Overview

Dataset statistics

Number of variables24
Number of observations30
Missing cells160
Missing cells (%)22.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 KiB
Average record size in memory211.4 B

Variable types

Categorical3
Numeric10
Text7
Unsupported3
DateTime1

Dataset

Description샘플 데이터
Author통계청
URLhttps://bigdata.seoul.go.kr/data/selectSampleData.do?sample_data_seq=45

Alerts

년도(year) has constant value ""Constant
부번(buld_slno_no) is highly imbalanced (78.9%)Imbalance
건물명(buld_nm) has 6 (20.0%) missing valuesMissing
건물동(buld_dong) has 28 (93.3%) missing valuesMissing
건물층(buld_floor) has 9 (30.0%) missing valuesMissing
건물호(buld_ho) has 19 (63.3%) missing valuesMissing
지번_본번(mnnm_no) has 2 (6.7%) missing valuesMissing
지번_부번(slno_no) has 6 (20.0%) missing valuesMissing
전화번호_지역(telno_area) has 30 (100.0%) missing valuesMissing
전화번호1(telno_1) has 30 (100.0%) missing valuesMissing
전화번호2(telno_2) has 30 (100.0%) missing valuesMissing
데이터_일련번호(data_sno) has unique valuesUnique
기업명(entrprs_nm) has unique valuesUnique
업종명(induty_nm) has unique valuesUnique
x좌표(xcrd) has unique valuesUnique
전화번호_지역(telno_area) is an unsupported type, check if it needs cleaning or further analysisUnsupported
전화번호1(telno_1) is an unsupported type, check if it needs cleaning or further analysisUnsupported
전화번호2(telno_2) is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 14:59:31.632337
Analysis finished2023-12-10 14:59:32.370601
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도(year)
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2016
30 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2016
2nd row2016
3rd row2016
4th row2016
5th row2016

Common Values

ValueCountFrequency (%)
2016 30
100.0%

Length

2023-12-10T23:59:32.515465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:59:32.774919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2016 30
100.0%

데이터_일련번호(data_sno)
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0048968 × 108
Minimum90260
Maximum7.0010074 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:59:33.014838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum90260
5-th percentile125155.4
Q1218000.75
median431228.5
Q3589698
95-th percentile2.7515474 × 109
Maximum7.0010074 × 109
Range7.0009172 × 109
Interquartile range (IQR)371697.25

Descriptive statistics

Standard deviation1.5450027 × 109
Coefficient of variation (CV)3.8577841
Kurtosis14.136731
Mean4.0048968 × 108
Median Absolute Deviation (MAD)204879.5
Skewness3.8389941
Sum1.201469 × 1010
Variance2.3870334 × 1018
MonotonicityNot monotonic
2023-12-10T23:59:33.310424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
546719 1
 
3.3%
501324 1
 
3.3%
503419 1
 
3.3%
567027 1
 
3.3%
685866 1
 
3.3%
371190 1
 
3.3%
442144 1
 
3.3%
7001007434 1
 
3.3%
312899 1
 
3.3%
174955 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
90260 1
3.3%
108959 1
3.3%
144951 1
3.3%
148693 1
3.3%
162538 1
3.3%
174955 1
3.3%
184599 1
3.3%
210574 1
3.3%
240281 1
3.3%
312899 1
3.3%
ValueCountFrequency (%)
7001007434 1
3.3%
5002161353 1
3.3%
797098 1
3.3%
762920 1
3.3%
693379 1
3.3%
685866 1
3.3%
650040 1
3.3%
597255 1
3.3%
567027 1
3.3%
546719 1
3.3%

행정동_코드(adstrd_code_se)
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1115664.7
Minimum1102052
Maximum1125074
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:59:33.589276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1102052
5-th percentile1102521
Q11107328.5
median1118552.5
Q31122064
95-th percentile1124075.1
Maximum1125074
Range23022
Interquartile range (IQR)14735.5

Descriptive statistics

Standard deviation7992.1839
Coefficient of variation (CV)0.0071636077
Kurtosis-1.2642066
Mean1115664.7
Median Absolute Deviation (MAD)4509.5
Skewness-0.58437645
Sum33469940
Variance63875004
MonotonicityNot monotonic
2023-12-10T23:59:33.871626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1123053 2
 
6.7%
1119054 1
 
3.3%
1106083 1
 
3.3%
1117054 1
 
3.3%
1122065 1
 
3.3%
1104068 1
 
3.3%
1105056 1
 
3.3%
1122055 1
 
3.3%
1125074 1
 
3.3%
1102052 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
1102052 1
3.3%
1102071 1
3.3%
1103071 1
3.3%
1104054 1
3.3%
1104068 1
3.3%
1105056 1
3.3%
1106081 1
3.3%
1106083 1
3.3%
1111065 1
3.3%
1112072 1
3.3%
ValueCountFrequency (%)
1125074 1
3.3%
1124081 1
3.3%
1124068 1
3.3%
1123071 1
3.3%
1123053 2
6.7%
1123052 1
3.3%
1122065 1
3.3%
1122061 1
3.3%
1122055 1
3.3%
1122054 1
3.3%

기업명(entrprs_nm)
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:59:34.269632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length9.1
Min length3

Characters and Unicode

Total characters273
Distinct characters125
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row(주)제일FNE
2nd rowDHL
3rd row㈜케이티서비스북부중랑지점
4th row덕진티엠에스주식회사
5th row(주)월드안전
ValueCountFrequency (%)
주식회사 2
 
5.6%
주)제일fne 1
 
2.8%
주)지화이브 1
 
2.8%
새마을 1
 
2.8%
휘트니스 1
 
2.8%
함박웃음치과의원 1
 
2.8%
금하텔레콤(주 1
 
2.8%
로담건축(주 1
 
2.8%
주)고어코리아 1
 
2.8%
유앤미의원 1
 
2.8%
Other values (25) 25
69.4%
2023-12-10T23:59:34.929189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 22
 
8.1%
( 18
 
6.6%
) 18
 
6.6%
스 9
 
3.3%
사 8
 
2.9%
이 7
 
2.6%
6
 
2.2%
무 5
 
1.8%
회 5
 
1.8%
리 4
 
1.5%
Other values (115) 171
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 222
81.3%
Open Punctuation 18
 
6.6%
Close Punctuation 18
 
6.6%
Space Separator 6
 
2.2%
Uppercase Letter 6
 
2.2%
Dash Punctuation 1
 
0.4%
Other Symbol 1
 
0.4%
Decimal Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 22
 
9.9%
스 9
 
4.1%
사 8
 
3.6%
이 7
 
3.2%
무 5
 
2.3%
회 5
 
2.3%
리 4
 
1.8%
어 4
 
1.8%
식 4
 
1.8%
서 4
 
1.8%
Other values (103) 150
67.6%
Uppercase Letter
ValueCountFrequency (%)
L 1
16.7%
H 1
16.7%
D 1
16.7%
E 1
16.7%
N 1
16.7%
F 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 223
81.7%
Common 44
 
16.1%
Latin 6
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 22
 
9.9%
스 9
 
4.0%
사 8
 
3.6%
이 7
 
3.1%
무 5
 
2.2%
회 5
 
2.2%
리 4
 
1.8%
어 4
 
1.8%
식 4
 
1.8%
서 4
 
1.8%
Other values (104) 151
67.7%
Latin
ValueCountFrequency (%)
L 1
16.7%
H 1
16.7%
D 1
16.7%
E 1
16.7%
N 1
16.7%
F 1
16.7%
Common
ValueCountFrequency (%)
( 18
40.9%
) 18
40.9%
6
 
13.6%
- 1
 
2.3%
2 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 222
81.3%
ASCII 50
 
18.3%
None 1
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 22
 
9.9%
스 9
 
4.1%
사 8
 
3.6%
이 7
 
3.2%
무 5
 
2.3%
회 5
 
2.3%
리 4
 
1.8%
어 4
 
1.8%
식 4
 
1.8%
서 4
 
1.8%
Other values (103) 150
67.6%
ASCII
ValueCountFrequency (%)
( 18
36.0%
) 18
36.0%
6
 
12.0%
- 1
 
2.0%
L 1
 
2.0%
H 1
 
2.0%
D 1
 
2.0%
E 1
 
2.0%
N 1
 
2.0%
F 1
 
2.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

업종코드(induty_code)
Real number (ℝ)

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54764.5
Minimum13222
Maximum96991
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:59:35.199315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13222
5-th percentile14112
Q143425
median58171.5
Q371345.25
95-th percentile85957.65
Maximum96991
Range83769
Interquartile range (IQR)27920.25

Descriptive statistics

Standard deviation23339.962
Coefficient of variation (CV)0.4261878
Kurtosis-0.64468701
Mean54764.5
Median Absolute Deviation (MAD)14490.5
Skewness-0.22793316
Sum1642935
Variance5.4475382 × 108
MonotonicityNot monotonic
2023-12-10T23:59:35.437703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
58221 4
 
13.3%
42412 2
 
6.7%
14112 2
 
6.7%
75992 1
 
3.3%
58122 1
 
3.3%
46599 1
 
3.3%
85501 1
 
3.3%
29294 1
 
3.3%
46592 1
 
3.3%
86202 1
 
3.3%
Other values (15) 15
50.0%
ValueCountFrequency (%)
13222 1
3.3%
14112 2
6.7%
18112 1
3.3%
25922 1
3.3%
29294 1
3.3%
42412 2
6.7%
46464 1
3.3%
46592 1
3.3%
46599 1
3.3%
46799 1
3.3%
ValueCountFrequency (%)
96991 1
3.3%
86202 1
3.3%
85659 1
3.3%
85502 1
3.3%
85501 1
3.3%
75992 1
3.3%
75110 1
3.3%
71393 1
3.3%
71202 1
3.3%
68112 1
3.3%

업종명(induty_nm)
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:59:35.805173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length7.5333333
Min length2

Characters and Unicode

Total characters226
Distinct characters118
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

Unique30 ?
Unique (%)100.0%

Sample

1st row유통
2nd row가방끈 제조
3rd row드론응용소프트웨어개발
4th row논술
5th row방송프로그램제작
ValueCountFrequency (%)
서비스 4
 
9.3%
유통 1
 
2.3%
조립제품 1
 
2.3%
의료기기(신체보정용기기 1
 
2.3%
화물운송 1
 
2.3%
알선 1
 
2.3%
측정측량기 1
 
2.3%
정밀기기도매업 1
 
2.3%
건물및토목엔지니어링 1
 
2.3%
디자인 1
 
2.3%
Other values (30) 30
69.8%
2023-12-10T23:59:36.886538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13
 
5.8%
기 10
 
4.4%
스 9
 
4.0%
서 7
 
3.1%
건 7
 
3.1%
비 7
 
3.1%
어 6
 
2.7%
제 6
 
2.7%
공 5
 
2.2%
축 5
 
2.2%
Other values (108) 151
66.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 206
91.2%
Space Separator 13
 
5.8%
Uppercase Letter 3
 
1.3%
Other Punctuation 2
 
0.9%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 10
 
4.9%
스 9
 
4.4%
서 7
 
3.4%
건 7
 
3.4%
비 7
 
3.4%
어 6
 
2.9%
제 6
 
2.9%
공 5
 
2.4%
축 5
 
2.4%
관 4
 
1.9%
Other values (100) 140
68.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
R 1
33.3%
E 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 206
91.2%
Common 17
 
7.5%
Latin 3
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 10
 
4.9%
스 9
 
4.4%
서 7
 
3.4%
건 7
 
3.4%
비 7
 
3.4%
어 6
 
2.9%
제 6
 
2.9%
공 5
 
2.4%
축 5
 
2.4%
관 4
 
1.9%
Other values (100) 140
68.0%
Common
ValueCountFrequency (%)
13
76.5%
) 1
 
5.9%
( 1
 
5.9%
, 1
 
5.9%
. 1
 
5.9%
Latin
ValueCountFrequency (%)
P 1
33.3%
R 1
33.3%
E 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 206
91.2%
ASCII 20
 
8.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13
65.0%
) 1
 
5.0%
( 1
 
5.0%
, 1
 
5.0%
P 1
 
5.0%
R 1
 
5.0%
E 1
 
5.0%
. 1
 
5.0%
Hangul
ValueCountFrequency (%)
기 10
 
4.9%
스 9
 
4.4%
서 7
 
3.4%
건 7
 
3.4%
비 7
 
3.4%
어 6
 
2.9%
제 6
 
2.9%
공 5
 
2.4%
축 5
 
2.4%
관 4
 
1.9%
Other values (100) 140
68.0%

도로명(rn)
Text

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:59:37.286902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.2
Min length3

Characters and Unicode

Total characters156
Distinct characters59
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

Unique26 ?
Unique (%)86.7%

Sample

1st row테헤란로
2nd row남부순환로
3rd row디지털로
4th row영신로34길
5th row도산대로68길
ValueCountFrequency (%)
테헤란로 2
 
6.7%
도봉로 2
 
6.7%
디지털로26길 1
 
3.3%
종로3길 1
 
3.3%
면목로 1
 
3.3%
방배천로24길 1
 
3.3%
통일로 1
 
3.3%
이태원로 1
 
3.3%
강남대로66길 1
 
3.3%
국제금융로 1
 
3.3%
Other values (18) 18
60.0%
2023-12-10T23:59:38.074038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 30
19.2%
길 13
 
8.3%
3 9
 
5.8%
디 5
 
3.2%
지 5
 
3.2%
털 5
 
3.2%
산 5
 
3.2%
6 4
 
2.6%
남 4
 
2.6%
1 4
 
2.6%
Other values (49) 72
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130
83.3%
Decimal Number 26
 
16.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 30
23.1%
길 13
 
10.0%
디 5
 
3.8%
지 5
 
3.8%
털 5
 
3.8%
산 5
 
3.8%
남 4
 
3.1%
대 4
 
3.1%
도 3
 
2.3%
헤 2
 
1.5%
Other values (42) 54
41.5%
Decimal Number
ValueCountFrequency (%)
3 9
34.6%
6 4
15.4%
1 4
15.4%
2 4
15.4%
5 2
 
7.7%
4 2
 
7.7%
8 1
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130
83.3%
Common 26
 
16.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 30
23.1%
길 13
 
10.0%
디 5
 
3.8%
지 5
 
3.8%
털 5
 
3.8%
산 5
 
3.8%
남 4
 
3.1%
대 4
 
3.1%
도 3
 
2.3%
헤 2
 
1.5%
Other values (42) 54
41.5%
Common
ValueCountFrequency (%)
3 9
34.6%
6 4
15.4%
1 4
15.4%
2 4
15.4%
5 2
 
7.7%
4 2
 
7.7%
8 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130
83.3%
ASCII 26
 
16.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 30
23.1%
길 13
 
10.0%
디 5
 
3.8%
지 5
 
3.8%
털 5
 
3.8%
산 5
 
3.8%
남 4
 
3.1%
대 4
 
3.1%
도 3
 
2.3%
헤 2
 
1.5%
Other values (42) 54
41.5%
ASCII
ValueCountFrequency (%)
3 9
34.6%
6 4
15.4%
1 4
15.4%
2 4
15.4%
5 2
 
7.7%
4 2
 
7.7%
8 1
 
3.8%

건물번호(buld_no)
Real number (ℝ)

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean168.73333
Minimum7
Maximum728
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:59:38.404722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile9
Q116.75
median88.5
Q3212.5
95-th percentile627.8
Maximum728
Range721
Interquartile range (IQR)195.75

Descriptive statistics

Standard deviation216.62775
Coefficient of variation (CV)1.2838468
Kurtosis1.1020267
Mean168.73333
Median Absolute Deviation (MAD)76.5
Skewness1.499582
Sum5062
Variance46927.582
MonotonicityNot monotonic
2023-12-10T23:59:38.777529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
111 2
 
6.7%
11 2
 
6.7%
22 2
 
6.7%
9 2
 
6.7%
124 1
 
3.3%
51 1
 
3.3%
202 1
 
3.3%
13 1
 
3.3%
698 1
 
3.3%
15 1
 
3.3%
Other values (16) 16
53.3%
ValueCountFrequency (%)
7 1
3.3%
9 2
6.7%
10 1
3.3%
11 2
6.7%
13 1
3.3%
15 1
3.3%
22 2
6.7%
29 1
3.3%
30 1
3.3%
33 1
3.3%
ValueCountFrequency (%)
728 1
3.3%
698 1
3.3%
542 1
3.3%
524 1
3.3%
457 1
3.3%
428 1
3.3%
248 1
3.3%
216 1
3.3%
202 1
3.3%
124 1
3.3%

부번(buld_slno_no)
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
29 
14
 
1

Length

Max length4
Median length4
Mean length3.9333333
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row<NA>
2nd row<NA>
3rd row14
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 29
96.7%
14 1
 
3.3%

Length

2023-12-10T23:59:39.074272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:59:39.325148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
96.7%
14 1
 
3.3%

건물명(buld_nm)
Text

MISSING 

Distinct23
Distinct (%)95.8%
Missing6
Missing (%)20.0%
Memory size372.0 B
2023-12-10T23:59:39.632170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9.5
Mean length4.9583333
Min length2

Characters and Unicode

Total characters119
Distinct characters49
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)91.7%

Sample

1st row해*
2nd row연*뉴*
3rd row로*어*타*
4th row대*월*마*용*
5th row원*전*상*
ValueCountFrequency (%)
상 2
 
8.3%
오*빌 1
 
4.2%
해 1
 
4.2%
신*빌 1
 
4.2%
벽*경*디*털*리*차 1
 
4.2%
한*i*타*2 1
 
4.2%
산 1
 
4.2%
대*아*알 1
 
4.2%
에*에*프*자 1
 
4.2%
금*동*신*플*스*파*상 1
 
4.2%
Other values (13) 13
54.2%
2023-12-10T23:59:40.538204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 56
47.1%
빌 5
 
4.2%
상 4
 
3.4%
신 4
 
3.4%
대 3
 
2.5%
타 2
 
1.7%
에 2
 
1.7%
원 2
 
1.7%
한 1
 
0.8%
스 1
 
0.8%
Other values (39) 39
32.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61
51.3%
Other Punctuation 56
47.1%
Decimal Number 1
 
0.8%
Uppercase Letter 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
빌 5
 
8.2%
상 4
 
6.6%
신 4
 
6.6%
대 3
 
4.9%
타 2
 
3.3%
에 2
 
3.3%
원 2
 
3.3%
한 1
 
1.6%
스 1
 
1.6%
파 1
 
1.6%
Other values (36) 36
59.0%
Other Punctuation
ValueCountFrequency (%)
* 56
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
I 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61
51.3%
Common 57
47.9%
Latin 1
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
빌 5
 
8.2%
상 4
 
6.6%
신 4
 
6.6%
대 3
 
4.9%
타 2
 
3.3%
에 2
 
3.3%
원 2
 
3.3%
한 1
 
1.6%
스 1
 
1.6%
파 1
 
1.6%
Other values (36) 36
59.0%
Common
ValueCountFrequency (%)
* 56
98.2%
2 1
 
1.8%
Latin
ValueCountFrequency (%)
I 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61
51.3%
ASCII 58
48.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 56
96.6%
2 1
 
1.7%
I 1
 
1.7%
Hangul
ValueCountFrequency (%)
빌 5
 
8.2%
상 4
 
6.6%
신 4
 
6.6%
대 3
 
4.9%
타 2
 
3.3%
에 2
 
3.3%
원 2
 
3.3%
한 1
 
1.6%
스 1
 
1.6%
파 1
 
1.6%
Other values (36) 36
59.0%

건물동(buld_dong)
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing28
Missing (%)93.3%
Memory size372.0 B
2023-12-10T23:59:40.740318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowY
2nd rowD
ValueCountFrequency (%)
y 1
50.0%
d 1
50.0%
2023-12-10T23:59:41.464833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 1
50.0%
D 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 1
50.0%
D 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 1
50.0%
D 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 1
50.0%
D 1
50.0%

건물층(buld_floor)
Text

MISSING 

Distinct11
Distinct (%)52.4%
Missing9
Missing (%)30.0%
Memory size372.0 B
2023-12-10T23:59:41.654039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.6190476
Min length1

Characters and Unicode

Total characters34
Distinct characters9
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

Unique7 ?
Unique (%)33.3%

Sample

1st row8
2nd row5*7*8
3rd row8
4th row1
5th row1*,*5
ValueCountFrequency (%)
1 9
42.9%
2 3
 
14.3%
8 2
 
9.5%
6 2
 
9.5%
5*7*8 1
 
4.8%
1*,*5 1
 
4.8%
5 1
 
4.8%
4 1
 
4.8%
7 1
 
4.8%
2023-12-10T23:59:42.252196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
29.4%
* 9
26.5%
2 3
 
8.8%
8 3
 
8.8%
5 3
 
8.8%
7 2
 
5.9%
6 2
 
5.9%
, 1
 
2.9%
4 1
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24
70.6%
Other Punctuation 10
29.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10
41.7%
2 3
 
12.5%
8 3
 
12.5%
5 3
 
12.5%
7 2
 
8.3%
6 2
 
8.3%
4 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
* 9
90.0%
, 1
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 10
29.4%
* 9
26.5%
2 3
 
8.8%
8 3
 
8.8%
5 3
 
8.8%
7 2
 
5.9%
6 2
 
5.9%
, 1
 
2.9%
4 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10
29.4%
* 9
26.5%
2 3
 
8.8%
8 3
 
8.8%
5 3
 
8.8%
7 2
 
5.9%
6 2
 
5.9%
, 1
 
2.9%
4 1
 
2.9%

건물호(buld_ho)
Text

MISSING 

Distinct11
Distinct (%)100.0%
Missing19
Missing (%)63.3%
Memory size372.0 B
2023-12-10T23:59:42.587676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.3636364
Min length3

Characters and Unicode

Total characters37
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)100.0%

Sample

1st row2*2
2nd row5*2
3rd row2*9
4th row6*1
5th row4*2
ValueCountFrequency (%)
2*2 1
9.1%
5*2 1
9.1%
2*9 1
9.1%
6*1 1
9.1%
4*2 1
9.1%
2*1 1
9.1%
2*8*2*9 1
9.1%
8*1 1
9.1%
b*1 1
9.1%
3*1 1
9.1%
2023-12-10T23:59:43.396732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 13
35.1%
2 9
24.3%
1 5
 
13.5%
5 2
 
5.4%
9 2
 
5.4%
8 2
 
5.4%
6 1
 
2.7%
4 1
 
2.7%
B 1
 
2.7%
3 1
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23
62.2%
Other Punctuation 13
35.1%
Uppercase Letter 1
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 9
39.1%
1 5
21.7%
5 2
 
8.7%
9 2
 
8.7%
8 2
 
8.7%
6 1
 
4.3%
4 1
 
4.3%
3 1
 
4.3%
Other Punctuation
ValueCountFrequency (%)
* 13
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36
97.3%
Latin 1
 
2.7%

Most frequent character per script

Common
ValueCountFrequency (%)
* 13
36.1%
2 9
25.0%
1 5
 
13.9%
5 2
 
5.6%
9 2
 
5.6%
8 2
 
5.6%
6 1
 
2.8%
4 1
 
2.8%
3 1
 
2.8%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 13
35.1%
2 9
24.3%
1 5
 
13.5%
5 2
 
5.4%
9 2
 
5.4%
8 2
 
5.4%
6 1
 
2.7%
4 1
 
2.7%
B 1
 
2.7%
3 1
 
2.7%

지번_본번(mnnm_no)
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)96.4%
Missing2
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean503.78571
Minimum69
Maximum1320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:59:43.687490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum69
5-th percentile88.7
Q1263.25
median505
Q3672.75
95-th percentile1015.85
Maximum1320
Range1251
Interquartile range (IQR)409.5

Descriptive statistics

Standard deviation307.90864
Coefficient of variation (CV)0.6111897
Kurtosis0.46527145
Mean503.78571
Median Absolute Deviation (MAD)187.5
Skewness0.58510455
Sum14106
Variance94807.73
MonotonicityNot monotonic
2023-12-10T23:59:44.017793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
644 2
 
6.7%
90 1
 
3.3%
605 1
 
3.3%
732 1
 
3.3%
510 1
 
3.3%
490 1
 
3.3%
1054 1
 
3.3%
178 1
 
3.3%
133 1
 
3.3%
110 1
 
3.3%
Other values (17) 17
56.7%
(Missing) 2
 
6.7%
ValueCountFrequency (%)
69 1
3.3%
88 1
3.3%
90 1
3.3%
110 1
3.3%
133 1
3.3%
178 1
3.3%
201 1
3.3%
284 1
3.3%
341 1
3.3%
371 1
3.3%
ValueCountFrequency (%)
1320 1
3.3%
1054 1
3.3%
945 1
3.3%
732 1
3.3%
724 1
3.3%
707 1
3.3%
678 1
3.3%
671 1
3.3%
644 2
6.7%
635 1
3.3%

지번_부번(slno_no)
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)83.3%
Missing6
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean19.708333
Minimum1
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:59:44.271556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.3
Q17.5
median15.5
Q326.25
95-th percentile54.25
Maximum90
Range89
Interquartile range (IQR)18.75

Descriptive statistics

Standard deviation19.685526
Coefficient of variation (CV)0.99884275
Kurtosis6.7504786
Mean19.708333
Median Absolute Deviation (MAD)10
Skewness2.3479879
Sum473
Variance387.51993
MonotonicityNot monotonic
2023-12-10T23:59:44.524884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
8 2
 
6.7%
18 2
 
6.7%
4 2
 
6.7%
20 2
 
6.7%
6 1
 
3.3%
5 1
 
3.3%
30 1
 
3.3%
26 1
 
3.3%
11 1
 
3.3%
12 1
 
3.3%
Other values (10) 10
33.3%
(Missing) 6
20.0%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
4 2
6.7%
5 1
3.3%
6 1
3.3%
8 2
6.7%
11 1
3.3%
12 1
3.3%
13 1
3.3%
14 1
3.3%
ValueCountFrequency (%)
90 1
3.3%
58 1
3.3%
33 1
3.3%
30 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
20 2
6.7%
18 2
6.7%
17 1
3.3%

전화번호_지역(telno_area)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

전화번호1(telno_1)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

전화번호2(telno_2)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

사용근로자수(cmcl_labrr_co)
Real number (ℝ)

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88.366667
Minimum10
Maximum1374
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:59:44.796367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile10.45
Q113
median19
Q354.75
95-th percentile225
Maximum1374
Range1364
Interquartile range (IQR)41.75

Descriptive statistics

Standard deviation249.63359
Coefficient of variation (CV)2.8249746
Kurtosis26.518337
Mean88.366667
Median Absolute Deviation (MAD)6.5
Skewness5.0404578
Sum2651
Variance62316.93
MonotonicityNot monotonic
2023-12-10T23:59:45.039401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
13 5
16.7%
11 3
 
10.0%
25 3
 
10.0%
18 2
 
6.7%
10 2
 
6.7%
19 2
 
6.7%
16 2
 
6.7%
24 1
 
3.3%
157 1
 
3.3%
62 1
 
3.3%
Other values (8) 8
26.7%
ValueCountFrequency (%)
10 2
 
6.7%
11 3
10.0%
13 5
16.7%
16 2
 
6.7%
18 2
 
6.7%
19 2
 
6.7%
24 1
 
3.3%
25 3
10.0%
26 1
 
3.3%
45 1
 
3.3%
ValueCountFrequency (%)
1374 1
3.3%
234 1
3.3%
214 1
3.3%
157 1
3.3%
90 1
3.3%
68 1
3.3%
62 1
3.3%
58 1
3.3%
45 1
3.3%
26 1
3.3%

창립년월(fndtn_ym)
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean200188.7
Minimum197309
Maximum201502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:59:45.319010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum197309
5-th percentile197499.1
Q1199857.5
median200803
Q3201204.75
95-th percentile201358.75
Maximum201502
Range4193
Interquartile range (IQR)1347.25

Descriptive statistics

Standard deviation1339.3589
Coefficient of variation (CV)0.0066904821
Kurtosis-0.023676855
Mean200188.7
Median Absolute Deviation (MAD)408
Skewness-1.1564922
Sum6005661
Variance1793882.3
MonotonicityNot monotonic
2023-12-10T23:59:45.684551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
201201 2
 
6.7%
200011 1
 
3.3%
200003 1
 
3.3%
201210 1
 
3.3%
200401 1
 
3.3%
199102 1
 
3.3%
197706 1
 
3.3%
201208 1
 
3.3%
200007 1
 
3.3%
201204 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
197309 1
3.3%
197410 1
3.3%
197608 1
3.3%
197706 1
3.3%
198101 1
3.3%
198805 1
3.3%
199102 1
3.3%
199809 1
3.3%
200003 1
3.3%
200007 1
3.3%
ValueCountFrequency (%)
201502 1
3.3%
201406 1
3.3%
201301 1
3.3%
201212 1
3.3%
201210 1
3.3%
201208 1
3.3%
201207 1
3.3%
201205 1
3.3%
201204 1
3.3%
201201 2
6.7%

x좌표(xcrd)
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean200050.71
Minimum186346.57
Maximum213109.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:59:45.964044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum186346.57
5-th percentile189931.97
Q1195116.9
median200543.64
Q3204222.82
95-th percentile211441.86
Maximum213109.53
Range26762.966
Interquartile range (IQR)9105.9125

Descriptive statistics

Standard deviation6725.1786
Coefficient of variation (CV)0.03361737
Kurtosis-0.39154145
Mean200050.71
Median Absolute Deviation (MAD)4376.527
Skewness-0.083614627
Sum6001521.2
Variance45228028
MonotonicityNot monotonic
2023-12-10T23:59:46.235681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
192891.8608 1
 
3.3%
194646.9401 1
 
3.3%
213109.5327 1
 
3.3%
205279.8438 1
 
3.3%
200548.2321 1
 
3.3%
196526.7898 1
 
3.3%
204050.8305 1
 
3.3%
198062.3882 1
 
3.3%
202845.1241 1
 
3.3%
205398.8311 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
186346.5669 1
3.3%
189405.8703 1
3.3%
190574.9898 1
3.3%
190777.8309 1
3.3%
191536.6203 1
3.3%
192891.8608 1
3.3%
193855.8181 1
3.3%
194646.9401 1
3.3%
196526.7898 1
3.3%
198062.3882 1
3.3%
ValueCountFrequency (%)
213109.5327 1
3.3%
211794.8912 1
3.3%
211010.3848 1
3.3%
206876.9189 1
3.3%
205760.914 1
3.3%
205398.8311 1
3.3%
205279.8438 1
3.3%
204280.1432 1
3.3%
204050.8305 1
3.3%
203342.0021 1
3.3%

y좌표(ycrd)
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean448750.4
Minimum441269.4
Maximum462353.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:59:46.477708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441269.4
5-th percentile441631.21
Q1444481.6
median448827.5
Q3452401.76
95-th percentile457018.08
Maximum462353.12
Range21083.724
Interquartile range (IQR)7920.1598

Descriptive statistics

Standard deviation5434.6799
Coefficient of variation (CV)0.012110696
Kurtosis-0.29458495
Mean448750.4
Median Absolute Deviation (MAD)4249.4705
Skewness0.49930318
Sum13462512
Variance29535745
MonotonicityNot monotonic
2023-12-10T23:59:46.718832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
441631.2077 2
 
6.7%
446120.9643 1
 
3.3%
453363.848 1
 
3.3%
451544.9076 1
 
3.3%
442798.9383 1
 
3.3%
451696.394 1
 
3.3%
447827.2663 1
 
3.3%
456098.339 1
 
3.3%
441269.3969 1
 
3.3%
457498.1566 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
441269.3969 1
3.3%
441631.2077 2
6.7%
441873.4163 1
3.3%
442798.9383 1
3.3%
442875.0923 1
3.3%
444047.4459 1
3.3%
444473.6962 1
3.3%
444505.3276 1
3.3%
445038.308 1
3.3%
445752.2307 1
3.3%
ValueCountFrequency (%)
462353.1209 1
3.3%
457498.1566 1
3.3%
456431.3142 1
3.3%
456098.339 1
3.3%
453363.848 1
3.3%
453161.021 1
3.3%
453004.2686 1
3.3%
452636.8871 1
3.3%
451696.394 1
3.3%
451544.9076 1
3.3%

기업구분(entrprs_nm)
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
근로자 10인 이상 50인 미만
22 
근로자 50인 이상 300인 미만
5 
근로자 300인 이상 1000인 미만
 
2
기타(정부기업,공기업)
 
1

Length

Max length20
Median length17
Mean length17.2
Min length12

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row근로자 10인 이상 50인 미만
2nd row근로자 10인 이상 50인 미만
3rd row근로자 300인 이상 1000인 미만
4th row근로자 10인 이상 50인 미만
5th row근로자 10인 이상 50인 미만

Common Values

ValueCountFrequency (%)
근로자 10인 이상 50인 미만 22
73.3%
근로자 50인 이상 300인 미만 5
 
16.7%
근로자 300인 이상 1000인 미만 2
 
6.7%
기타(정부기업,공기업) 1
 
3.3%

Length

2023-12-10T23:59:47.049998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:59:47.305158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
근로자 29
19.9%
이상 29
19.9%
미만 29
19.9%
50인 27
18.5%
10인 22
15.1%
300인 7
 
4.8%
1000인 2
 
1.4%
기타(정부기업,공기업 1
 
0.7%

적재일시(ldadng_dt)
Date

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2017-12-27 17:25:00
Maximum2017-12-27 17:25:02
2023-12-10T23:59:47.498176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:47.724436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

Sample

년도(year)데이터_일련번호(data_sno)행정동_코드(adstrd_code_se)기업명(entrprs_nm)업종코드(induty_code)업종명(induty_nm)도로명(rn)건물번호(buld_no)부번(buld_slno_no)건물명(buld_nm)건물동(buld_dong)건물층(buld_floor)건물호(buld_ho)지번_본번(mnnm_no)지번_부번(slno_no)전화번호_지역(telno_area)전화번호1(telno_1)전화번호2(telno_2)사용근로자수(cmcl_labrr_co)창립년월(fndtn_ym)x좌표(xcrd)y좌표(ycrd)기업구분(entrprs_nm)적재일시(ldadng_dt)
020165467191123053(주)제일FNE75992유통테헤란로30<NA>해*<NA>82*264417<NA><NA><NA>18200011192891.8608446120.9643근로자 10인 이상 50인 미만2017-12-27 17:25:02
120162402811119054DHL13222가방끈 제조남부순환로9<NA>연*뉴*<NA>5*7*85*267813<NA><NA><NA>19199809211010.3848453363.848근로자 10인 이상 50인 미만2017-12-27 17:25:00
220161089591117071㈜케이티서비스북부중랑지점61299드론응용소프트웨어개발디지털로1114로*어*타*<NA>8<NA>9028<NA><NA><NA>45201301193855.8181450196.7349근로자 300인 이상 1000인 미만2017-12-27 17:25:01
320161486931104054덕진티엠에스주식회사96991논술영신로34길216<NA>대*월*마*용*<NA>12*96052<NA><NA><NA>1374201502189405.8703453004.2686근로자 10인 이상 50인 미만2017-12-27 17:25:00
420166500401111065(주)월드안전42412방송프로그램제작도산대로68길33<NA><NA><NA><NA><NA>6918<NA><NA><NA>13198805190777.8309450451.7232근로자 10인 이상 50인 미만2017-12-27 17:25:02
520165972551103071(주)피에이씨 건축사사무소46800각종제품디지털로31길29<NA><NA><NA>1*,*5<NA>34190<NA><NA><NA>62197309201845.0039446141.7558근로자 10인 이상 50인 미만2017-12-27 17:25:02
6201650021613531123071세진세무회계사무소56114산업용컴퓨터제조서초중앙로31길542<NA>원*전*상*<NA>1*6*17074<NA><NA><NA>157197608201342.879450555.8575근로자 300인 이상 1000인 미만2017-12-27 17:25:02
720161845991119075한국피엠오주식회사71202영어가마산로10<NA>신*양<NA>1*<NA>50027<NA><NA><NA>13201207186346.5669449827.7426근로자 10인 이상 50인 미만2017-12-27 17:25:01
820161449511121072(주)웨어밸리14112커피.음료여의공원로22<NA>원*Y14*22841<NA><NA><NA>24200805201716.2926462353.1209근로자 10인 이상 50인 미만2017-12-27 17:25:02
920162105741122054어바웃 모델46464실내인테리어공사디지털로33길9<NA>선*빌*<NA>1<NA>45633<NA><NA><NA>13200801211794.8912456431.3142기타(정부기업,공기업)2017-12-27 17:25:00
년도(year)데이터_일련번호(data_sno)행정동_코드(adstrd_code_se)기업명(entrprs_nm)업종코드(induty_code)업종명(induty_nm)도로명(rn)건물번호(buld_no)부번(buld_slno_no)건물명(buld_nm)건물동(buld_dong)건물층(buld_floor)건물호(buld_ho)지번_본번(mnnm_no)지번_부번(slno_no)전화번호_지역(telno_area)전화번호1(telno_1)전화번호2(telno_2)사용근로자수(cmcl_labrr_co)창립년월(fndtn_ym)x좌표(xcrd)y좌표(ycrd)기업구분(entrprs_nm)적재일시(ldadng_dt)
202016902601106081로담건축(주)58221건물및토목엔지니어링 서비스국제금융로728<NA>금*동*신*플*스*파*상*<NA>6*8*1132020<NA><NA><NA>90201212203342.0021451282.263근로자 10인 이상 50인 미만2017-12-27 17:25:00
2120161625381124068(주)고어코리아58221디자인, 기획테헤란로80<NA>에*에*프*자<NA>7<NA>110<NA><NA><NA><NA>234200602205760.914457498.1566근로자 10인 이상 50인 미만2017-12-27 17:25:02
2220161749551102052유앤미의원46799건설엔지니어링및부대인력공급강남대로66길97<NA><NA><NA>2<NA><NA>5<NA><NA><NA>18198101205398.8311441269.3969근로자 10인 이상 50인 미만2017-12-27 17:25:02
2320163128991125074법무법인한누리71393서비스이태원로524<NA>대*아*알<NA><NA>B*1133<NA><NA><NA><NA>10201204202845.1241456098.339근로자 10인 이상 50인 미만2017-12-27 17:25:00
24201670010074341122055(주)에스제이 컴퍼니글로벌85502건축공사통일로15<NA>산*<NA><NA><NA>178<NA><NA><NA><NA>58200007198062.3882441631.2077근로자 10인 이상 50인 미만2017-12-27 17:25:02
2520164421441105056(주)천일오토모빌-대치서비스86202진료서비스방배천로24길698<NA>한*I*타*2*<NA>1*<NA>10548<NA><NA><NA>11201208204050.8305441631.2077근로자 10인 이상 50인 미만2017-12-27 17:25:02
2620163711901104068(주)이니셜닷컴46592배관자재도봉로13<NA>벽*경*디*털*리*차<NA>13*1490<NA><NA><NA><NA>25197706196526.7898447827.2663근로자 10인 이상 50인 미만2017-12-27 17:25:01
2720166858661122065동양전기안전관리(주)29294척추 관절 치료면목로202<NA><NA><NA>22*5<NA>6<NA><NA><NA>13199102200548.2321451696.394근로자 10인 이상 50인 미만2017-12-27 17:25:02
2820165670271117054주식회사 미래제어기술85501아파트건설종로3길51<NA>상*<NA>1<NA>510<NA><NA><NA><NA>68200401205279.8438442798.9383근로자 50인 이상 300인 미만2017-12-27 17:25:00
2920165034191106083(주)스파이더네트웍스46599일반건축공사왕산로11<NA>우*빌*<NA>1*<NA>73218<NA><NA><NA>25201210213109.5327451544.9076근로자 50인 이상 300인 미만2017-12-27 17:25:02