gimi9 Pandas Profiling

Dataset statistics

Number of variables	14
Number of observations	200
Missing cells	134
Missing cells (%)	4.8%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	22.8 KiB
Average record size in memory	116.7 B

Variable types

Text	5
Numeric	5
Categorical	4

Dataset

Description	Sample
Author	오픈메이트
URL	https://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=OPMPUBLICINFO0000005

Alerts

`PUBLIC2_NM` is highly overall correlated with `X_AXIS` and 5 other fields	High correlation
`PUBLIC1_CD` is highly overall correlated with `X_AXIS` and 5 other fields	High correlation
`PUBLIC1_NM` is highly overall correlated with `X_AXIS` and 5 other fields	High correlation
`PUBLIC2_CD` is highly overall correlated with `X_AXIS` and 5 other fields	High correlation
`X_AXIS` is highly overall correlated with `PUBLIC1_CD` and 3 other fields	High correlation
`BLK_CD` is highly overall correlated with `PUBLIC1_CD` and 3 other fields	High correlation
`HOUS_ID` is highly overall correlated with `BLD_CD` and 4 other fields	High correlation
`BLD_CD` is highly overall correlated with `HOUS_ID`	High correlation
`ROAD_ADDR` has 67 (33.5%) missing values	Missing
`BLD_CD` has 66 (33.0%) missing values	Missing
`PUBLIC_CD` has unique values	Unique

Reproduction

Analysis started	2023-12-10 06:22:06.290141
Analysis finished	2023-12-10 06:22:21.766928
Duration	15.48 seconds
Software version	ydata-profiling vv4.5.1
Download configuration	config.json

PUBLIC_CD
Text

UNIQUE

Distinct	200
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

Length

Max length	8
Median length	8
Mean length	8
Min length	8

Characters and Unicode

Total characters	1600
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	200 ?
Unique (%)	100.0%

Sample

1st row	P0202883
2nd row	P0202884
3rd row	P0202885
4th row	P0202886
5th row	P0202887

Value	Count	Frequency (%)
p0202883	1	0.5%
p0108530	1	0.5%
p0202946	1	0.5%
p0108521	1	0.5%
p0108522	1	0.5%
p0108523	1	0.5%
p0108524	1	0.5%
p0108525	1	0.5%
p0108526	1	0.5%
p0108527	1	0.5%
Other values (190)	190	95.0%

Most occurring characters

Value	Count	Frequency (%)
0	439	27.4%
P	200	12.5%
2	186	11.6%
8	176	11.0%
1	162	10.1%
4	114	7.1%
5	103	6.4%
9	99	6.2%
3	43	2.7%
6	40	2.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1400	87.5%
Uppercase Letter	200	12.5%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	439	31.4%
2	186	13.3%
8	176	12.6%
1	162	11.6%
4	114	8.1%
5	103	7.4%
9	99	7.1%
3	43	3.1%
6	40	2.9%
7	38	2.7%

Uppercase Letter

Value	Count	Frequency (%)
P	200	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1400	87.5%
Latin	200	12.5%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	439	31.4%
2	186	13.3%
8	176	12.6%
1	162	11.6%
4	114	8.1%
5	103	7.4%
9	99	7.1%
3	43	3.1%
6	40	2.9%
7	38	2.7%

Latin

Value	Count	Frequency (%)
P	200	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1600	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	439	27.4%
P	200	12.5%
2	186	11.6%
8	176	11.0%
1	162	10.1%
4	114	7.1%
5	103	6.4%
9	99	6.2%
3	43	2.7%
6	40	2.5%

PUBLIC_NM
Text

Distinct	185
Distinct (%)	92.5%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

Length

Max length	11
Median length	9
Mean length	6.325
Min length	5

Characters and Unicode

Total characters	1265
Distinct characters	150
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	172 ?
Unique (%)	86.0%

Sample

1st row	남산동행정복지센터
2nd row	부곡1동주민센터
3rd row	부곡2동주민센터
4th row	부곡3동주민센터
5th row	부곡4동주민센터

Value	Count	Frequency (%)
흑산도관측소	3	1.5%
창원관측소	3	1.5%
백령도관측소	2	1.0%
천안관측소	2	1.0%
수원관측소	2	1.0%
철원관측소	2	1.0%
군산관측소	2	1.0%
영월관측소	2	1.0%
대관령관측소	2	1.0%
전주관측소	2	1.0%
Other values (175)	178	89.0%

Most occurring characters

Value	Count	Frequency (%)
소	126	10.0%
관	125	9.9%
측	123	9.7%
주	87	6.9%
동	80	6.3%
터	78	6.2%
센	78	6.2%
민	74	5.8%
산	26	2.1%
1	17	1.3%
Other values (140)	451	35.7%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	1212	95.8%
Decimal Number	53	4.2%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
소	126	10.4%
관	125	10.3%
측	123	10.1%
주	87	7.2%
동	80	6.6%
터	78	6.4%
센	78	6.4%
민	74	6.1%
산	26	2.1%
천	15	1.2%
Other values (134)	400	33.0%

Decimal Number

Value	Count	Frequency (%)
1	17	32.1%
2	17	32.1%
3	10	18.9%
4	6	11.3%
5	2	3.8%
6	1	1.9%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	1212	95.8%
Common	53	4.2%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
소	126	10.4%
관	125	10.3%
측	123	10.1%
주	87	7.2%
동	80	6.6%
터	78	6.4%
센	78	6.4%
민	74	6.1%
산	26	2.1%
천	15	1.2%
Other values (134)	400	33.0%

Common

Value	Count	Frequency (%)
1	17	32.1%
2	17	32.1%
3	10	18.9%
4	6	11.3%
5	2	3.8%
6	1	1.9%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	1212	95.8%
ASCII	53	4.2%

Most frequent character per block

Hangul

Value	Count	Frequency (%)
소	126	10.4%
관	125	10.3%
측	123	10.1%
주	87	7.2%
동	80	6.6%
터	78	6.4%
센	78	6.4%
민	74	6.1%
산	26	2.1%
천	15	1.2%
Other values (134)	400	33.0%

ASCII

Value	Count	Frequency (%)
1	17	32.1%
2	17	32.1%
3	10	18.9%
4	6	11.3%
5	2	3.8%
6	1	1.9%

ROAD_ADDR
Text

MISSING

Distinct	127
Distinct (%)	95.5%
Missing	67
Missing (%)	33.5%
Memory size	1.7 KiB

Length

Max length	27
Median length	24
Mean length	19.428571
Min length	14

Characters and Unicode

Total characters	2584
Distinct characters	174
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	122 ?
Unique (%)	91.7%

Sample

1st row	부산광역시 금정구 중앙대로2097번길 4
2nd row	부산광역시 금정구 동부곡로6번길 29
3rd row	부산광역시 금정구 부곡로156번길 7
4th row	부산광역시 금정구 기찰로 107
5th row	부산광역시 금정구 부곡로18번안길 37

Value	Count	Frequency (%)
부산광역시	34	5.8%
전라북도	25	4.3%
서울특별시	23	3.9%
남구	17	2.9%
송파구	16	2.7%
전주시	15	2.6%
완산구	14	2.4%
금정구	13	2.2%
강원도	12	2.1%
정읍시	8	1.4%
Other values (309)	406	69.6%

Most occurring characters

Value	Count	Frequency (%)
	450	17.4%
시	113	4.4%
로	107	4.1%
1	102	3.9%
구	84	3.3%
2	80	3.1%
도	78	3.0%
길	62	2.4%
산	60	2.3%
3	60	2.3%
Other values (164)	1388	53.7%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	1649	63.8%
Decimal Number	453	17.5%
Space Separator	450	17.4%
Dash Punctuation	32	1.2%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
시	113	6.9%
로	107	6.5%
구	84	5.1%
도	78	4.7%
길	62	3.8%
산	60	3.6%
전	48	2.9%
남	47	2.9%
북	43	2.6%
부	40	2.4%
Other values (152)	967	58.6%

Decimal Number

Value	Count	Frequency (%)
1	102	22.5%
2	80	17.7%
3	60	13.2%
7	44	9.7%
6	37	8.2%
5	31	6.8%
4	31	6.8%
9	30	6.6%
8	22	4.9%
0	16	3.5%

Space Separator

Value	Count	Frequency (%)
	450	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	32	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	1649	63.8%
Common	935	36.2%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
시	113	6.9%
로	107	6.5%
구	84	5.1%
도	78	4.7%
길	62	3.8%
산	60	3.6%
전	48	2.9%
남	47	2.9%
북	43	2.6%
부	40	2.4%
Other values (152)	967	58.6%

Common

Value	Count	Frequency (%)
	450	48.1%
1	102	10.9%
2	80	8.6%
3	60	6.4%
7	44	4.7%
6	37	4.0%
-	32	3.4%
5	31	3.3%
4	31	3.3%
9	30	3.2%
Other values (2)	38	4.1%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	1649	63.8%
ASCII	935	36.2%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	450	48.1%
1	102	10.9%
2	80	8.6%
3	60	6.4%
7	44	4.7%
6	37	4.0%
-	32	3.4%
5	31	3.3%
4	31	3.3%
9	30	3.2%
Other values (2)	38	4.1%

Hangul

Value	Count	Frequency (%)
시	113	6.9%
로	107	6.5%
구	84	5.1%
도	78	4.7%
길	62	3.8%
산	60	3.6%
전	48	2.9%
남	47	2.9%
북	43	2.6%
부	40	2.4%
Other values (152)	967	58.6%

X_AXIS
Real number (ℝ)

HIGH CORRELATION

Distinct	189
Distinct (%)	94.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	374885.82

Minimum	104040
Maximum	528119
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 KiB

Quantile statistics

Minimum	104040
5-th percentile	247831.1
Q1	312049.25
median	347789
Q3	469682.25
95-th percentile	501288.8
Maximum	528119
Range	424079
Interquartile range (IQR)	157633

Descriptive statistics

Standard deviation	95819.549
Coefficient of variation (CV)	0.25559662
Kurtosis	-0.64670992
Mean	374885.82
Median Absolute Deviation (MAD)	68546.5
Skewness	-0.16727707
Sum	74977163
Variance	9.1813859 × 10⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
166625	3	1.5%
452343	3	1.5%
104040	2	1.0%
440765	2	1.0%
288525	2	1.0%
310221	2	1.0%
263216	2	1.0%
491323	2	1.0%
463603	2	1.0%
228598	1	0.5%
Other values (179)	179	89.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
104040	2	1.0%
134861	1	0.5%
166625	3	1.5%
181927	1	0.5%
228598	1	0.5%
240224	1	0.5%
244166	1	0.5%
248024	1	0.5%
250676	1	0.5%
252071	1	0.5%

Value	Count	Frequency (%)
528119	1	0.5%
522818	1	0.5%
521114	1	0.5%
520519	1	0.5%
512295	1	0.5%
508702	1	0.5%
501691	1	0.5%
501627	1	0.5%
501455	1	0.5%
501418	1	0.5%

Y_AXIS
Real number (ℝ)

Distinct	189
Distinct (%)	94.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	391678.99

Minimum	73178
Maximum	627692
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 KiB

Quantile statistics

Minimum	73178
5-th percentile	232489.15
Q1	285886
median	357851
Q3	520955.5
95-th percentile	587839.35
Maximum	627692
Range	554514
Interquartile range (IQR)	235069.5

Descriptive statistics

Standard deviation	127390.08
Coefficient of variation (CV)	0.32524103
Kurtosis	-0.90151488
Mean	391678.99
Median Absolute Deviation (MAD)	80410.5
Skewness	0.073597265
Sum	78335799
Variance	1.6228233 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
235083	3	1.5%
285886	3	1.5%
601271	2	1.0%
508966	2	1.0%
379045	2	1.0%
519443	2	1.0%
568271	2	1.0%
280449	2	1.0%
564130	2	1.0%
277949	1	0.5%
Other values (179)	179	89.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
73178	1	0.5%
82562	1	0.5%
88474	1	0.5%
102955	1	0.5%
154891	1	0.5%
165417	1	0.5%
203808	1	0.5%
209747	1	0.5%
224695	1	0.5%
226032	1	0.5%

Value	Count	Frequency (%)
627692	1	0.5%
622315	1	0.5%
616321	1	0.5%
612857	1	0.5%
606338	1	0.5%
601271	2	1.0%
595263	1	0.5%
589239	1	0.5%
588948	1	0.5%
587781	1	0.5%

BLK_CD
Real number (ℝ)

HIGH CORRELATION

Distinct	188
Distinct (%)	94.5%
Missing	1
Missing (%)	0.5%
Infinite	0
Infinite (%)	0.0%
Mean	250208.32

Minimum	380
Maximum	519172
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 KiB

Quantile statistics

Minimum	380
5-th percentile	26944
Q1	82006.5
median	238274
Q3	409951.5
95-th percentile	506250.9
Maximum	519172
Range	518792
Interquartile range (IQR)	327945

Descriptive statistics

Standard deviation	167084.71
Coefficient of variation (CV)	0.6677824
Kurtosis	-1.4031413
Mean	250208.32
Median Absolute Deviation (MAD)	164831
Skewness	0.14874522
Sum	49791455
Variance	2.79173 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
72769	3	1.5%
70404	3	1.5%
434582	2	1.0%
25257	2	1.0%
125874	2	1.0%
488667	2	1.0%
508144	2	1.0%
408205	2	1.0%
400907	2	1.0%
494545	1	0.5%
Other values (178)	178	89.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
380	1	0.5%
4518	1	0.5%
7626	1	0.5%
8136	1	0.5%
9007	1	0.5%
9439	1	0.5%
16508	1	0.5%
25257	2	1.0%
26521	1	0.5%
26991	1	0.5%

Value	Count	Frequency (%)
519172	1	0.5%
516722	1	0.5%
516259	1	0.5%
515587	1	0.5%
514310	1	0.5%
511915	1	0.5%
509434	1	0.5%
508144	2	1.0%
507960	1	0.5%
506061	1	0.5%

PUBLIC1_CD
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

P01000	123
P02000	77

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	P02000
2nd row	P02000
3rd row	P02000
4th row	P02000
5th row	P02000

Common Values

Value	Count	Frequency (%)
P01000	123	61.5%
P02000	77	38.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
p01000	123	61.5%
p02000	77	38.5%

PUBLIC1_NM
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

공공기관	123
행정기관	77

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	행정기관
2nd row	행정기관
3rd row	행정기관
4th row	행정기관
5th row	행정기관

Common Values

Value	Count	Frequency (%)
공공기관	123	61.5%
행정기관	77	38.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
공공기관	123	61.5%
행정기관	77	38.5%

PUBLIC2_CD
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

P01004	123
P02003	77

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	P02003
2nd row	P02003
3rd row	P02003
4th row	P02003
5th row	P02003

Common Values

Value	Count	Frequency (%)
P01004	123	61.5%
P02003	77	38.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
p01004	123	61.5%
p02003	77	38.5%

PUBLIC2_NM
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

기상대/측우소	123
동/읍/면/리사무소	77

Length

Max length	10
Median length	7
Mean length	8.155
Min length	7

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	동/읍/면/리사무소
2nd row	동/읍/면/리사무소
3rd row	동/읍/면/리사무소
4th row	동/읍/면/리사무소
5th row	동/읍/면/리사무소

Common Values

Value	Count	Frequency (%)
기상대/측우소	123	61.5%
동/읍/면/리사무소	77	38.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
기상대/측우소	123	61.5%
동/읍/면/리사무소	77	38.5%

ADDRESS
Text

Distinct	189
Distinct (%)	94.5%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

Length

Max length	46
Median length	28
Mean length	23.085
Min length	16

Characters and Unicode

Total characters	4617
Distinct characters	220
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	180 ?
Unique (%)	90.0%

Sample

1st row	부산광역시 금정구 중앙대로2097번길 4 (남산동)
2nd row	부산광역시 금정구 동부곡로6번길 29 (부곡동)
3rd row	부산광역시 금정구 부곡로156번길 7 (부곡동)
4th row	부산광역시 금정구 기찰로 107 (부곡동)
5th row	부산광역시 금정구 부곡로18번안길 37 (부곡동)

Value	Count	Frequency (%)
부산광역시	34	3.5%
전라북도	33	3.4%
서울특별시	23	2.4%
강원도	21	2.2%
전라남도	19	2.0%
경상북도	17	1.8%
남구	17	1.8%
송파구	16	1.7%
전주시	15	1.6%
경상남도	14	1.5%
Other values (566)	752	78.3%

Most occurring characters

Value	Count	Frequency (%)
	761	16.5%
1	161	3.5%
시	151	3.3%
번	139	3.0%
도	139	3.0%
동	125	2.7%
지	125	2.7%
2	118	2.6%
-	110	2.4%
산	102	2.2%
Other values (210)	2686	58.2%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	2872	62.2%
Decimal Number	764	16.5%
Space Separator	761	16.5%
Dash Punctuation	110	2.4%
Open Punctuation	55	1.2%
Close Punctuation	55	1.2%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
시	151	5.3%
번	139	4.8%
도	139	4.8%
동	125	4.4%
지	125	4.4%
산	102	3.6%
구	97	3.4%
남	77	2.7%
전	76	2.6%
리	75	2.6%
Other values (196)	1766	61.5%

Decimal Number

Value	Count	Frequency (%)
1	161	21.1%
2	118	15.4%
3	102	13.4%
6	68	8.9%
7	62	8.1%
4	60	7.9%
5	55	7.2%
9	49	6.4%
0	49	6.4%
8	40	5.2%

Space Separator

Value	Count	Frequency (%)
	761	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	110	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	55	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	55	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	2872	62.2%
Common	1745	37.8%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
시	151	5.3%
번	139	4.8%
도	139	4.8%
동	125	4.4%
지	125	4.4%
산	102	3.6%
구	97	3.4%
남	77	2.7%
전	76	2.6%
리	75	2.6%
Other values (196)	1766	61.5%

Common

Value	Count	Frequency (%)
	761	43.6%
1	161	9.2%
2	118	6.8%
-	110	6.3%
3	102	5.8%
6	68	3.9%
7	62	3.6%
4	60	3.4%
(	55	3.2%
5	55	3.2%
Other values (4)	193	11.1%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	2872	62.2%
ASCII	1745	37.8%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	761	43.6%
1	161	9.2%
2	118	6.8%
-	110	6.3%
3	102	5.8%
6	68	3.9%
7	62	3.6%
4	60	3.4%
(	55	3.2%
5	55	3.2%
Other values (4)	193	11.1%

Hangul

Value	Count	Frequency (%)
시	151	5.3%
번	139	4.8%
도	139	4.8%
동	125	4.4%
지	125	4.4%
산	102	3.6%
구	97	3.4%
남	77	2.7%
전	76	2.6%
리	75	2.6%
Other values (196)	1766	61.5%

HOUS_ID
Real number (ℝ)

HIGH CORRELATION

Distinct	189
Distinct (%)	94.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.7280074 × 10¹⁸

Minimum	1.1290133 × 10¹⁸
Maximum	5.0130259 × 10¹⁸
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 KiB

Quantile statistics

Minimum	1.1290133 × 10¹⁸
5-th percentile	1.1710106 × 10¹⁸
Q1	2.6410109 × 10¹⁸
median	4.3131613 × 10¹⁸
Q3	4.6170214 × 10¹⁸
95-th percentile	4.8311118 × 10¹⁸
Maximum	5.0130259 × 10¹⁸
Range	3.8840126 × 10¹⁸
Interquartile range (IQR)	1.9760105 × 10¹⁸

Descriptive statistics

Standard deviation	1.216775 × 10¹⁸
Coefficient of variation (CV)	0.32638749
Kurtosis	-0.34510774
Mean	3.7280074 × 10¹⁸
Median Absolute Deviation (MAD)	4.0386567 × 10¹⁷
Skewness	-1.0042597
Sum	7.7317184 × 10¹⁸
Variance	1.4805413 × 10³⁶
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4691036022002720000	3	1.5%
4812510100100010117	3	1.5%
2872033024102420013	2	1.0%
4275025022003220000	2	1.0%
4513013800100100000	2	1.0%
4111313100002080016	2	1.0%
2871032027008100003	2	1.0%
2614010600100320010	2	1.0%
4276038024002790010	2	1.0%
4691032027001840000	1	0.5%
Other values (179)	179	89.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1129013300002930006	1	0.5%
1129013300006730003	1	0.5%
1129013300009660125	1	0.5%
1129013300010200000	1	0.5%
1129013500000160008	1	0.5%
1129013800000690054	1	0.5%
1129013800001170005	1	0.5%
1171010400001130001	1	0.5%
1171010400001730000	1	0.5%
1171010500002650000	1	0.5%

Value	Count	Frequency (%)
5013025927006850004	1	0.5%
5013025323016220001	1	0.5%
5013010100005400003	1	0.5%
5011010700011230013	1	0.5%
4889033034012300114	1	0.5%
4889025021001290004	1	0.5%
4888034022014470007	1	0.5%
4884031021007970002	1	0.5%
4872025024000400004	1	0.5%
4833031027012160037	1	0.5%

BLD_CD
Real number (ℝ)

HIGH CORRELATION MISSING

Distinct	128
Distinct (%)	95.5%
Missing	66
Missing (%)	33.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.4397707 × 10²⁴

Minimum	1.1290133 × 10²⁴
Maximum	5.0130259 × 10²⁴
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 KiB

Quantile statistics

Minimum	1.1290133 × 10²⁴
5-th percentile	1.1563116 × 10²⁴
Q1	2.6290107 × 10²⁴
median	4.2120395 × 10²⁴
Q3	4.5126069 × 10²⁴
95-th percentile	4.850881 × 10²⁴
Maximum	5.0130259 × 10²⁴
Range	3.8840126 × 10²⁴
Interquartile range (IQR)	1.8835962 × 10²⁴

Descriptive statistics

Standard deviation	1.3287304 × 10²⁴
Coefficient of variation (CV)	0.38628458
Kurtosis	-1.1201085
Mean	3.4397707 × 10²⁴
Median Absolute Deviation (MAD)	6.1798109 × 10²³
Skewness	-0.59434515
Sum	4.6092927 × 10²⁶
Variance	1.7655244 × 10⁴⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4.8125101002000097e+24	3	1.5%
4.2760380241027906e+24	2	1.0%
4.11131310010208e+24	2	1.0%
4.27502502210322e+24	2	1.0%
2.61401060020032e+24	2	1.0%
4.8170126001069504e+24	1	0.5%
4.18302502110192e+24	1	0.5%
4.51111280010662e+24	1	0.5%
4.51111190010032e+24	1	0.5%
4.51111240010071e+24	1	0.5%
Other values (118)	118	59.0%
(Missing)	66	33.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1.12901330010293e+24	1	0.5%
1.12901330010673e+24	1	0.5%
1.12901330010966e+24	1	0.5%
1.1290133001102e+24	1	0.5%
1.12901350010016e+24	1	0.5%
1.12901380010069e+24	1	0.5%
1.12901380010117e+24	1	0.5%
1.17101040010113e+24	1	0.5%
1.17101040010173e+24	1	0.5%
1.17101050010265e+24	1	0.5%

Value	Count	Frequency (%)
5.013025927106849e+24	1	0.5%
5.01302532320076e+24	1	0.5%
5.0130101001054e+24	1	0.5%
5.01101010011182e+24	1	0.5%
4.889025021101289e+24	1	0.5%
4.88803402211447e+24	1	0.5%
4.88403102110797e+24	1	0.5%
4.83303102711216e+24	1	0.5%
4.82701020011073e+24	1	0.5%
4.8170126001069504e+24	1	0.5%

HOUS_ADDR
Text

Distinct	189
Distinct (%)	94.5%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

Length

Max length	29
Median length	27
Mean length	22.305
Min length	17

Characters and Unicode

Total characters	4461
Distinct characters	188
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	180 ?
Unique (%)	90.0%

Sample

1st row	부산광역시 금정구 남산동 21-5번지
2nd row	부산광역시 금정구 부곡동 323-1번지
3rd row	부산광역시 금정구 부곡동 265-10번지
4th row	부산광역시 금정구 부곡동 59-11번지
5th row	부산광역시 금정구 부곡동 395-14번지

Value	Count	Frequency (%)
부산광역시	34	3.8%
전라북도	33	3.7%
서울특별시	23	2.6%
강원도	21	2.3%
전라남도	19	2.1%
경상북도	17	1.9%
남구	17	1.9%
송파구	16	1.8%
전주시	15	1.7%
경상남도	14	1.6%
Other values (517)	692	76.8%

Most occurring characters

Value	Count	Frequency (%)
	701	15.7%
지	203	4.6%
번	200	4.5%
1	186	4.2%
-	158	3.5%
시	153	3.4%
도	139	3.1%
동	139	3.1%
2	126	2.8%
산	104	2.3%
Other values (178)	2352	52.7%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	2765	62.0%
Decimal Number	837	18.8%
Space Separator	701	15.7%
Dash Punctuation	158	3.5%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
지	203	7.3%
번	200	7.2%
시	153	5.5%
도	139	5.0%
동	139	5.0%
산	104	3.8%
구	95	3.4%
리	76	2.7%
남	75	2.7%
전	73	2.6%
Other values (166)	1508	54.5%

Decimal Number

Value	Count	Frequency (%)
1	186	22.2%
2	126	15.1%
3	99	11.8%
4	76	9.1%
6	68	8.1%
5	65	7.8%
7	64	7.6%
0	58	6.9%
9	48	5.7%
8	47	5.6%

Space Separator

Value	Count	Frequency (%)
	701	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	158	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	2765	62.0%
Common	1696	38.0%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
지	203	7.3%
번	200	7.2%
시	153	5.5%
도	139	5.0%
동	139	5.0%
산	104	3.8%
구	95	3.4%
리	76	2.7%
남	75	2.7%
전	73	2.6%
Other values (166)	1508	54.5%

Common

Value	Count	Frequency (%)
	701	41.3%
1	186	11.0%
-	158	9.3%
2	126	7.4%
3	99	5.8%
4	76	4.5%
6	68	4.0%
5	65	3.8%
7	64	3.8%
0	58	3.4%
Other values (2)	95	5.6%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	2765	62.0%
ASCII	1696	38.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	701	41.3%
1	186	11.0%
-	158	9.3%
2	126	7.4%
3	99	5.8%
4	76	4.5%
6	68	4.0%
5	65	3.8%
7	64	3.8%
0	58	3.4%
Other values (2)	95	5.6%

Hangul

Value	Count	Frequency (%)
지	203	7.3%
번	200	7.2%
시	153	5.5%
도	139	5.0%
동	139	5.0%
산	104	3.8%
구	95	3.4%
리	76	2.7%
남	75	2.7%
전	73	2.6%
Other values (166)	1508	54.5%

Heatmap
Table

	X_AXIS	Y_AXIS	BLK_CD	PUBLIC1_CD	PUBLIC1_NM	PUBLIC2_CD	PUBLIC2_NM	HOUS_ID	BLD_CD
X_AXIS	1.000	0.788	0.688	0.739	0.739	0.739	0.739	0.670	0.682
Y_AXIS	0.788	1.000	0.832	0.637	0.637	0.637	0.637	0.743	0.806
BLK_CD	0.688	0.832	1.000	0.775	0.775	0.775	0.775	0.719	0.739
PUBLIC1_CD	0.739	0.637	0.775	1.000	1.000	1.000	1.000	0.715	0.915
PUBLIC1_NM	0.739	0.637	0.775	1.000	1.000	1.000	1.000	0.715	0.915
PUBLIC2_CD	0.739	0.637	0.775	1.000	1.000	1.000	1.000	0.715	0.915
PUBLIC2_NM	0.739	0.637	0.775	1.000	1.000	1.000	1.000	0.715	0.915
HOUS_ID	0.670	0.743	0.719	0.715	0.715	0.715	0.715	1.000	1.000
BLD_CD	0.682	0.806	0.739	0.915	0.915	0.915	0.915	1.000	1.000

Heatmap
Table

	PUBLIC2_NM	PUBLIC1_CD	PUBLIC1_NM	PUBLIC2_CD
PUBLIC2_NM	1.000	0.989	0.989	0.989
PUBLIC1_CD	0.989	1.000	0.989	0.989
PUBLIC1_NM	0.989	0.989	1.000	0.989
PUBLIC2_CD	0.989	0.989	0.989	1.000

Heatmap
Table

	X_AXIS	Y_AXIS	BLK_CD	HOUS_ID	BLD_CD	PUBLIC1_CD	PUBLIC1_NM	PUBLIC2_CD	PUBLIC2_NM
X_AXIS	1.000	-0.127	0.111	-0.180	-0.246	0.572	0.572	0.572	0.572
Y_AXIS	-0.127	1.000	0.139	-0.350	-0.314	0.486	0.486	0.486	0.486
BLK_CD	0.111	0.139	1.000	-0.061	-0.074	0.597	0.597	0.597	0.597
HOUS_ID	-0.180	-0.350	-0.061	1.000	1.000	0.766	0.766	0.766	0.766
BLD_CD	-0.246	-0.314	-0.074	1.000	1.000	0.213	0.213	0.213	0.213
PUBLIC1_CD	0.572	0.486	0.597	0.766	0.213	1.000	0.989	0.989	0.989
PUBLIC1_NM	0.572	0.486	0.597	0.766	0.213	0.989	1.000	0.989	0.989
PUBLIC2_CD	0.572	0.486	0.597	0.766	0.213	0.989	0.989	1.000	0.989
PUBLIC2_NM	0.572	0.486	0.597	0.766	0.213	0.989	0.989	0.989	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

First rows
Last rows

	PUBLIC_CD	PUBLIC_NM	ROAD_ADDR	X_AXIS	Y_AXIS	BLK_CD	PUBLIC1_CD	PUBLIC1_NM	PUBLIC2_CD	PUBLIC2_NM	ADDRESS	HOUS_ID	BLD_CD	HOUS_ADDR
0	P0202883	남산동행정복지센터	부산광역시 금정구 중앙대로2097번길 4	499570	297505	80730	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 금정구 중앙대로2097번길 4 (남산동)	2641010400000210005	2641010400100210005026583	부산광역시 금정구 남산동 21-5번지
1	P0202884	부곡1동주민센터	부산광역시 금정구 동부곡로6번길 29	499616	292262	82244	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 금정구 동부곡로6번길 29 (부곡동)	2641010900003230001	2641010900103230001023841	부산광역시 금정구 부곡동 323-1번지
2	P0202885	부곡2동주민센터	부산광역시 금정구 부곡로156번길 7	499661	292865	82533	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 금정구 부곡로156번길 7 (부곡동)	2641010900002650010	2641010900102650010013749	부산광역시 금정구 부곡동 265-10번지
3	P0202886	부곡3동주민센터	부산광역시 금정구 기찰로 107	499749	294051	82632	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 금정구 기찰로 107 (부곡동)	2641010900000590011	2641010900100590011000619	부산광역시 금정구 부곡동 59-11번지
4	P0202887	부곡4동주민센터	부산광역시 금정구 부곡로18번안길 37	499297	291757	82841	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 금정구 부곡로18번안길 37 (부곡동)	2641010900003950014	2641010900103950014018966	부산광역시 금정구 부곡동 395-14번지
5	P0202888	서1동주민센터	부산광역시 금정구 서부로69번길 17	500260	291595	81904	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 금정구 서부로69번길 17 (서동)	2641011000001610014	2641011000101610014016619	부산광역시 금정구 서동 161-14번지
6	P0202889	서2동행정복지센터	부산광역시 금정구 서동중심로 33	500756	290995	76091	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 금정구 서동중심로 33 (서동)	2641011000002970446	2641011000102970446012899	부산광역시 금정구 서동 297-446번지
7	P0202890	서3동주민센터	부산광역시 금정구 서곡로33번길 9	500699	291475	82109	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 금정구 서곡로33번길 9 (서동)	2641011000003970008	2641011000103970008030159	부산광역시 금정구 서동 397-8번지
8	P0202891	선두구동주민센터	부산광역시 금정구 두구죽전1길 13	501455	300479	83212	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 금정구 두구죽전1길 13 (선두구동)	2641010100001740001	2641010100101740001027254	부산광역시 금정구 두구동 174-1번지
9	P0202892	장전1동주민센터	부산광역시 금정구 금강로335번길 27	498944	293731	82767	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 금정구 금강로335번길 27 (장전동)	2641010800001540001	2641010800101540001005292	부산광역시 금정구 장전동 154-1번지

	PUBLIC_CD	PUBLIC_NM	ROAD_ADDR	X_AXIS	Y_AXIS	BLK_CD	PUBLIC1_CD	PUBLIC1_NM	PUBLIC2_CD	PUBLIC2_NM	ADDRESS	HOUS_ID	BLD_CD	HOUS_ADDR
190	P0202969	문현2동주민센터	부산광역시 남구 전포대로92번길 31-7	497576	283460	240810	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 남구 전포대로92번길 31-7 (문현동)	2629010900005460042	2629010900105460042017644	부산광역시 남구 문현동 546-42번지
191	P0202970	문현3동주민센터	부산광역시 남구 고동골로4번길 7-18	497858	282672	239477	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 남구 고동골로4번길 7-18 (문현동)	2629010900002050044	2629010900102050044014647	부산광역시 남구 문현동 205-44번지
192	P0202971	문현4동주민센터	부산광역시 남구 수영로 12	497627	282453	235954	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 남구 수영로 12 3층 (문현동)	2629010900003660018	2629010900103660018026603	부산광역시 남구 문현동 366-18번지
193	P0202972	용당동주민센터	부산광역시 남구 신선로 349-4	500012	280421	239413	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 남구 신선로 349-4 (용당동)	2629010800004010001	2629010800104010001013021	부산광역시 남구 용당동 401-1번지
194	P0202973	용호1동주민센터	부산광역시 남구 용호로42번길 140	501282	280784	239710	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 남구 용호로42번길 140 (용호동)	2629010700004140047	2629010700104140047010068	부산광역시 남구 용호동 414-47번지
195	P0202974	용호2동주민센터	부산광역시 남구 용호로197번길 41	501691	280127	239903	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 남구 용호로197번길 41 (용호동)	2629010700005170019	2629010700105170019029994	부산광역시 남구 용호동 517-19번지
196	P0202975	용호3동주민센터	부산광역시 남구 동명로145번길 33	501627	280813	239953	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 남구 동명로145번길 33 (용호동)	2629010700003710002	2629010700103710002029816	부산광역시 남구 용호동 371-2번지
197	P0202976	용호4동주민센터	부산광역시 남구 용호로216번길 10	501418	279944	240027	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 남구 용호로216번길 10 (용호동)	2629010700005330023	2629010700105330023030007	부산광역시 남구 용호동 533-23번지
198	P0202977	우암동주민센터	부산광역시 남구 우암로 190-15	498253	281218	240616	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 남구 우암로 190-15 (우암동)	2629011000001620015	2629011000101620015021487	부산광역시 남구 우암동 162-15번지
199	P0202978	범일1동주민센터	부산광역시 동구 범상로 12	495796	282998	234925	P02000	행정기관	P02003	동/읍/면/리사무소	부산광역시 동구 범상로 12 (범일동)	2617010400014380083	2617010400114380088003002	부산광역시 동구 범일동 1438-83번지

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Uppercase Letter

Most occurring scripts

Most frequent character per script

Common

Latin

Most occurring blocks

Most frequent character per block

ASCII

Most occurring characters

Most occurring categories

Most frequent character per category

Other Letter

Decimal Number

Most occurring scripts

Most frequent character per script

Hangul

Common

Most occurring blocks

Most frequent character per block

Hangul

ASCII

Most occurring characters

Most occurring categories

Most frequent character per category

Other Letter

Decimal Number

Space Separator

Dash Punctuation

Most occurring scripts

Most frequent character per script

Hangul

Common

Most occurring blocks

Most frequent character per block

ASCII

Hangul

Common Values

Length

Common Values (Plot)

Common Values

Length

Common Values (Plot)

Common Values

Length

Common Values (Plot)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Other Letter

Decimal Number

Space Separator

Dash Punctuation

Open Punctuation

Close Punctuation

Most occurring scripts

Most frequent character per script

Hangul

Common

Most occurring blocks

Most frequent character per block

ASCII

Hangul

Most occurring characters

Most occurring categories

Most frequent character per category

Other Letter

Decimal Number

Space Separator

Dash Punctuation

Most occurring scripts

Most frequent character per script