gimi9 Pandas Profiling

Dataset statistics

Number of variables	14
Number of observations	200
Missing cells	164
Missing cells (%)	5.9%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	23.2 KiB
Average record size in memory	118.7 B

Variable types

Text	5
Numeric	6
Categorical	3

Dataset

Description	Sample
Author	오픈메이트
URL	https://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=OPMBANKSHOP000000007

Alerts

`BANK_CD` is highly overall correlated with `REG_DATE` and 2 other fields	High correlation
`BANK_NM` is highly overall correlated with `REG_DATE` and 2 other fields	High correlation
`REG_DATE` is highly overall correlated with `BANK_CD` and 2 other fields	High correlation
`HOUS_ID` is highly overall correlated with `BLD_CD`	High correlation
`BLD_CD` is highly overall correlated with `HOUS_ID`	High correlation
`SHOP_CLSS` is highly overall correlated with `REG_DATE` and 2 other fields	High correlation
`SHOP_CLSS` is highly imbalanced (75.8%)	Imbalance
`REG_DATE` has 164 (82.0%) missing values	Missing
`BSHOP_CD` has unique values	Unique

Reproduction

Analysis started	2023-12-10 06:39:24.342074
Analysis finished	2023-12-10 06:39:47.971471
Duration	23.63 seconds
Software version	ydata-profiling vv4.5.1
Download configuration	config.json

BSHOP_CD
Text

UNIQUE

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

Length

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

Characters and Unicode

Total characters	1200
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	A00050
2nd row	A00051
3rd row	A00052
4th row	A00053
5th row	A00054

Value	Count	Frequency (%)
a00050	1	0.5%
a09958	1	0.5%
a09969	1	0.5%
a09949	1	0.5%
a09950	1	0.5%
a09951	1	0.5%
a09952	1	0.5%
a09953	1	0.5%
a09954	1	0.5%
a09955	1	0.5%
Other values (190)	190	95.0%

Most occurring characters

Value	Count	Frequency (%)
0	328	27.3%
9	292	24.3%
A	200	16.7%
8	91	7.6%
5	51	4.2%
6	49	4.1%
1	47	3.9%
7	47	3.9%
4	34	2.8%
2	31	2.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1000	83.3%
Uppercase Letter	200	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	328	32.8%
9	292	29.2%
8	91	9.1%
5	51	5.1%
6	49	4.9%
1	47	4.7%
7	47	4.7%
4	34	3.4%
2	31	3.1%
3	30	3.0%

Uppercase Letter

Value	Count	Frequency (%)
A	200	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1000	83.3%
Latin	200	16.7%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	328	32.8%
9	292	29.2%
8	91	9.1%
5	51	5.1%
6	49	4.9%
1	47	4.7%
7	47	4.7%
4	34	3.4%
2	31	3.1%
3	30	3.0%

Latin

Value	Count	Frequency (%)
A	200	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1200	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	328	27.3%
9	292	24.3%
A	200	16.7%
8	91	7.6%
5	51	4.2%
6	49	4.1%
1	47	3.9%
7	47	3.9%
4	34	2.8%
2	31	2.6%

BSHOP_NM
Text

Distinct	199
Distinct (%)	99.5%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

Length

Max length	15
Median length	12
Mean length	7.59
Min length	2

Characters and Unicode

Total characters	1518
Distinct characters	163
Distinct categories	5 ?
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	198 ?
Unique (%)	99.0%

Sample

1st row	영업부
2nd row	오창
3rd row	용인
4th row	울산
5th row	원주

Value	Count	Frequency (%)
남광주농협	17	5.4%
남동농협	13	4.1%
김천농협	11	3.5%
김해농협	10	3.2%
남대전농협	9	2.9%
기흥농협	8	2.5%
김제농협	7	2.2%
김포축산농협	7	2.2%
김해축산농협	6	1.9%
낙생농협	6	1.9%
Other values (193)	220	70.1%

Most occurring characters

Value	Count	Frequency (%)
협	138	9.1%
농	135	8.9%
지	132	8.7%
점	121	8.0%
	114	7.5%
김	77	5.1%
남	60	4.0%
주	43	2.8%
동	38	2.5%
산	32	2.1%
Other values (153)	628	41.4%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	1396	92.0%
Space Separator	114	7.5%
Close Punctuation	3	0.2%
Open Punctuation	3	0.2%
Math Symbol	2	0.1%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
협	138	9.9%
농	135	9.7%
지	132	9.5%
점	121	8.7%
김	77	5.5%
남	60	4.3%
주	43	3.1%
동	38	2.7%
산	32	2.3%
천	30	2.1%
Other values (148)	590	42.3%

Math Symbol

Value	Count	Frequency (%)
>	1	50.0%
<	1	50.0%

Space Separator

Value	Count	Frequency (%)
	114	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	3	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	3	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	1396	92.0%
Common	122	8.0%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
협	138	9.9%
농	135	9.7%
지	132	9.5%
점	121	8.7%
김	77	5.5%
남	60	4.3%
주	43	3.1%
동	38	2.7%
산	32	2.3%
천	30	2.1%
Other values (148)	590	42.3%

Common

Value	Count	Frequency (%)
	114	93.4%
)	3	2.5%
(	3	2.5%
>	1	0.8%
<	1	0.8%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	1396	92.0%
ASCII	122	8.0%

Most frequent character per block

Hangul

Value	Count	Frequency (%)
협	138	9.9%
농	135	9.7%
지	132	9.5%
점	121	8.7%
김	77	5.5%
남	60	4.3%
주	43	3.1%
동	38	2.7%
산	32	2.3%
천	30	2.1%
Other values (148)	590	42.3%

ASCII

Value	Count	Frequency (%)
	114	93.4%
)	3	2.5%
(	3	2.5%
>	1	0.8%
<	1	0.8%

ROAD_ADDR
Text

Distinct	199
Distinct (%)	99.5%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

Length

Max length	29
Median length	23
Mean length	17.81
Min length	13

Characters and Unicode

Total characters	3562
Distinct characters	215
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	198 ?
Unique (%)	99.0%

Sample

1st row	서울특별시 영등포구 은행로 14
2nd row	충청북도 청주시 청원구 오창읍 중심상업로 47
3rd row	경기도 용인시 기흥구 동백중앙로 269
4th row	울산광역시 남구 봉월로 56
5th row	강원도 원주시 건강로 1

Value	Count	Frequency (%)
경기도	38	4.4%
경상남도	26	3.0%
경상북도	26	3.0%
김해시	21	2.5%
김천시	20	2.3%
광주광역시	19	2.2%
인천광역시	18	2.1%
전라남도	16	1.9%
김포시	15	1.8%
서울특별시	15	1.8%
Other values (410)	641	75.0%

Most occurring characters

Value	Count	Frequency (%)
	655	18.4%
시	192	5.4%
로	179	5.0%
도	137	3.8%
1	126	3.5%
남	105	2.9%
2	98	2.8%
구	94	2.6%
경	93	2.6%
김	79	2.2%
Other values (205)	1804	50.6%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	2299	64.5%
Space Separator	655	18.4%
Decimal Number	595	16.7%
Dash Punctuation	13	0.4%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
시	192	8.4%
로	179	7.8%
도	137	6.0%
남	105	4.6%
구	94	4.1%
경	93	4.0%
김	79	3.4%
광	73	3.2%
상	59	2.6%
기	53	2.3%
Other values (193)	1235	53.7%

Decimal Number

Value	Count	Frequency (%)
1	126	21.2%
2	98	16.5%
5	60	10.1%
8	52	8.7%
6	50	8.4%
4	48	8.1%
0	43	7.2%
7	40	6.7%
9	39	6.6%
3	39	6.6%

Space Separator

Value	Count	Frequency (%)
	655	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	13	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	2299	64.5%
Common	1263	35.5%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
시	192	8.4%
로	179	7.8%
도	137	6.0%
남	105	4.6%
구	94	4.1%
경	93	4.0%
김	79	3.4%
광	73	3.2%
상	59	2.6%
기	53	2.3%
Other values (193)	1235	53.7%

Common

Value	Count	Frequency (%)
	655	51.9%
1	126	10.0%
2	98	7.8%
5	60	4.8%
8	52	4.1%
6	50	4.0%
4	48	3.8%
0	43	3.4%
7	40	3.2%
9	39	3.1%
Other values (2)	52	4.1%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	2299	64.5%
ASCII	1263	35.5%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	655	51.9%
1	126	10.0%
2	98	7.8%
5	60	4.8%
8	52	4.1%
6	50	4.0%
4	48	3.8%
0	43	3.4%
7	40	3.2%
9	39	3.1%
Other values (2)	52	4.1%

Hangul

Value	Count	Frequency (%)
시	192	8.4%
로	179	7.8%
도	137	6.0%
남	105	4.6%
구	94	4.1%
경	93	4.0%
김	79	3.4%
광	73	3.2%
상	59	2.6%
기	53	2.3%
Other values (193)	1235	53.7%

X_AXIS
Real number (ℝ)

Distinct	198
Distinct (%)	99.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	346801.29

Minimum	220249
Maximum	522300
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 KiB

Quantile statistics

Minimum	220249
5-th percentile	282296.35
Q1	288854.75
median	318186.5
Q3	409948.25
95-th percentile	481723.1
Maximum	522300
Range	302051
Interquartile range (IQR)	121093.5

Descriptive statistics

Standard deviation	72411.084
Coefficient of variation (CV)	0.20879704
Kurtosis	-0.43145265
Mean	346801.29
Median Absolute Deviation (MAD)	32516.5
Skewness	0.94840365
Sum	69360258
Variance	5.2433651 × 10⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
273086	2	1.0%
282605	2	1.0%
282797	1	0.5%
282309	1	0.5%
283131	1	0.5%
283676	1	0.5%
283839	1	0.5%
283487	1	0.5%
283263	1	0.5%
282543	1	0.5%
Other values (188)	188	94.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
220249	1	0.5%
259000	1	0.5%
266211	1	0.5%
266922	1	0.5%
273086	2	1.0%
273395	1	0.5%
278746	1	0.5%
281833	1	0.5%
282056	1	0.5%
282309	1	0.5%

Value	Count	Frequency (%)
522300	1	0.5%
518626	1	0.5%
511499	1	0.5%
510682	1	0.5%
509904	1	0.5%
503260	1	0.5%
499611	1	0.5%
483462	1	0.5%
482590	1	0.5%
481820	1	0.5%

Y_AXIS
Real number (ℝ)

Distinct	199
Distinct (%)	99.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	414410.45

Minimum	99522
Maximum	627961
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 KiB

Quantile statistics

Minimum	99522
5-th percentile	271724.05
Q1	292900
median	391645
Q3	539871.5
95-th percentile	562127.65
Maximum	627961
Range	528439
Interquartile range (IQR)	246971.5

Descriptive statistics

Standard deviation	118141.78
Coefficient of variation (CV)	0.28508398
Kurtosis	-1.2293577
Mean	414410.45
Median Absolute Deviation (MAD)	109849
Skewness	-0.026627938
Sum	82882089
Variance	1.395748 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
287809	2	1.0%
267044	1	0.5%
275424	1	0.5%
374501	1	0.5%
270673	1	0.5%
273221	1	0.5%
271777	1	0.5%
271269	1	0.5%
271109	1	0.5%
269329	1	0.5%
Other values (189)	189	94.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
99522	1	0.5%
107201	1	0.5%
225128	1	0.5%
260992	1	0.5%
267044	1	0.5%
269329	1	0.5%
269873	1	0.5%
270673	1	0.5%
271109	1	0.5%
271269	1	0.5%

Value	Count	Frequency (%)
627961	1	0.5%
626372	1	0.5%
626289	1	0.5%
618281	1	0.5%
585029	1	0.5%
572433	1	0.5%
571112	1	0.5%
569917	1	0.5%
568354	1	0.5%
562159	1	0.5%

BLK_CD
Real number (ℝ)

Distinct	199
Distinct (%)	99.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	251615.94

Minimum	19839
Maximum	516740
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 KiB

Quantile statistics

Minimum	19839
5-th percentile	39444.5
Q1	95924.25
median	190075.5
Q3	425870.75
95-th percentile	495431.8
Maximum	516740
Range	496901
Interquartile range (IQR)	329946.5

Descriptive statistics

Standard deviation	168480.63
Coefficient of variation (CV)	0.66959444
Kurtosis	-1.5935925
Mean	251615.94
Median Absolute Deviation (MAD)	139041.5
Skewness	0.18224278
Sum	50323188
Variance	2.8385724 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
69553	2	1.0%
121572	1	0.5%
69696	1	0.5%
48012	1	0.5%
495163	1	0.5%
63585	1	0.5%
63524	1	0.5%
62748	1	0.5%
63600	1	0.5%
63488	1	0.5%
Other values (189)	189	94.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
19839	1	0.5%
20164	1	0.5%
23713	1	0.5%
23890	1	0.5%
26735	1	0.5%
26831	1	0.5%
28868	1	0.5%
30223	1	0.5%
35557	1	0.5%
37934	1	0.5%

Value	Count	Frequency (%)
516740	1	0.5%
512980	1	0.5%
511602	1	0.5%
510854	1	0.5%
508415	1	0.5%
507890	1	0.5%
507688	1	0.5%
507535	1	0.5%
499534	1	0.5%
497081	1	0.5%

BANK_CD
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

93	136
2	36
11	26
95	2

Length

Max length	2
Median length	2
Mean length	1.82
Min length	1

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

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

Common Values

Value	Count	Frequency (%)
93	136	68.0%
2	36	18.0%
11	26	13.0%
95	2	1.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
93	136	68.0%
2	36	18.0%
11	26	13.0%
95	2	1.0%

BANK_NM
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

지역농협	136
KDB산업은행	36
NH농협은행	26
단위수협	2

Length

Max length	7
Median length	4
Mean length	4.8
Min length	4

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

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

Common Values

Value	Count	Frequency (%)
지역농협	136	68.0%
KDB산업은행	36	18.0%
NH농협은행	26	13.0%
단위수협	2	1.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
지역농협	136	68.0%
kdb산업은행	36	18.0%
nh농협은행	26	13.0%
단위수협	2	1.0%

ADDRESS
Text

Distinct	199
Distinct (%)	99.5%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

Length

Max length	52
Median length	36
Mean length	19.22
Min length	11

Characters and Unicode

Total characters	3844
Distinct characters	253
Distinct categories	7 ?
Distinct scripts	3 ?
Distinct blocks	2 ?

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

Unique

Unique	198 ?
Unique (%)	99.0%

Sample

1st row	서울특별시 영등포구 은행로 14
2nd row	충청북도 청주시 청원구 오창읍 중심상업로 47
3rd row	경기도 용인시 기흥구 동백중앙로 269
4th row	울산광역시 남구 봉월로 56
5th row	강원도 원주시 건강로 1

Value	Count	Frequency (%)
경기도	33	3.7%
경상북도	23	2.5%
김해시	21	2.3%
김천시	20	2.2%
경상남도	20	2.2%
광주광역시	15	1.7%
서울특별시	15	1.7%
김포시	15	1.7%
서구	13	1.4%
남구	13	1.4%
Other values (461)	714	79.2%

Most occurring characters

Value	Count	Frequency (%)
	729	19.0%
시	183	4.8%
로	178	4.6%
1	137	3.6%
도	119	3.1%
2	109	2.8%
남	106	2.8%
구	95	2.5%
경	94	2.4%
김	80	2.1%
Other values (243)	2014	52.4%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	2427	63.1%
Space Separator	729	19.0%
Decimal Number	633	16.5%
Open Punctuation	18	0.5%
Close Punctuation	18	0.5%
Dash Punctuation	14	0.4%
Uppercase Letter	5	0.1%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
시	183	7.5%
로	178	7.3%
도	119	4.9%
남	106	4.4%
구	95	3.9%
경	94	3.9%
김	80	3.3%
광	65	2.7%
동	55	2.3%
기	53	2.2%
Other values (224)	1399	57.6%

Decimal Number

Value	Count	Frequency (%)
1	137	21.6%
2	109	17.2%
5	61	9.6%
8	54	8.5%
6	52	8.2%
0	50	7.9%
4	48	7.6%
9	41	6.5%
7	41	6.5%
3	40	6.3%

Uppercase Letter

Value	Count	Frequency (%)
T	1	20.0%
P	1	20.0%
A	1	20.0%
H	1	20.0%
L	1	20.0%

Space Separator

Value	Count	Frequency (%)
	729	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	18	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	18	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	14	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	2427	63.1%
Common	1412	36.7%
Latin	5	0.1%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
시	183	7.5%
로	178	7.3%
도	119	4.9%
남	106	4.4%
구	95	3.9%
경	94	3.9%
김	80	3.3%
광	65	2.7%
동	55	2.3%
기	53	2.2%
Other values (224)	1399	57.6%

Common

Value	Count	Frequency (%)
	729	51.6%
1	137	9.7%
2	109	7.7%
5	61	4.3%
8	54	3.8%
6	52	3.7%
0	50	3.5%
4	48	3.4%
9	41	2.9%
7	41	2.9%
Other values (4)	90	6.4%

Latin

Value	Count	Frequency (%)
T	1	20.0%
P	1	20.0%
A	1	20.0%
H	1	20.0%
L	1	20.0%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	2427	63.1%
ASCII	1417	36.9%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	729	51.4%
1	137	9.7%
2	109	7.7%
5	61	4.3%
8	54	3.8%
6	52	3.7%
0	50	3.5%
4	48	3.4%
9	41	2.9%
7	41	2.9%
Other values (9)	95	6.7%

Hangul

Value	Count	Frequency (%)
시	183	7.5%
로	178	7.3%
도	119	4.9%
남	106	4.4%
구	95	3.9%
경	94	3.9%
김	80	3.3%
광	65	2.7%
동	55	2.3%
기	53	2.2%
Other values (224)	1399	57.6%

REG_DATE
Real number (ℝ)

HIGH CORRELATION MISSING

Distinct	30
Distinct (%)	83.3%
Missing	164
Missing (%)	82.0%
Infinite	0
Infinite (%)	0.0%
Mean	19949456

Minimum	19540401
Maximum	20160302
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 KiB

Quantile statistics

Minimum	19540401
5-th percentile	19540401
Q1	19885772
median	20010862
Q3	20110218
95-th percentile	20150405
Maximum	20160302
Range	619901
Interquartile range (IQR)	224445.75

Descriptive statistics

Standard deviation	193430.12
Coefficient of variation (CV)	0.0096960098
Kurtosis	-0.0082121285
Mean	19949456
Median Absolute Deviation (MAD)	109998.5
Skewness	-0.96572598
Sum	7.1818041 × 10⁸
Variance	3.7415211 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=30)

Value	Count	Frequency (%)
19540401	4	2.0%
20150102	2	1.0%
19920824	2	1.0%
20110214	2	1.0%
19911025	1	0.5%
20050509	1	0.5%
19900909	1	0.5%
20050613	1	0.5%
19871209	1	0.5%
20150630	1	0.5%
Other values (20)	20	10.0%
(Missing)	164	82.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
19540401	4	2.0%
19680201	1	0.5%
19730510	1	0.5%
19780615	1	0.5%
19860418	1	0.5%
19871209	1	0.5%
19890626	1	0.5%
19890707	1	0.5%
19891028	1	0.5%
19900909	1	0.5%

Value	Count	Frequency (%)
20160302	1	0.5%
20150630	1	0.5%
20150330	1	0.5%
20150102	2	1.0%
20120906	1	0.5%
20120427	1	0.5%
20120323	1	0.5%
20110228	1	0.5%
20110214	2	1.0%
20100326	1	0.5%

SHOP_CLSS
Categorical

HIGH CORRELATION IMBALANCE

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

지점	192
출장소	8

Length

Max length	3
Median length	2
Mean length	2.04
Min length	2

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

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

Common Values

Value	Count	Frequency (%)
지점	192	96.0%
출장소	8	4.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
지점	192	96.0%
출장소	8	4.0%

HOUS_ID
Real number (ℝ)

HIGH CORRELATION

Distinct	199
Distinct (%)	99.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.8350862 × 10¹⁸

Minimum	1.1110125 × 10¹⁸
Maximum	5.0110256 × 10¹⁸
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 KiB

Quantile statistics

Minimum	1.1110125 × 10¹⁸
5-th percentile	1.1650108 × 10¹⁸
Q1	2.9155108 × 10¹⁸
median	4.1570106 × 10¹⁸
Q3	4.7150104 × 10¹⁸
95-th percentile	4.8250118 × 10¹⁸
Maximum	5.0110256 × 10¹⁸
Range	3.9000131 × 10¹⁸
Interquartile range (IQR)	1.7994996 × 10¹⁸

Descriptive statistics

Standard deviation	1.0661138 × 10¹⁸
Coefficient of variation (CV)	0.27798952
Kurtosis	0.45133262
Mean	3.8350862 × 10¹⁸
Median Absolute Deviation (MAD)	5.5802497 × 10¹⁷
Skewness	-1.1413022
Sum	-7.7460129 × 10¹⁸
Variance	1.1365986 × 10³⁶
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4686037024008220031	2	1.0%
4617012800001880011	1	0.5%
4686035026008560003	1	0.5%
4513014400008050001	1	0.5%
4617011100000600010	1	0.5%
4617011600003160000	1	0.5%
4617012200013900001	1	0.5%
4617011500000910000	1	0.5%
4617011500000610001	1	0.5%
4617010200011000000	1	0.5%
Other values (189)	189	94.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1111012500000140000	1	0.5%
1114011800001180000	1	0.5%
1154510100003710037	1	0.5%
1154510200009540004	1	0.5%
1156011000000160003	1	0.5%
1162010200006070073	1	0.5%
1165010200000110001	1	0.5%
1165010300007600000	1	0.5%
1165010600000360014	1	0.5%
1165010600000500006	1	0.5%

Value	Count	Frequency (%)
5011025634016340000	1	0.5%
5011012200037840008	1	0.5%
4888038021010170000	1	0.5%
4888037021005560001	1	0.5%
4882040021008190019	1	0.5%
4825032028006380003	1	0.5%
4825032025012750001	1	0.5%
4825013100013340002	1	0.5%
4825012500011610001	1	0.5%
4825012000001610024	1	0.5%

BLD_CD
Real number (ℝ)

HIGH CORRELATION

Distinct	199
Distinct (%)	99.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.8396805 × 10²⁴

Minimum	1.1110125 × 10²⁴
Maximum	5.0110256 × 10²⁴
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 KiB

Quantile statistics

Minimum	1.1110125 × 10²⁴
5-th percentile	1.1650108 × 10²⁴
Q1	2.9155108 × 10²⁴
median	4.1570106 × 10²⁴
Q3	4.7150104 × 10²⁴
95-th percentile	4.8250118 × 10²⁴
Maximum	5.0110256 × 10²⁴
Range	3.9000131 × 10²⁴
Interquartile range (IQR)	1.7994996 × 10²⁴

Descriptive statistics

Standard deviation	1.0671 × 10²⁴
Coefficient of variation (CV)	0.27791376
Kurtosis	0.45933568
Mean	3.8396805 × 10²⁴
Median Absolute Deviation (MAD)	5.5802492 × 10²³
Skewness	-1.1499002
Sum	7.679361 × 10²⁶
Variance	1.1387025 × 10⁴⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4.68603702410822e+24	2	1.0%
4.61701280010188e+24	1	0.5%
4.68603502610856e+24	1	0.5%
4.5130144001080496e+24	1	0.5%
4.6170111001006e+24	1	0.5%
4.61701160010316e+24	1	0.5%
4.6170122001138895e+24	1	0.5%
4.61701150010088e+24	1	0.5%
4.61701150010061e+24	1	0.5%
4.617010200111e+24	1	0.5%
Other values (189)	189	94.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1.11101250010014e+24	1	0.5%
1.11401180010118e+24	1	0.5%
1.15451010010371e+24	1	0.5%
1.15451020010954e+24	1	0.5%
1.15601100010016e+24	1	0.5%
1.16201020010607e+24	1	0.5%
1.16501020010011e+24	1	0.5%
1.1650103001076e+24	1	0.5%
1.16501060010036e+24	1	0.5%
1.1650106001005e+24	1	0.5%

Value	Count	Frequency (%)
5.01102563401634e+24	1	0.5%
5.01101220013784e+24	1	0.5%
4.88803802111017e+24	1	0.5%
4.88803702110556e+24	1	0.5%
4.88204002110819e+24	1	0.5%
4.82503202810638e+24	1	0.5%
4.8250320251127505e+24	1	0.5%
4.82503102911334e+24	1	0.5%
4.82503102610039e+24	1	0.5%
4.8250120001016096e+24	1	0.5%

HOUS_ADDR
Text

Distinct	199
Distinct (%)	99.5%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

Length

Max length	28
Median length	26
Mean length	20.815
Min length	16

Characters and Unicode

Total characters	4163
Distinct characters	181
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	198 ?
Unique (%)	99.0%

Sample

1st row	서울특별시 영등포구 여의도동 16-3번지
2nd row	충청북도 청주시 청원구 오창읍 양청리 792-1번지
3rd row	경기도 용인시 기흥구 중동 830-3번지
4th row	울산광역시 남구 신정동 1156-4번지
5th row	강원도 원주시 반곡동 1901-2번지

Value	Count	Frequency (%)
경기도	38	4.4%
경상북도	26	3.0%
경상남도	26	3.0%
김해시	21	2.5%
김천시	20	2.3%
광주광역시	19	2.2%
인천광역시	18	2.1%
전라남도	16	1.9%
김포시	15	1.8%
서울특별시	15	1.8%
Other values (435)	641	75.0%

Most occurring characters

Value	Count	Frequency (%)
	655	15.7%
지	202	4.9%
번	200	4.8%
1	192	4.6%
동	191	4.6%
시	188	4.5%
-	148	3.6%
도	137	3.3%
구	102	2.5%
경	93	2.2%
Other values (171)	2055	49.4%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	2567	61.7%
Decimal Number	793	19.0%
Space Separator	655	15.7%
Dash Punctuation	148	3.6%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
지	202	7.9%
번	200	7.8%
동	191	7.4%
시	188	7.3%
도	137	5.3%
구	102	4.0%
경	93	3.6%
남	90	3.5%
광	73	2.8%
김	67	2.6%
Other values (159)	1224	47.7%

Decimal Number

Value	Count	Frequency (%)
1	192	24.2%
4	89	11.2%
2	81	10.2%
5	71	9.0%
6	70	8.8%
8	65	8.2%
0	63	7.9%
3	60	7.6%
7	55	6.9%
9	47	5.9%

Space Separator

Value	Count	Frequency (%)
	655	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	148	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	2567	61.7%
Common	1596	38.3%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
지	202	7.9%
번	200	7.8%
동	191	7.4%
시	188	7.3%
도	137	5.3%
구	102	4.0%
경	93	3.6%
남	90	3.5%
광	73	2.8%
김	67	2.6%
Other values (159)	1224	47.7%

Common

Value	Count	Frequency (%)
	655	41.0%
1	192	12.0%
-	148	9.3%
4	89	5.6%
2	81	5.1%
5	71	4.4%
6	70	4.4%
8	65	4.1%
0	63	3.9%
3	60	3.8%
Other values (2)	102	6.4%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	2567	61.7%
ASCII	1596	38.3%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	655	41.0%
1	192	12.0%
-	148	9.3%
4	89	5.6%
2	81	5.1%
5	71	4.4%
6	70	4.4%
8	65	4.1%
0	63	3.9%
3	60	3.8%
Other values (2)	102	6.4%

Hangul

Value	Count	Frequency (%)
지	202	7.9%
번	200	7.8%
동	191	7.4%
시	188	7.3%
도	137	5.3%
구	102	4.0%
경	93	3.6%
남	90	3.5%
광	73	2.8%
김	67	2.6%
Other values (159)	1224	47.7%

Heatmap
Table

	X_AXIS	Y_AXIS	BLK_CD	BANK_CD	BANK_NM	REG_DATE	SHOP_CLSS	HOUS_ID	BLD_CD
X_AXIS	1.000	0.695	0.488	0.484	0.484	0.000	0.000	0.707	0.715
Y_AXIS	0.695	1.000	0.590	0.000	0.000	0.000	0.000	0.660	0.643
BLK_CD	0.488	0.590	1.000	0.275	0.275	0.142	0.000	0.587	0.598
BANK_CD	0.484	0.000	0.275	1.000	1.000	NaN	0.723	0.438	0.308
BANK_NM	0.484	0.000	0.275	1.000	1.000	NaN	0.723	0.438	0.308
REG_DATE	0.000	0.000	0.142	NaN	NaN	1.000	NaN	0.617	0.617
SHOP_CLSS	0.000	0.000	0.000	0.723	0.723	NaN	1.000	0.000	0.000
HOUS_ID	0.707	0.660	0.587	0.438	0.438	0.617	0.000	1.000	1.000
BLD_CD	0.715	0.643	0.598	0.308	0.308	0.617	0.000	1.000	1.000

Heatmap
Table

	BANK_CD	SHOP_CLSS	BANK_NM
BANK_CD	1.000	0.515	1.000
SHOP_CLSS	0.515	1.000	0.515
BANK_NM	1.000	0.515	1.000

Heatmap
Table

	X_AXIS	Y_AXIS	BLK_CD	REG_DATE	HOUS_ID	BLD_CD	BANK_CD	BANK_NM	SHOP_CLSS
X_AXIS	1.000	-0.163	0.141	0.020	0.410	0.412	0.319	0.319	0.000
Y_AXIS	-0.163	1.000	0.157	0.218	-0.435	-0.438	0.000	0.000	0.000
BLK_CD	0.141	0.157	1.000	0.131	0.034	0.036	0.157	0.157	0.000
REG_DATE	0.020	0.218	0.131	1.000	-0.057	-0.052	1.000	1.000	1.000
HOUS_ID	0.410	-0.435	0.034	-0.057	1.000	0.998	0.213	0.213	0.000
BLD_CD	0.412	-0.438	0.036	-0.052	0.998	1.000	0.123	0.123	0.071
BANK_CD	0.319	0.000	0.157	1.000	0.213	0.123	1.000	1.000	0.515
BANK_NM	0.319	0.000	0.157	1.000	0.213	0.123	1.000	1.000	0.515
SHOP_CLSS	0.000	0.000	0.000	1.000	0.000	0.071	0.515	0.515	1.000

Count
Matrix

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.

First rows
Last rows

	BSHOP_CD	BSHOP_NM	ROAD_ADDR	X_AXIS	Y_AXIS	BLK_CD	BANK_CD	BANK_NM	ADDRESS	REG_DATE	SHOP_CLSS	HOUS_ID	BLD_CD	HOUS_ADDR
0	A00050	영업부	서울특별시 영등포구 은행로 14	304810	547759	227388	2	KDB산업은행	서울특별시 영등포구 은행로 14	19680201	지점	1156011000000160003	1156011000100160003031606	서울특별시 영등포구 여의도동 16-3번지
1	A00051	오창	충청북도 청주시 청원구 오창읍 중심상업로 47	349181	457252	443039	2	KDB산업은행	충청북도 청주시 청원구 오창읍 중심상업로 47	20160302	지점	4311425345007920001	4371025345107920001000001	충청북도 청주시 청원구 오창읍 양청리 792-1번지
2	A00052	용인	경기도 용인시 기흥구 동백중앙로 269	325086	519758	431340	2	KDB산업은행	경기도 용인시 기흥구 동백중앙로 269	20110214	지점	4146311600008300003	4146311600108300003017945	경기도 용인시 기흥구 중동 830-3번지
3	A00053	울산	울산광역시 남구 봉월로 56	518626	327223	274425	2	KDB산업은행	울산광역시 남구 봉월로 56	19730510	지점	3114010400011560004	3114010400111560004011993	울산광역시 남구 신정동 1156-4번지
4	A00054	원주	강원도 원주시 건강로 1	398950	525028	429147	2	KDB산업은행	강원도 원주시 건강로 1	20060515	지점	4213011700019010002	4213011700119010002000001	강원도 원주시 반곡동 1901-2번지
5	A00055	의정부	경기도 의정부시 시민로 31	315469	571112	282439	2	KDB산업은행	경기도 의정부시 시민로 31	20150102	지점	4115010100004860011	4115010100104860011020763	경기도 의정부시 의정부동 486-11번지
6	A00056	인천	인천광역시 남동구 미래로 42	285693	539858	422724	2	KDB산업은행	인천광역시 남동구 미래로 42	19540401	지점	2820010100011400000	2820010100111400000000001	인천광역시 남동구 구월동 1140번지
7	A00057	일산	경기도 고양시 일산동구 중앙로 1201	292213	561970	292931	2	KDB산업은행	경기도 고양시 일산동구 중앙로 1201	20040726	지점	4128510400008900000	4128510400108900000002637	경기도 고양시 일산동구 장항동 890번지
8	A00058	잠실	서울특별시 송파구 올림픽로 289	320856	546203	154879	2	KDB산업은행	서울특별시 송파구 올림픽로 289	19890626	지점	1171010200000070019	1171010200100070019000140	서울특별시 송파구 신천동 7-19번지
9	A00059	잠원	서울특별시 서초구 강남대로 565	313586	546010	23890	2	KDB산업은행	서울특별시 서초구 강남대로 565	20120427	지점	1165010600000360014	1165010600100360014019363	서울특별시 서초구 잠원동 36-14번지

	BSHOP_CD	BSHOP_NM	ROAD_ADDR	X_AXIS	Y_AXIS	BLK_CD	BANK_CD	BANK_NM	ADDRESS	REG_DATE	SHOP_CLSS	HOUS_ID	BLD_CD	HOUS_ADDR
190	A00002	강남	서울특별시 강남구 영동대로 508	317354	545758	270751	2	KDB산업은행	서울특별시 강남구 영동대로 508	19920824	지점	1168010500001680001	1168010500101680001016579	서울특별시 강남구 삼성동 168-1번지
191	A00003	경산	경상북도 경산시 대학로 73	466197	359634	164659	2	KDB산업은행	경상북도 경산시 대학로 73	20120906	지점	4729011100002550120	4729011100102550099000001	경상북도 경산시 정평동 255-120번지
192	A00004	경주	경상북도 경주시 화랑로 125	509904	361228	77824	2	KDB산업은행	경상북도 경주시 화랑로 125	20150630	지점	4713010400003860006	4713010400103860006005652	경상북도 경주시 성동동 386-6번지
193	A00005	광주	광주광역시 광산구 무진대로 261	291715	285439	489639	2	KDB산업은행	광주광역시 광산구 무진대로 261	19540401	지점	2920010900015840001	2920010900115840001041538	광주광역시 광산구 우산동 1584-1번지
194	A00006	구미	경상북도 구미시 송정대로 107	431704	390819	321420	2	KDB산업은행	경상북도 구미시 송정대로 107	19871209	지점	4719011000000780000	4719011000100780000027926	경상북도 구미시 송정동 78번지
195	A00007	군산	전라북도 군산시 월명로 206	284389	374339	460544	2	KDB산업은행	전라북도 군산시 월명로 206	19891028	지점	4513014100008540002	4513014100108540002000001	전라북도 군산시 수송동 854-2번지
196	A00008	금남로	광주광역시 동구 금남로 168	301041	284249	109349	2	KDB산업은행	광주광역시 동구 금남로 168	20150102	지점	2911010200000620017	2911010200100620017003445	광주광역시 동구 금남로5가 62-17번지
197	A00009	금정	부산광역시 금정구 중앙대로 1817	499611	294702	83443	2	KDB산업은행	부산광역시 금정구 중앙대로 1817	19900909	지점	2641010700000840018	2641010700100840018011702	부산광역시 금정구 구서동 84-18번지
198	A00010	금천	서울특별시 금천구 시흥대로 488	302834	542228	20164	2	KDB산업은행	서울특별시 금천구 시흥대로 488	19911025	지점	1154510200009540004	1154510200109540004007611	서울특별시 금천구 독산동 954-4번지
199	A00011	김포	경기도 김포시 중봉로 15	285169	558728	410130	2	KDB산업은행	경기도 김포시 중봉로 15	20050509	지점	4157010500005060000	4157010500105060000023794	경기도 김포시 감정동 506번지

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

Math Symbol

Space Separator

Close Punctuation

Open Punctuation

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)

Most occurring characters

Most occurring categories

Most frequent character per category

Other Letter

Decimal Number

Uppercase Letter

Space Separator

Open Punctuation

Close Punctuation

Dash Punctuation

Most occurring scripts

Most frequent character per script

Hangul

Common

Latin

Most occurring blocks

Most frequent character per block

ASCII

Hangul

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