gimi9 Pandas Profiling

Dataset statistics

Number of variables	14
Number of observations	200
Missing cells	290
Missing cells (%)	10.4%
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	6
Numeric	5
Categorical	2
Unsupported	1

Dataset

Description	Sample
Author	오픈메이트
URL	https://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=OPMTERMINAL000000015

Alerts

`TERMINAL_CLSS` has constant value ""	Constant
`PROC_CLSS` has constant value ""	Constant
`BLD_CD` is highly overall correlated with `HOUS_ID` and 1 other fields	High correlation
`HOUS_ID` is highly overall correlated with `BLD_CD` and 1 other fields	High correlation
`Y_AXIS` is highly overall correlated with `BLD_CD` and 1 other fields	High correlation
`BLD_CD` has 44 (22.0%) missing values	Missing
`EDIT_NEWADDR` has 46 (23.0%) missing values	Missing
`ROUTE_CNT` has 200 (100.0%) missing values	Missing
`TERMINAL_CD` has unique values	Unique
`TERMINAL_NM` has unique values	Unique
`ROUTE_CNT` is an unsupported type, check if it needs cleaning or further analysis	Unsupported

Reproduction

Analysis started	2023-12-10 06:16:50.076521
Analysis finished	2023-12-10 06:17:06.223117
Duration	16.15 seconds
Software version	ydata-profiling vv4.5.1
Download configuration	config.json

TERMINAL_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	E00207
2nd row	E00209
3rd row	E00210
4th row	E00211
5th row	E00212

Value	Count	Frequency (%)
e00207	1	0.5%
e00141	1	0.5%
e00160	1	0.5%
e00129	1	0.5%
e00130	1	0.5%
e00131	1	0.5%
e00132	1	0.5%
e00133	1	0.5%
e00134	1	0.5%
e00136	1	0.5%
Other values (190)	190	95.0%

Most occurring characters

Value	Count	Frequency (%)
0	511	42.6%
E	200	16.7%
1	113	9.4%
2	86	7.2%
4	56	4.7%
6	44	3.7%
3	42	3.5%
7	40	3.3%
5	40	3.3%
8	35	2.9%

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	511	51.1%
1	113	11.3%
2	86	8.6%
4	56	5.6%
6	44	4.4%
3	42	4.2%
7	40	4.0%
5	40	4.0%
8	35	3.5%
9	33	3.3%

Uppercase Letter

Value	Count	Frequency (%)
E	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	511	51.1%
1	113	11.3%
2	86	8.6%
4	56	5.6%
6	44	4.4%
3	42	4.2%
7	40	4.0%
5	40	4.0%
8	35	3.5%
9	33	3.3%

Latin

Value	Count	Frequency (%)
E	200	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1200	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	511	42.6%
E	200	16.7%
1	113	9.4%
2	86	7.2%
4	56	4.7%
6	44	3.7%
3	42	3.5%
7	40	3.3%
5	40	3.3%
8	35	2.9%

TERMINAL_NM
Text

UNIQUE

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

Length

Max length	25
Median length	21
Mean length	9.41
Min length	4

Characters and Unicode

Total characters	1882
Distinct characters	153
Distinct categories	3 ?
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	200 ?
Unique (%)	100.0%

Sample

1st row	동서울고속버스터미널(동서울종합터미널)
2nd row	동창공용버스터미널(세지정류소)
3rd row	동해시외버스터미널
4th row	두밀리정류소
5th row	두원공대

Value	Count	Frequency (%)
동서울고속버스터미널(동서울종합터미널	1	0.5%
다시공용버스정류장	1	0.5%
대둔산공용버스터미널	1	0.5%
내촌포천정류소	1	0.5%
노성정류소	1	0.5%
노원역정류소	1	0.5%
녹동신항정류소	1	0.5%
녹동터미널(녹동공용버스정류장	1	0.5%
녹전정류소	1	0.5%
논티정류소	1	0.5%
Other values (190)	190	95.0%

Most occurring characters

Value	Count	Frequency (%)
정	128	6.8%
류	122	6.5%
미	117	6.2%
터	112	6.0%
널	112	6.0%
버	102	5.4%
스	102	5.4%
소	100	5.3%
시	60	3.2%
외	55	2.9%
Other values (143)	872	46.3%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	1784	94.8%
Close Punctuation	49	2.6%
Open Punctuation	49	2.6%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
정	128	7.2%
류	122	6.8%
미	117	6.6%
터	112	6.3%
널	112	6.3%
버	102	5.7%
스	102	5.7%
소	100	5.6%
시	60	3.4%
외	55	3.1%
Other values (141)	774	43.4%

Close Punctuation

Value	Count	Frequency (%)
)	49	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	49	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	1784	94.8%
Common	98	5.2%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
정	128	7.2%
류	122	6.8%
미	117	6.6%
터	112	6.3%
널	112	6.3%
버	102	5.7%
스	102	5.7%
소	100	5.6%
시	60	3.4%
외	55	3.1%
Other values (141)	774	43.4%

Common

Value	Count	Frequency (%)
)	49	50.0%
(	49	50.0%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	1784	94.8%
ASCII	98	5.2%

Most frequent character per block

Hangul

Value	Count	Frequency (%)
정	128	7.2%
류	122	6.8%
미	117	6.6%
터	112	6.3%
널	112	6.3%
버	102	5.7%
스	102	5.7%
소	100	5.6%
시	60	3.4%
외	55	3.1%
Other values (141)	774	43.4%

ASCII

Value	Count	Frequency (%)
)	49	50.0%
(	49	50.0%

BLD_CD
Real number (ℝ)

HIGH CORRELATION MISSING

Distinct	148
Distinct (%)	94.9%
Missing	44
Missing (%)	22.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.2521288 × 10²⁴

Minimum	1.1215103 × 10²⁴
Maximum	4.889045 × 10²⁴
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 KiB

Quantile statistics

Minimum	1.1215103 × 10²⁴
5-th percentile	2.7170102 × 10²⁴
Q1	4.1820307 × 10²⁴
median	4.4755322 × 10²⁴
Q3	4.6822825 × 10²⁴
95-th percentile	4.8155417 × 10²⁴
Maximum	4.889045 × 10²⁴
Range	3.7675347 × 10²⁴
Interquartile range (IQR)	5.0025187 × 10²³

Descriptive statistics

Standard deviation	7.3756726 × 10²³
Coefficient of variation (CV)	0.17345835
Kurtosis	6.6921813
Mean	4.2521288 × 10²⁴
Median Absolute Deviation (MAD)	2.3749315 × 10²³
Skewness	-2.4972745
Sum	6.6333209 × 10²⁶
Variance	5.4400547 × 10⁴⁷
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2.91401150010049e+24	2	1.0%
2.71701020011856e+24	2	1.0%
3.01101150010068e+24	2	1.0%
3.01401170010759e+24	2	1.0%
4.6770253241161294e+24	2	1.0%
4.82501090011264e+24	2	1.0%
4.5180119001005104e+24	2	1.0%
3.01701120010908e+24	2	1.0%
4.1570101001038e+24	1	0.5%
4.1730350331080497e+24	1	0.5%
Other values (138)	138	69.0%
(Missing)	44	22.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1.12151030010546e+24	1	0.5%
1.16501080011446e+24	1	0.5%
1.16801010010831e+24	1	0.5%
1.1710107001015e+24	1	0.5%
2.67102502110124e+24	1	0.5%
2.7140102e+24	1	0.5%
2.71401020010328e+24	1	0.5%
2.71701020011856e+24	2	1.0%
2.72601020011041e+24	1	0.5%
2.91401150010049e+24	2	1.0%

Value	Count	Frequency (%)
4.889045023108991e+24	1	0.5%
4.88802502411005e+24	1	0.5%
4.88202502510416e+24	1	0.5%
4.87203302610442e+24	1	0.5%
4.8310109001097906e+24	1	0.5%
4.82501090011264e+24	2	1.0%
4.8240350211009693e+24	1	0.5%
4.81271060010267e+24	1	0.5%
4.8125158001000494e+24	1	0.5%
4.7930350211026e+24	1	0.5%

EDIT_ADDR
Text

Distinct	192
Distinct (%)	96.0%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

Length

Max length	28
Median length	26
Mean length	22.52
Min length	18

Characters and Unicode

Total characters	4504
Distinct characters	202
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	184 ?
Unique (%)	92.0%

Sample

1st row	서울특별시 광진구 구의동 546-1번지
2nd row	전라남도 나주시 세지면 오봉리 727-173번지
3rd row	강원도 동해시 천곡동 485-10번지
4th row	경기도 가평군 가평읍 두밀리 742번지
5th row	경기도 안성시 죽산면 장원리 716번지

Value	Count	Frequency (%)
경기도	30	3.2%
경상북도	30	3.2%
강원도	26	2.7%
전라남도	24	2.5%
충청남도	23	2.4%
전라북도	17	1.8%
충청북도	14	1.5%
경상남도	12	1.3%
대전광역시	9	0.9%
가평군	7	0.7%
Other values (621)	758	79.8%

Most occurring characters

Value	Count	Frequency (%)
	750	16.7%
지	206	4.6%
번	200	4.4%
도	188	4.2%
1	179	4.0%
-	164	3.6%
리	145	3.2%
시	110	2.4%
면	100	2.2%
군	98	2.2%
Other values (192)	2364	52.5%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	2807	62.3%
Decimal Number	783	17.4%
Space Separator	750	16.7%
Dash Punctuation	164	3.6%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
지	206	7.3%
번	200	7.1%
도	188	6.7%
리	145	5.2%
시	110	3.9%
면	100	3.6%
군	98	3.5%
경	85	3.0%
동	82	2.9%
남	78	2.8%
Other values (180)	1515	54.0%

Decimal Number

Value	Count	Frequency (%)
1	179	22.9%
3	91	11.6%
2	78	10.0%
6	75	9.6%
4	70	8.9%
7	68	8.7%
5	64	8.2%
8	57	7.3%
9	56	7.2%
0	45	5.7%

Space Separator

Value	Count	Frequency (%)
	750	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	164	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	2807	62.3%
Common	1697	37.7%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
지	206	7.3%
번	200	7.1%
도	188	6.7%
리	145	5.2%
시	110	3.9%
면	100	3.6%
군	98	3.5%
경	85	3.0%
동	82	2.9%
남	78	2.8%
Other values (180)	1515	54.0%

Common

Value	Count	Frequency (%)
	750	44.2%
1	179	10.5%
-	164	9.7%
3	91	5.4%
2	78	4.6%
6	75	4.4%
4	70	4.1%
7	68	4.0%
5	64	3.8%
8	57	3.4%
Other values (2)	101	6.0%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	2807	62.3%
ASCII	1697	37.7%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	750	44.2%
1	179	10.5%
-	164	9.7%
3	91	5.4%
2	78	4.6%
6	75	4.4%
4	70	4.1%
7	68	4.0%
5	64	3.8%
8	57	3.4%
Other values (2)	101	6.0%

Hangul

Value	Count	Frequency (%)
지	206	7.3%
번	200	7.1%
도	188	6.7%
리	145	5.2%
시	110	3.9%
면	100	3.6%
군	98	3.5%
경	85	3.0%
동	82	2.9%
남	78	2.8%
Other values (180)	1515	54.0%

EDIT_NEWADDR
Text

MISSING

Distinct	146
Distinct (%)	94.8%
Missing	46
Missing (%)	23.0%
Memory size	1.7 KiB

Length

Max length	25
Median length	23
Mean length	19.506494
Min length	14

Characters and Unicode

Total characters	3004
Distinct characters	197
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	3 ?

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

Unique

Unique	138 ?
Unique (%)	89.6%

Sample

1st row	서울특별시 광진구 강변역로 50
2nd row	전라남도 나주시 세지면 동창로 142
3rd row	경기도 가평군 가평읍 태봉두밀로 598
4th row	강원도 홍천군 두촌면 자은로 370
5th row	강원도 횡성군 둔내면 경강로둔방10길 12

Value	Count	Frequency (%)
경상북도	24	3.3%
전라남도	22	3.0%
경기도	21	2.9%
강원도	18	2.5%
전라북도	15	2.1%
충청남도	13	1.8%
충청북도	11	1.5%
경상남도	10	1.4%
대전광역시	8	1.1%
서구	6	0.8%
Other values (472)	580	79.7%

Most occurring characters

Value	Count	Frequency (%)
	574	19.1%
도	143	4.8%
로	131	4.4%
1	105	3.5%
시	83	2.8%
군	77	2.6%
경	71	2.4%
면	68	2.3%
남	58	1.9%
3	56	1.9%
Other values (187)	1638	54.5%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	1942	64.6%
Space Separator	574	19.1%
Decimal Number	472	15.7%
Dash Punctuation	15	0.5%
Other Punctuation	1	< 0.1%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
도	143	7.4%
로	131	6.7%
시	83	4.3%
군	77	4.0%
경	71	3.7%
면	68	3.5%
남	58	3.0%
북	56	2.9%
대	48	2.5%
전	46	2.4%
Other values (174)	1161	59.8%

Decimal Number

Value	Count	Frequency (%)
1	105	22.2%
3	56	11.9%
2	53	11.2%
0	43	9.1%
9	42	8.9%
4	41	8.7%
5	39	8.3%
8	36	7.6%
7	31	6.6%
6	26	5.5%

Space Separator

Value	Count	Frequency (%)
	574	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	15	100.0%

Other Punctuation

Value	Count	Frequency (%)
·	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	1942	64.6%
Common	1062	35.4%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
도	143	7.4%
로	131	6.7%
시	83	4.3%
군	77	4.0%
경	71	3.7%
면	68	3.5%
남	58	3.0%
북	56	2.9%
대	48	2.5%
전	46	2.4%
Other values (174)	1161	59.8%

Common

Value	Count	Frequency (%)
	574	54.0%
1	105	9.9%
3	56	5.3%
2	53	5.0%
0	43	4.0%
9	42	4.0%
4	41	3.9%
5	39	3.7%
8	36	3.4%
7	31	2.9%
Other values (3)	42	4.0%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	1942	64.6%
ASCII	1061	35.3%
None	1	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	574	54.1%
1	105	9.9%
3	56	5.3%
2	53	5.0%
0	43	4.1%
9	42	4.0%
4	41	3.9%
5	39	3.7%
8	36	3.4%
7	31	2.9%
Other values (2)	41	3.9%

Hangul

Value	Count	Frequency (%)
도	143	7.4%
로	131	6.7%
시	83	4.3%
군	77	4.0%
경	71	3.7%
면	68	3.5%
남	58	3.0%
북	56	2.9%
대	48	2.5%
전	46	2.4%
Other values (174)	1161	59.8%

None

Value	Count	Frequency (%)
·	1	100.0%

BLK_CD_V4
Real number (ℝ)

Distinct	192
Distinct (%)	96.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	251878.23

Minimum	409
Maximum	511318
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 KiB

Quantile statistics

Minimum	409
5-th percentile	21383.5
Q1	74519
median	303423
Q3	353662.75
95-th percentile	485628.7
Maximum	511318
Range	510909
Interquartile range (IQR)	279143.75

Descriptive statistics

Standard deviation	156071.17
Coefficient of variation (CV)	0.61962946
Kurtosis	-1.2449579
Mean	251878.23
Median Absolute Deviation (MAD)	130583.5
Skewness	-0.12774103
Sum	50375646
Variance	2.4358211 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
49693	2	1.0%
118832	2	1.0%
498133	2	1.0%
268880	2	1.0%
265930	2	1.0%
485265	2	1.0%
360227	2	1.0%
257379	2	1.0%
362889	1	0.5%
336890	1	0.5%
Other values (182)	182	91.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
409	1	0.5%
1905	1	0.5%
2910	1	0.5%
4591	1	0.5%
5516	1	0.5%
6275	1	0.5%
6789	1	0.5%
7212	1	0.5%
12096	1	0.5%
15693	1	0.5%

Value	Count	Frequency (%)
511318	1	0.5%
511317	1	0.5%
510962	1	0.5%
508729	1	0.5%
505212	1	0.5%
498133	2	1.0%
498052	1	0.5%
494534	1	0.5%
492539	1	0.5%
485265	2	1.0%

TERMINAL_CLSS
Categorical

CONSTANT

Distinct	1
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

시외	200

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

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

Common Values

Value	Count	Frequency (%)
시외	200	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
시외	200	100.0%

ROUTE_CNT
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	200
Missing (%)	100.0%
Memory size	1.9 KiB

ADDRESS
Text

Distinct	193
Distinct (%)	96.5%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

Length

Max length	25
Median length	23
Mean length	20.365
Min length	14

Characters and Unicode

Total characters	4073
Distinct characters	203
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	186 ?
Unique (%)	93.0%

Sample

1st row	서울특별시 광진구 구의동 546-1
2nd row	전라남도 나주시 세지면 오봉리 727-173
3rd row	강원도 동해시 천곡동 485-10
4th row	경기도 가평군 가평읍 두밀리 742
5th row	경기도 안성시 죽산면 장원리 716

Value	Count	Frequency (%)
경기도	28	3.0%
경상북도	27	2.9%
강원도	26	2.8%
충청남도	23	2.4%
전라남도	23	2.4%
전라북도	15	1.6%
경상남도	12	1.3%
충청북도	12	1.3%
대전광역시	8	0.9%
가평군	7	0.7%
Other values (628)	758	80.7%

Most occurring characters

Value	Count	Frequency (%)
	739	18.1%
도	180	4.4%
1	177	4.3%
-	154	3.8%
리	138	3.4%
시	105	2.6%
군	102	2.5%
면	102	2.5%
3	89	2.2%
경	85	2.1%
Other values (193)	2202	54.1%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	2395	58.8%
Decimal Number	785	19.3%
Space Separator	739	18.1%
Dash Punctuation	154	3.8%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
도	180	7.5%
리	138	5.8%
시	105	4.4%
군	102	4.3%
면	102	4.3%
경	85	3.5%
남	79	3.3%
동	75	3.1%
북	67	2.8%
전	59	2.5%
Other values (181)	1403	58.6%

Decimal Number

Value	Count	Frequency (%)
1	177	22.5%
3	89	11.3%
2	83	10.6%
6	72	9.2%
7	72	9.2%
4	71	9.0%
5	64	8.2%
8	55	7.0%
9	54	6.9%
0	48	6.1%

Space Separator

Value	Count	Frequency (%)
	739	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	154	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	2395	58.8%
Common	1678	41.2%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
도	180	7.5%
리	138	5.8%
시	105	4.4%
군	102	4.3%
면	102	4.3%
경	85	3.5%
남	79	3.3%
동	75	3.1%
북	67	2.8%
전	59	2.5%
Other values (181)	1403	58.6%

Common

Value	Count	Frequency (%)
	739	44.0%
1	177	10.5%
-	154	9.2%
3	89	5.3%
2	83	4.9%
6	72	4.3%
7	72	4.3%
4	71	4.2%
5	64	3.8%
8	55	3.3%
Other values (2)	102	6.1%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	2395	58.8%
ASCII	1678	41.2%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	739	44.0%
1	177	10.5%
-	154	9.2%
3	89	5.3%
2	83	4.9%
6	72	4.3%
7	72	4.3%
4	71	4.2%
5	64	3.8%
8	55	3.3%
Other values (2)	102	6.1%

Hangul

Value	Count	Frequency (%)
도	180	7.5%
리	138	5.8%
시	105	4.4%
군	102	4.3%
면	102	4.3%
경	85	3.5%
남	79	3.3%
동	75	3.1%
북	67	2.8%
전	59	2.5%
Other values (181)	1403	58.6%

HOUS_ID
Real number (ℝ)

HIGH CORRELATION

Distinct	192
Distinct (%)	96.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.2377179 × 10¹⁸

Minimum	1.1215103 × 10¹⁸
Maximum	4.889045 × 10¹⁸
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 KiB

Quantile statistics

Minimum	1.1215103 × 10¹⁸
5-th percentile	2.7170102 × 10¹⁸
Q1	4.182031 × 10¹⁸
median	4.4180246 × 10¹⁸
Q3	4.6792863 × 10¹⁸
95-th percentile	4.8132768 × 10¹⁸
Maximum	4.889045 × 10¹⁸
Range	3.7675347 × 10¹⁸
Interquartile range (IQR)	4.9725532 × 10¹⁷

Descriptive statistics

Standard deviation	7.4323121 × 10¹⁷
Coefficient of variation (CV)	0.17538478
Kurtosis	7.311128
Mean	4.2377179 × 10¹⁸
Median Absolute Deviation (MAD)	2.5300471 × 10¹⁷
Skewness	-2.6215074
Sum	-1.0066548 × 10¹⁸
Variance	5.5239264 × 10³⁵
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4518011900000510001	2	1.0%
3017011200009080000	2	1.0%
4677025324016130001	2	1.0%
3014011500004650001	2	1.0%
3011011500000680002	2	1.0%
4825010900012640000	2	1.0%
2914011500000490001	2	1.0%
2717010200018560003	2	1.0%
4380031021001170015	1	0.5%
4773044036000570001	1	0.5%
Other values (182)	182	91.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1121510300005460001	1	0.5%
1135010500005890006	1	0.5%
1165010800014460001	1	0.5%
1168010100008310000	1	0.5%
1171010700001500013	1	0.5%
1171010700003200008	1	0.5%
2671025021001240000	1	0.5%
2714010200003280001	1	0.5%
2714010200004810001	1	0.5%
2717010200018560003	2	1.0%

Value	Count	Frequency (%)
4889045023008990005	1	0.5%
4888025024010050000	1	0.5%
4882025025004160002	1	0.5%
4872038021002240014	1	0.5%
4872033026004410031	1	0.5%
4831010900009790002	1	0.5%
4827039021001110019	1	0.5%
4825010900012640000	2	1.0%
4824035021000970002	1	0.5%
4812710600002670000	1	0.5%

PROC_CLSS
Categorical

CONSTANT

Distinct	1
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

1	200

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

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

Common Values

Value	Count	Frequency (%)
1	200	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	200	100.0%

X_AXIS
Real number (ℝ)

Distinct	192
Distinct (%)	96.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	371236.46

Minimum	259130
Maximum	535968
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 KiB

Quantile statistics

Minimum	259130
5-th percentile	274011.3
Q1	318229.75
median	351265.5
Q3	432259.75
95-th percentile	494784.25
Maximum	535968
Range	276838
Interquartile range (IQR)	114030

Descriptive statistics

Standard deviation	70505.442
Coefficient of variation (CV)	0.18992058
Kurtosis	-0.87320849
Mean	371236.46
Median Absolute Deviation (MAD)	53114.5
Skewness	0.42652476
Sum	74247291
Variance	4.9710174 × 10⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
302812	2	1.0%
345841	2	1.0%
321167	2	1.0%
345249	2	1.0%
349711	2	1.0%
479594	2	1.0%
298151	2	1.0%
450317	2	1.0%
431816	1	0.5%
432104	1	0.5%
Other values (182)	182	91.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
259130	1	0.5%
261255	1	0.5%
261794	1	0.5%
263893	1	0.5%
267888	1	0.5%
269050	1	0.5%
269191	1	0.5%
272961	1	0.5%
273137	1	0.5%
273580	1	0.5%

Value	Count	Frequency (%)
535968	1	0.5%
529831	1	0.5%
525967	1	0.5%
523995	1	0.5%
523301	1	0.5%
510676	1	0.5%
508826	1	0.5%
499581	1	0.5%
498720	1	0.5%
497772	1	0.5%

Y_AXIS
Real number (ℝ)

HIGH CORRELATION

Distinct	192
Distinct (%)	96.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	425622.15

Minimum	201664
Maximum	654421
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 KiB

Quantile statistics

Minimum	201664
5-th percentile	254336.75
Q1	343833.5
median	421704
Q3	514789.75
95-th percentile	580470.45
Maximum	654421
Range	452757
Interquartile range (IQR)	170956.25

Descriptive statistics

Standard deviation	107922.41
Coefficient of variation (CV)	0.2535639
Kurtosis	-0.90383956
Mean	425622.15
Median Absolute Deviation (MAD)	91515
Skewness	-0.13554869
Sum	85124429
Variance	1.1647247 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
322252	2	1.0%
418070	2	1.0%
215368	2	1.0%
412641	2	1.0%
416881	2	1.0%
292611	2	1.0%
285206	2	1.0%
365176	2	1.0%
480141	1	0.5%
427481	1	0.5%
Other values (182)	182	91.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
201664	1	0.5%
206644	1	0.5%
207405	1	0.5%
215368	2	1.0%
219172	1	0.5%
223503	1	0.5%
231322	1	0.5%
237217	1	0.5%
245041	1	0.5%
254826	1	0.5%

Value	Count	Frequency (%)
654421	1	0.5%
617513	1	0.5%
616901	1	0.5%
612947	1	0.5%
612832	1	0.5%
605753	1	0.5%
593750	1	0.5%
585189	1	0.5%
584040	1	0.5%
583785	1	0.5%

EDIT_TERMINAL_NM
Text

Distinct	198
Distinct (%)	99.0%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

Length

Max length	13
Median length	12
Mean length	7.09
Min length	4

Characters and Unicode

Total characters	1418
Distinct characters	148
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

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

Unique

Unique	196 ?
Unique (%)	98.0%

Sample

1st row	동서울고속버스터미널
2nd row	동창공용버스터미널
3rd row	동해시외버스터미널
4th row	두밀리정류소
5th row	두원공대

Value	Count	Frequency (%)
광주종합버스터미널	2	1.0%
남부터미널	2	1.0%
내장산공용버스터미널	1	0.5%
나로도공용터미널	1	0.5%
동서울고속버스터미널	1	0.5%
노원역정류소	1	0.5%
녹동신항정류소	1	0.5%
녹동터미널	1	0.5%
녹전정류소	1	0.5%
논티정류소	1	0.5%
Other values (188)	188	94.0%

Most occurring characters

Value	Count	Frequency (%)
정	117	8.3%
류	113	8.0%
소	93	6.6%
미	84	5.9%
터	79	5.6%
널	79	5.6%
버	75	5.3%
스	75	5.3%
시	44	3.1%
외	40	2.8%
Other values (138)	619	43.7%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	1418	100.0%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
정	117	8.3%
류	113	8.0%
소	93	6.6%
미	84	5.9%
터	79	5.6%
널	79	5.6%
버	75	5.3%
스	75	5.3%
시	44	3.1%
외	40	2.8%
Other values (138)	619	43.7%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	1418	100.0%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
정	117	8.3%
류	113	8.0%
소	93	6.6%
미	84	5.9%
터	79	5.6%
널	79	5.6%
버	75	5.3%
스	75	5.3%
시	44	3.1%
외	40	2.8%
Other values (138)	619	43.7%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	1418	100.0%

Most frequent character per block

Hangul

Value	Count	Frequency (%)
정	117	8.3%
류	113	8.0%
소	93	6.6%
미	84	5.9%
터	79	5.6%
널	79	5.6%
버	75	5.3%
스	75	5.3%
시	44	3.1%
외	40	2.8%
Other values (138)	619	43.7%

Phik (φk)
Auto

Heatmap
Table

	BLD_CD	BLK_CD_V4	HOUS_ID	X_AXIS	Y_AXIS
BLD_CD	1.000	0.625	1.000	0.498	0.721
BLK_CD_V4	0.625	1.000	0.533	0.601	0.653
HOUS_ID	1.000	0.533	1.000	0.480	0.710
X_AXIS	0.498	0.601	0.480	1.000	0.467
Y_AXIS	0.721	0.653	0.710	0.467	1.000

Heatmap
Table

	BLD_CD	BLK_CD_V4	HOUS_ID	X_AXIS	Y_AXIS
BLD_CD	1.000	-0.036	1.000	0.205	-0.557
BLK_CD_V4	-0.036	1.000	-0.082	0.149	0.127
HOUS_ID	1.000	-0.082	1.000	0.167	-0.586
X_AXIS	0.205	0.149	0.167	1.000	0.154
Y_AXIS	-0.557	0.127	-0.586	0.154	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

	TERMINAL_CD	TERMINAL_NM	BLD_CD	EDIT_ADDR	EDIT_NEWADDR	BLK_CD_V4	TERMINAL_CLSS	ROUTE_CNT	ADDRESS	HOUS_ID	PROC_CLSS	X_AXIS	Y_AXIS	EDIT_TERMINAL_NM
0	E00207	동서울고속버스터미널(동서울종합터미널)	1121510300105460001009810	서울특별시 광진구 구의동 546-1번지	서울특별시 광진구 강변역로 50	211864	시외	<NA>	서울특별시 광진구 구의동 546-1	1121510300005460001	1	320140	548421	동서울고속버스터미널
1	E00209	동창공용버스터미널(세지정류소)	4617031021107270173097938	전라남도 나주시 세지면 오봉리 727-173번지	전라남도 나주시 세지면 동창로 142	62753	시외	<NA>	전라남도 나주시 세지면 오봉리 727-173	4617031021007270173	1	285827	258757	동창공용버스터미널
2	E00210	동해시외버스터미널	<NA>	강원도 동해시 천곡동 485-10번지	<NA>	184778	시외	<NA>	강원도 동해시 천곡동 485-10	4217010100004850010	1	497772	547797	동해시외버스터미널
3	E00211	두밀리정류소	4182025026107420000002868	경기도 가평군 가평읍 두밀리 742번지	경기도 가평군 가평읍 태봉두밀로 598	303267	시외	<NA>	경기도 가평군 가평읍 두밀리 742	4182025026007420000	1	350717	578877	두밀리정류소
4	E00212	두원공대	<NA>	경기도 안성시 죽산면 장원리 716번지	<NA>	511317	시외	<NA>	경기도 안성시 죽산면 장원리 716	4155040023007160000	1	348840	496340	두원공대
5	E00213	두촌정류소	4272032024108170001010797	강원도 홍천군 두촌면 자은리 817-1번지	강원도 홍천군 두촌면 자은로 370	307710	시외	<NA>	강원도 홍천군 두촌면 자은리 817-1	4272032024008170001	1	402052	585189	두촌정류소
6	E00214	둔내버스터미널	4273033022100890007010748	강원도 횡성군 둔내면 둔방내리 89-7번지	강원도 횡성군 둔내면 경강로둔방10길 12	418386	시외	<NA>	강원도 횡성군 둔내면 둔방내리 89-7	4273033022000890007	1	419036	545734	둔내버스터미널
7	E00215	둔산시외버스정류소(고속)	3017011200109080000018415	대전광역시 서구 둔산동 908번지	대전광역시 서구 청사로 281	118832	시외	<NA>	대전광역시 서구 둔산2동 908	3017011200009080000	1	345841	418070	둔산시외버스정류소
8	E00216	둔산시외버스정류장	3017011200109080000018415	대전광역시 서구 둔산동 908번지	대전광역시 서구 청사로 281	118832	시외	<NA>	대전광역시 서구 둔산2동 908	3017011200009080000	1	345841	418070	둔산시외버스정류장
9	E00217	둔포정류소	4420036021104770008068879	충청남도 아산시 둔포면 둔포리 477-8번지	충청남도 아산시 둔포면 둔포중앙로 115	441183	시외	<NA>	충청남도 아산시 둔포면 둔포리 477-8	4420036021004770008	1	314559	481407	둔포정류소

	TERMINAL_CD	TERMINAL_NM	BLD_CD	EDIT_ADDR	EDIT_NEWADDR	BLK_CD_V4	TERMINAL_CLSS	ROUTE_CNT	ADDRESS	HOUS_ID	PROC_CLSS	X_AXIS	Y_AXIS	EDIT_TERMINAL_NM
190	E00474	영산포터미널(영산포공용터미널)	4617012800101910000017217	전라남도 나주시 이창동 191번지	전라남도 나주시 예향로 3803	63733	시외	<NA>	전라남도 나주시 이창동 191	4617012800001910000	1	282691	266986	영산포터미널
191	E00475	영암고속터미널(영암버스터미널)	4683025025100040001044503	전라남도 영암군 영암읍 남풍리 4-1번지	전라남도 영암군 영암읍 동문로 8	68200	시외	<NA>	전라남도 영암군 영암읍 남풍리 4-1	4683025025000040001	1	281492	245041	영암고속터미널
192	E00477	영월시외버스터미널	4275025022101870006018617	강원도 영월군 영월읍 하송리 187-1번지	강원도 영월군 영월읍 중앙1로 23	68035	시외	<NA>	강원도 영월군 영월읍 하송리 187-1	4275025022001870001	1	441506	509125	영월시외버스터미널
193	E00482	영해버스정류장	4777036030106370001028935	경상북도 영덕군 영해면 성내리 637-1번지	경상북도 영덕군 영해면 예주시장길 5	337756	시외	<NA>	경상북도 영덕군 영해면 성내리 637-1	4777036030006370001	1	525967	438433	영해버스정류장
194	E00483	예미정류소	4277025921106910004002482	강원도 정선군 신동읍 예미리 691-4번지	강원도 정선군 신동읍 의림로 286	187222	시외	<NA>	강원도 정선군 신동읍 예미리 691-4	4277025921006910004	1	457383	513025	예미정류소
195	E00485	예천시외버스공용정류장(예천버스터미널)	4790025027100650002049512	경상북도 예천군 예천읍 대심리 66-1번지	경상북도 예천군 예천읍 충효로 165	442748	시외	<NA>	경상북도 예천군 예천읍 대심리 66-1	4790025027000660001	1	439826	449785	예천시외버스공용정류장
196	E00486	오산시외버스터미널	<NA>	경기도 오산시 오산동 603-1번지	<NA>	141753	시외	<NA>	경기도 오산시 오산동 603-1	4137010100006030001	1	317335	506078	오산시외버스터미널
197	E00488	오수공용버스터미널(오수공용정류장)	4575035521103620001127739	전라북도 임실군 오수면 오수리 362-1번지	전라북도 임실군 오수면 오수로 173	325008	시외	<NA>	전라북도 임실군 오수면 오수리 362-1	4575035521003620001	1	339124	326892	오수공용버스터미널
198	E00489	오음리정류소	<NA>	강원도 화천군 간동면 오음리 612-9번지	<NA>	309149	시외	<NA>	강원도 화천군 간동면 오음리 612-9	4279031024006120009	1	384153	605753	오음리정류소
199	E00490	오창시외버스정류소	4371025345008210004004630	충청북도 청주시 청원구 오창읍 양청리 821-4번지	충청북도 청주시 청원구 오창읍 중심상업로 7	442760	시외	<NA>	충청북도 청주시 청원구 오창읍 중심상업로 7	4311425345008210004	1	349154	456841	오창시외버스정류소

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

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

Most occurring characters

Most occurring categories

Most frequent character per category

Other Letter

Decimal Number

Space Separator

Dash Punctuation

Other Punctuation

Most occurring scripts

Most frequent character per script

Hangul

Common

Most occurring blocks

Most frequent character per block

ASCII

Hangul

None

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

Most occurring scripts

Most frequent character per script

Hangul

Common

Most occurring blocks

Most frequent character per block

ASCII

Hangul

Common Values

Length