
Other values (2) 52
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1149
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 201
17.5%
- 200
17.4%
2 157
13.7%
4 82
7.1%
5 82
7.1%
9 81
7.0%
1 80
 
7.0%
3 78
 
6.8%
6 75
 
6.5%
8 61
 
5.3%
Other values (2) 52
 
4.5%

x_utmk_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean988185.34
Minimum940180
Maximum1152872
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:05:11.745791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum940180
5-th percentile942468.05
Q1949276.5
median958433
Q3964316.25
95-th percentile1142566.1
Maximum1152872
Range212692
Interquartile range (IQR)15039.75

Descriptive statistics

Standard deviation72553.894
Coefficient of variation (CV)0.073421342
Kurtosis0.83193377
Mean988185.34
Median Absolute Deviation (MAD)8644.5
Skewness1.6586084
Sum98818534
Variance5.2640675 × 109
MonotonicityNot monotonic
2023-12-10T19:05:12.537942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
956382 1
 
1.0%
949534 1
 
1.0%
960422 1
 
1.0%
959628 1
 
1.0%
959191 1
 
1.0%
959498 1
 
1.0%
960589 1
 
1.0%
957288 1
 
1.0%
954270 1
 
1.0%
959401 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
940180 1
1.0%
940767 1
1.0%
941786 1
1.0%
942326 1
1.0%
942374 1
1.0%
942473 1
1.0%
942703 1
1.0%
942822 1
1.0%
943318 1
1.0%
944276 1
1.0%
ValueCountFrequency (%)
1152872 1
1.0%
1148212 1
1.0%
1145154 1
1.0%
1143987 1
1.0%
1142606 1
1.0%
1142564 1
1.0%
1141900 1
1.0%
1141040 1
1.0%
1140387 1
1.0%
1140354 1
1.0%

y_utmk_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1902937.9
Minimum1676386
Maximum1964831
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:05:12.872437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1676386
5-th percentile1680179.1
Q11943590.5
median1949543.5
Q31954331.2
95-th percentile1959825.1
Maximum1964831
Range288445
Interquartile range (IQR)10740.75

Descriptive statistics

Standard deviation103590.59
Coefficient of variation (CV)0.054437192
Kurtosis0.86697014
Mean1902937.9
Median Absolute Deviation (MAD)5579.5
Skewness-1.6821803
Sum1.9029378 × 108
Variance1.0731011 × 1010
MonotonicityNot monotonic
2023-12-10T19:05:13.202814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1953157 1
 
1.0%
1944729 1
 
1.0%
1946386 1
 
1.0%
1945707 1
 
1.0%
1947239 1
 
1.0%
1944021 1
 
1.0%
1944953 1
 
1.0%
1943784 1
 
1.0%
1942514 1
 
1.0%
1942737 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1676386 1
1.0%
1678440 1
1.0%
1678441 1
1.0%
1679681 1
1.0%
1679840 1
1.0%
1680197 1
1.0%
1680517 1
1.0%
1681565 1
1.0%
1682265 1
1.0%
1683390 1
1.0%
ValueCountFrequency (%)
1964831 1
1.0%
1963554 1
1.0%
1962260 1
1.0%
1961082 1
1.0%
1960453 1
1.0%
1959792 1
1.0%
1959689 1
1.0%
1959332 1
1.0%
1958538 1
1.0%
1958407 1
1.0%

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

2023-12-10T19:05:13.528239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:05:13.688953image/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
공공데이터포털
100 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공데이터포털 100
100.0%

Length

2023-12-10T19:05:13.964153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:05:14.112922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공데이터포털 100
100.0%

FILE_NAME
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC_485_DMSTC_MCST_OLDLSR_2019
100 

Length

Max length29
Median length29
Mean length29
Min length29

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_485_DMSTC_MCST_OLDLSR_2019
2nd rowKC_485_DMSTC_MCST_OLDLSR_2019
3rd rowKC_485_DMSTC_MCST_OLDLSR_2019
4th rowKC_485_DMSTC_MCST_OLDLSR_2019
5th rowKC_485_DMSTC_MCST_OLDLSR_2019

Common Values

ValueCountFrequency (%)
KC_485_DMSTC_MCST_OLDLSR_2019 100
100.0%

Length

2023-12-10T19:05:14.306700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:05:14.481951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_485_dmstc_mcst_oldlsr_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

2023-12-10T19:05:14.687099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:05:14.858312image/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_cdoper_mbytelnox_utmk_cdy_utmk_cdlst_updt_dtdata_orgnFILE_NAMEbase_ymd
0KC485PC19N000001문화시설복지종로노인종합복지관서울특별시종로구1111016500이화동1111064000이화동111104100223서울특별시 종로구 율곡로19길 17-8 (이화동)3100다사56353137.576762127.006013사회복지법인02-742-9500956382195315720191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
1KC485PC19N000002문화시설복지종로노인종합복지관 무악센터서울특별시종로구1111018700무악동1111057000무악동111104100479서울특별시 종로구 통일로14길 36 (무악동)3030다사52153037.575907126.958126사회복지법인02-6247-9900952153195308620191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
2KC485PC19N000003문화시설복지서울노인복지센터서울특별시종로구1111013400경운동1111061500종로1.2.3.4가동111102100001서울특별시 종로구 삼일대로 467 (경운동)3147다사54553037.576013126.985804사회복지법인02-6220-8500954597195308420191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
3KC485PC19N000004문화시설복지약수노인종합복지관서울특별시중구1114016200신당동1114063500약수동111404103074서울특별시 중구 다산로6길 11 (신당동)4597다사56650437.552461127.009313지자체02-2234-3515956659195046020191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
4KC485PC19N000005문화시설복지청구노인복지센터서울특별시중구1114016200신당동1114064500청구동111404103303서울특별시 중구 청구로3길 69 (신당동)4591다사57150937.55654127.014318지자체02-2234-3517957104195091020191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
5KC485PC19N000006문화시설복지용산노인종합복지관서울특별시용산구1117013100한남동1117068500한남동111704106039서울특별시 용산구 독서당로11길 16 (한남동)4410다사56348137.531344127.006481사회복지법인02-794-6100956397194811820191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
6KC485PC19N000007문화시설복지구립청파노인복지센터서울특별시용산구1117010800서계동1117055500청파동111704106389서울특별시 용산구 청파로83길 26 (서계동)4303다사52950437.552006126.967694사회복지법인02-703-6011952983195042920191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
7KC485PC19N000008문화시설복지왕십리도선동노인복지센터서울특별시성동구1120010100상왕십리동1120053500왕십리도선동112003005009서울특별시 성동구 마장로 141 (상왕십리동)4700다사58052137.567878127.025511사회복지법인02-6925-0456958099195216320191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
8KC485PC19N000009문화시설복지사근동노인복지센터서울특별시성동구1120010600사근동1120055000사근동112004109297서울특별시 성동구 사근동길 37 (사근동)4761다사59851437.561498127.045311사단법인02-6956-0707959844195144620191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
9KC485PC19N000010문화시설복지성동노인종합복지관서울특별시성동구1120010500마장동1120054000마장동112003103002서울특별시 성동구 마조로 77 (마장동)4759다사59451837.564809127.041319사회복지법인02-6341-8642959493195181520191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
idlclasmlsfcfclt_namectprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrzip_cdgrid_cdx_cdy_cdoper_mbytelnox_utmk_cdy_utmk_cdlst_updt_dtdata_orgnFILE_NAMEbase_ymd
90KC485PC19N000091문화시설복지영도구노인복지관분관부산광역시영도구2620012000청학동2620063000청학제1동262004184112부산광역시 영도구 봉래길 372 (청학동)49032마라41878435.091116129.056691사회복지법인051-418-63001141900167844120191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
91KC485PC19N000092문화시설복지다사랑복합문화예술회관부산광역시부산진구2623011000가야동2623071000가야제1동262303129008부산광역시 부산진구 대학로 60 (가야동)47336마라39784935.150457129.034499사회복지법인051-891-17431139775168499120191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
92KC485PC19N000093문화시설복지부산진구 노인복지관부산광역시부산진구2623010200전포동2623061000전포제2동262304187677부산광역시 부산진구 전포대로300번길 6 (전포동)47236마라42686535.16403129.065833사회복지법인051-808-80901142606168654120191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
93KC485PC19N000094문화시설복지부산진구 노인복지관 신암분관부산광역시부산진구2623010400범천동2623078000범천제2동262304187482부산광역시 부산진구 신암로135번길 35 (범천동)47348마라41085135.151446129.048394사회복지법인051-714-60901141040168512020191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
94KC485PC19N000095문화시설복지동래구노인복지관부산광역시동래구2626010700명륜동2626054500명륜동262604190116부산광역시 동래구 명륜로207번길 18 (명륜동)47742마라43991935.212382129.081929학교법인051-554-62521143987169192720191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
95KC485PC19N000096문화시설복지남구노인복지관부산광역시남구2629010600대연동2629055000대연제5동262903131008부산광역시 남구 못골로 97-10 (대연동)48444마라45183435.136176129.093264학교법인051-628-12911145154168349120191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
96KC485PC19N000097문화시설복지실버벨노인복지관부산광역시북구2632010500구포동2632052100구포제3동263204196298부산광역시 북구 시랑로114번길 45 (구포동)46643마라37389835.19423129.008634사회복지법인051-337-59591137346168981020191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
97KC485PC19N000098문화시설복지어진샘노인종합복지관부산광역시해운대구2635010400재송동2635065000재송제1동263504199162부산광역시 해운대구 재반로12번길 16 (재송동)48057마라48288335.179839129.127696사회복지법인051-784-80081148212168838520191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
98KC485PC19N000099문화시설복지장산노인복지관부산광역시해운대구2635010700좌동2635055100좌제1동263503133038부산광역시 해운대구 좌동로 126 (좌동)48107마라52887735.173738129.178746사회복지법인051-704-91411152872168778520191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125
99KC485PC19N000100문화시설복지사하사랑채노인복지관부산광역시사하구2638010100괴정동2638053000괴정제3동263803134014부산광역시 사하구 사리로 35 (괴정동)49339마라36579635.103028128.998723사회복지법인051-293-95441136596167968120191113공공데이터포털KC_485_DMSTC_MCST_OLDLSR_201920191125