gimi9 Pandas Profiling

Dataset statistics

Number of variables	14
Number of observations	64
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	7.5 KiB
Average record size in memory	120.1 B

Variable types

Numeric	7
Text	4
Categorical	3

Dataset

Description	Sample
Author	오픈메이트
URL	https://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=OPMSUBWAY0000013FREE

Alerts

`서울특별시` has constant value ""	Constant
`서울3호선` is highly overall correlated with `296` and 3 other fields	High correlation
`서울교통공사` is highly overall correlated with `296` and 2 other fields	High correlation
`296` is highly overall correlated with `서울교통공사` and 1 other fields	High correlation
`316657` is highly overall correlated with `543608` and 2 other fields	High correlation
`543608` is highly overall correlated with `316657` and 2 other fields	High correlation
`8476` is highly overall correlated with `서울3호선`	High correlation
`1168011800003390002` is highly overall correlated with `316657` and 4 other fields	High correlation
`1168011800103390002000001` is highly overall correlated with `316657` and 2 other fields	High correlation
`296` has unique values	Unique

Reproduction

Analysis started	2023-12-10 06:41:48.148368
Analysis finished	2023-12-10 06:42:01.435514
Duration	13.29 seconds
Software version	ydata-profiling vv4.5.1
Download configuration	config.json

296
Real number (ℝ)

HIGH CORRELATION UNIQUE

Distinct	64
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	485.6875

Minimum	60
Maximum	1048
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	708.0 B

Quantile statistics

Minimum	60
5-th percentile	63.15
Q1	288.75
median	336.5
Q3	656.25
95-th percentile	1044.85
Maximum	1048
Range	988
Interquartile range (IQR)	367.5

Descriptive statistics

Standard deviation	330.53515
Coefficient of variation (CV)	0.68055108
Kurtosis	-1.045635
Mean	485.6875
Median Absolute Deviation (MAD)	270
Skewness	0.48767683
Sum	31084
Variance	109253.49
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
298	1	1.6%
335	1	1.6%
441	1	1.6%
338	1	1.6%
964	1	1.6%
650	1	1.6%
1048	1	1.6%
648	1	1.6%
242	1	1.6%
311	1	1.6%
Other values (54)	54	84.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
60	1	1.6%
61	1	1.6%
62	1	1.6%
63	1	1.6%
64	1	1.6%
65	1	1.6%
66	1	1.6%
67	1	1.6%
68	1	1.6%
69	1	1.6%

Value	Count	Frequency (%)
1048	1	1.6%
1047	1	1.6%
1046	1	1.6%
1045	1	1.6%
1044	1	1.6%
1043	1	1.6%
1042	1	1.6%
1041	1	1.6%
964	1	1.6%
963	1	1.6%

도곡
Text

Distinct	56
Distinct (%)	87.5%
Missing	0
Missing (%)	0.0%
Memory size	644.0 B

Length

Max length	8
Median length	2
Mean length	2.84375
Min length	2

Characters and Unicode

Total characters	182
Distinct characters	88
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	49 ?
Unique (%)	76.6%

Sample

1st row	학여울
2nd row	신사
3rd row	도곡
4th row	까치산
5th row	매봉

Value	Count	Frequency (%)
김포공항	3	4.7%
강남구청	2	3.1%
수서	2	3.1%
강남	2	3.1%
선정릉	2	3.1%
선릉	2	3.1%
송정	2	3.1%
역삼	1	1.6%
우장산	1	1.6%
화곡	1	1.6%
Other values (46)	46	71.9%

Most occurring characters

Value	Count	Frequency (%)
정	6	3.3%
화	6	3.3%
구	6	3.3%
산	6	3.3%
공	5	2.7%
삼	5	2.7%
청	4	2.2%
곡	4	2.2%
양	4	2.2%
릉	4	2.2%
Other values (78)	132	72.5%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	178	97.8%
Decimal Number	3	1.6%
Other Punctuation	1	0.5%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
정	6	3.4%
화	6	3.4%
구	6	3.4%
산	6	3.4%
공	5	2.8%
삼	5	2.8%
청	4	2.2%
곡	4	2.2%
양	4	2.2%
릉	4	2.2%
Other values (74)	128	71.9%

Decimal Number

Value	Count	Frequency (%)
1	1	33.3%
9	1	33.3%
4	1	33.3%

Other Punctuation

Value	Count	Frequency (%)
.	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	178	97.8%
Common	4	2.2%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
정	6	3.4%
화	6	3.4%
구	6	3.4%
산	6	3.4%
공	5	2.8%
삼	5	2.8%
청	4	2.2%
곡	4	2.2%
양	4	2.2%
릉	4	2.2%
Other values (74)	128	71.9%

Common

Value	Count	Frequency (%)
.	1	25.0%
1	1	25.0%
9	1	25.0%
4	1	25.0%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	178	97.8%
ASCII	4	2.2%

Most frequent character per block

Hangul

Value	Count	Frequency (%)
정	6	3.4%
화	6	3.4%
구	6	3.4%
산	6	3.4%
공	5	2.8%
삼	5	2.8%
청	4	2.2%
곡	4	2.2%
양	4	2.2%
릉	4	2.2%
Other values (74)	128	71.9%

ASCII

Value	Count	Frequency (%)
.	1	25.0%
1	1	25.0%
9	1	25.0%
4	1	25.0%

316657
Real number (ℝ)

HIGH CORRELATION

Distinct	56
Distinct (%)	87.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	309399.44

Minimum	294043
Maximum	320768
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	708.0 B

Quantile statistics

Minimum	294043
5-th percentile	294441.65
Q1	298140.5
median	314085
Q3	316108
95-th percentile	318712.85
Maximum	320768
Range	26725
Interquartile range (IQR)	17967.5

Descriptive statistics

Standard deviation	9216.8549
Coefficient of variation (CV)	0.029789501
Kurtosis	-1.3328833
Mean	309399.44
Median Absolute Deviation (MAD)	2744
Skewness	-0.68826231
Sum	19801564
Variance	84950415
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
294389	3	4.7%
315447	2	3.1%
314276	2	3.1%
320768	2	3.1%
295155	2	3.1%
316108	2	3.1%
315646	2	3.1%
313088	1	1.6%
315388	1	1.6%
315014	1	1.6%
Other values (46)	46	71.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
294043	1	1.6%
294389	3	4.7%
294740	1	1.6%
295108	1	1.6%
295155	2	3.1%
295316	1	1.6%
295647	1	1.6%
296433	1	1.6%
296617	1	1.6%
297378	1	1.6%

Value	Count	Frequency (%)
320768	2	3.1%
319225	1	1.6%
318797	1	1.6%
318236	1	1.6%
318113	1	1.6%
317604	1	1.6%
317379	1	1.6%
317362	1	1.6%
317175	1	1.6%
317001	1	1.6%

543608
Real number (ℝ)

HIGH CORRELATION

Distinct	55
Distinct (%)	85.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	549669.53

Minimum	542829
Maximum	562747
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	708.0 B

Quantile statistics

Minimum	542829
5-th percentile	543182.45
Q1	545127
median	548019
Q3	552288.75
95-th percentile	560316.8
Maximum	562747
Range	19918
Interquartile range (IQR)	7161.75

Descriptive statistics

Standard deviation	5623.4283
Coefficient of variation (CV)	0.010230562
Kurtosis	-0.45740975
Mean	549669.53
Median Absolute Deviation (MAD)	3755
Skewness	0.75998866
Sum	35178850
Variance	31622946
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
543182	3	4.7%
551774	3	4.7%
546542	2	3.1%
544442	2	3.1%
545837	2	3.1%
545127	2	3.1%
551689	2	3.1%
549432	1	1.6%
546210	1	1.6%
562747	1	1.6%
Other values (45)	45	70.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
542829	1	1.6%
543182	3	4.7%
543185	1	1.6%
543419	1	1.6%
543608	1	1.6%
543668	1	1.6%
543904	1	1.6%
544011	1	1.6%
544207	1	1.6%
544243	1	1.6%

Value	Count	Frequency (%)
562747	1	1.6%
561990	1	1.6%
561249	1	1.6%
560384	1	1.6%
559936	1	1.6%
559520	1	1.6%
558732	1	1.6%
558681	1	1.6%
558130	1	1.6%
558006	1	1.6%

8614
Real number (ℝ)

Distinct	54
Distinct (%)	84.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	223327.44

Minimum	8614
Maximum	508825
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	708.0 B

Quantile statistics

Minimum	8614
5-th percentile	14569
Q1	31965
median	267957
Q3	338456.5
95-th percentile	419443.75
Maximum	508825
Range	500211
Interquartile range (IQR)	306491.5

Descriptive statistics

Standard deviation	148885.61
Coefficient of variation (CV)	0.66666958
Kurtosis	-0.97137195
Mean	223327.44
Median Absolute Deviation (MAD)	82565
Skewness	-0.10314808
Sum	14292956
Variance	2.2166925 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
270896	3	4.7%
508825	3	4.7%
31206	2	3.1%
142099	2	3.1%
14569	2	3.1%
270951	2	3.1%
350522	2	3.1%
350504	2	3.1%
24515	1	1.6%
215887	1	1.6%
Other values (44)	44	68.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
8614	1	1.6%
11968	1	1.6%
14557	1	1.6%
14569	2	3.1%
14839	1	1.6%
16192	1	1.6%
16484	1	1.6%
16835	1	1.6%
16887	1	1.6%
17357	1	1.6%

Value	Count	Frequency (%)
508825	3	4.7%
420271	1	1.6%
414756	1	1.6%
414556	1	1.6%
414237	1	1.6%
414023	1	1.6%
412914	1	1.6%
364689	1	1.6%
359066	1	1.6%
350522	2	3.1%

서울특별시
Categorical

CONSTANT

Distinct	1
Distinct (%)	1.6%
Missing	0
Missing (%)	0.0%
Memory size	644.0 B

서울특별시	64

Length

Max length	5
Median length	5
Mean length	5
Min length	5

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

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

Common Values

Value	Count	Frequency (%)
서울특별시	64	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
서울특별시	64	100.0%

서울교통공사
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	7.8%
Missing	0
Missing (%)	0.0%
Memory size	644.0 B

서울교통공사	43
KORAIL	11
우이신설경전철	8
코레일공항철도	1
네오트랜스	1

Length

Max length	7
Median length	6
Mean length	6.125
Min length	5

Unique

Unique	2 ?
Unique (%)	3.1%

Sample

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

Common Values

Value	Count	Frequency (%)
서울교통공사	43	67.2%
KORAIL	11	17.2%
우이신설경전철	8	12.5%
코레일공항철도	1	1.6%
네오트랜스	1	1.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
서울교통공사	43	67.2%
korail	11	17.2%
우이신설경전철	8	12.5%
코레일공항철도	1	1.6%
네오트랜스	1	1.6%

서울3호선
Categorical

HIGH CORRELATION

Distinct	11
Distinct (%)	17.2%
Missing	0
Missing (%)	0.0%
Memory size	644.0 B

서울9호선	15
분당선	10
서울5호선	9
서울3호선	8
우이신설경전철	8
Other values (6)	14

Length

Max length	7
Median length	5
Mean length	4.875
Min length	3

Unique

Unique	3 ?
Unique (%)	4.7%

Sample

1st row	서울3호선
2nd row	서울3호선
3rd row	분당선
4th row	서울5호선
5th row	서울3호선

Common Values

Value	Count	Frequency (%)
서울9호선	15	23.4%
분당선	10	15.6%
서울5호선	9	14.1%
서울3호선	8	12.5%
우이신설경전철	8	12.5%
서울2호선	4	6.2%
서울7호선	4	6.2%
서울4호선	3	4.7%
동해선	1	1.6%
공항철도	1	1.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
서울9호선	15	23.4%
분당선	10	15.6%
서울5호선	9	14.1%
서울3호선	8	12.5%
우이신설경전철	8	12.5%
서울2호선	4	6.2%
서울7호선	4	6.2%
서울4호선	3	4.7%
동해선	1	1.6%
공항철도	1	1.6%

8476
Real number (ℝ)

HIGH CORRELATION

Distinct	60
Distinct (%)	93.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	15539.141

Minimum	-99999
Maximum	142563
Zeros	0
Zeros (%)	0.0%
Negative	5
Negative (%)	7.8%
Memory size	708.0 B

Quantile statistics

Minimum	-99999
5-th percentile	-99999
Q1	5207.75
median	15103
Q3	32703.25
95-th percentile	76041.9
Maximum	142563
Range	242562
Interquartile range (IQR)	27495.5

Descriptive statistics

Standard deviation	41756.62
Coefficient of variation (CV)	2.6871898
Kurtosis	3.8537026
Mean	15539.141
Median Absolute Deviation (MAD)	11462
Skewness	-1.0068858
Sum	994505
Variance	1.7436153 × 10⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-99999	5	7.8%
81867	1	1.6%
12856	1	1.6%
3605	1	1.6%
26341	1	1.6%
45304	1	1.6%
13069	1	1.6%
4020	1	1.6%
29296	1	1.6%
79242	1	1.6%
Other values (50)	50	78.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-99999	5	7.8%
2089	1	1.6%
2494	1	1.6%
3197	1	1.6%
3204	1	1.6%
3553	1	1.6%
3605	1	1.6%
3677	1	1.6%
4020	1	1.6%
4090	1	1.6%

Value	Count	Frequency (%)
142563	1	1.6%
82042	1	1.6%
81867	1	1.6%
79242	1	1.6%
57908	1	1.6%
52658	1	1.6%
51797	1	1.6%
51001	1	1.6%
47444	1	1.6%
46978	1	1.6%

서울 강남구 남부순환로 지하 2814
Text

Distinct	56
Distinct (%)	87.5%
Missing	0
Missing (%)	0.0%
Memory size	644.0 B

Length

Max length	20
Median length	18
Mean length	17.078125
Min length	13

Characters and Unicode

Total characters	1093
Distinct characters	61
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	49 ?
Unique (%)	76.6%

Sample

1st row	서울 강남구 남부순환로 지하 3104
2nd row	서울 강남구 도산대로 지하 102
3rd row	서울 강남구 남부순환로 지하 2814
4th row	서울 강서구 강서로 지하 54
5th row	서울 강남구 남부순환로 지하 2744

Value	Count	Frequency (%)
서울	64	20.4%
지하	57	18.2%
강남구	32	10.2%
강서구	21	6.7%
강북구	11	3.5%
삼양로	7	2.2%
공항대로	6	1.9%
학동로	5	1.6%
테헤란로	4	1.3%
봉은사로	4	1.3%
Other values (71)	102	32.6%

Most occurring characters

Value	Count	Frequency (%)
	249	22.8%
서	87	8.0%
강	68	6.2%
구	66	6.0%
울	64	5.9%
로	61	5.6%
하	60	5.5%
지	57	5.2%
남	38	3.5%
2	29	2.7%
Other values (51)	314	28.7%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	660	60.4%
Space Separator	249	22.8%
Decimal Number	184	16.8%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
서	87	13.2%
강	68	10.3%
구	66	10.0%
울	64	9.7%
로	61	9.2%
하	60	9.1%
지	57	8.6%
남	38	5.8%
양	11	1.7%
북	11	1.7%
Other values (40)	137	20.8%

Decimal Number

Value	Count	Frequency (%)
2	29	15.8%
1	25	13.6%
3	22	12.0%
0	22	12.0%
5	18	9.8%
4	16	8.7%
6	15	8.2%
7	13	7.1%
8	13	7.1%
9	11	6.0%

Space Separator

Value	Count	Frequency (%)
	249	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	660	60.4%
Common	433	39.6%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
서	87	13.2%
강	68	10.3%
구	66	10.0%
울	64	9.7%
로	61	9.2%
하	60	9.1%
지	57	8.6%
남	38	5.8%
양	11	1.7%
북	11	1.7%
Other values (40)	137	20.8%

Common

Value	Count	Frequency (%)
	249	57.5%
2	29	6.7%
1	25	5.8%
3	22	5.1%
0	22	5.1%
5	18	4.2%
4	16	3.7%
6	15	3.5%
7	13	3.0%
8	13	3.0%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	660	60.4%
ASCII	433	39.6%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	249	57.5%
2	29	6.7%
1	25	5.8%
3	22	5.1%
0	22	5.1%
5	18	4.2%
4	16	3.7%
6	15	3.5%
7	13	3.0%
8	13	3.0%

Hangul

Value	Count	Frequency (%)
서	87	13.2%
강	68	10.3%
구	66	10.0%
울	64	9.7%
로	61	9.2%
하	60	9.1%
지	57	8.6%
남	38	5.8%
양	11	1.7%
북	11	1.7%
Other values (40)	137	20.8%

1168011800003390002
Real number (ℝ)

HIGH CORRELATION

Distinct	54
Distinct (%)	84.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.155659 × 10¹⁸

Minimum	1.1305101 × 10¹⁸
Maximum	1.1680118 × 10¹⁸
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	708.0 B

Quantile statistics

Minimum	1.1305101 × 10¹⁸
5-th percentile	1.1305101 × 10¹⁸
Q1	1.1500103 × 10¹⁸
median	1.1590106 × 10¹⁸
Q3	1.1680105 × 10¹⁸
95-th percentile	1.1680115 × 10¹⁸
Maximum	1.1680118 × 10¹⁸
Range	3.75017 × 10¹⁶
Interquartile range (IQR)	1.8000225 × 10¹⁶

Descriptive statistics

Standard deviation	1.4091055 × 10¹⁶
Coefficient of variation (CV)	0.01219309
Kurtosis	-0.86043687
Mean	1.155659 × 10¹⁸
Median Absolute Deviation (MAD)	9.0001 × 10¹⁵
Skewness	-0.69364056
Sum	1.7520211 × 10¹⁷
Variance	1.9855783 × 10³²
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1168010500001720066	3	4.7%
1150010900008860000	3	4.7%
1168010800002790067	2	3.1%
1168011500007280000	2	3.1%
1150010800000290005	2	3.1%
1168010500001110044	2	3.1%
1168010500001110114	2	3.1%
1168010100008580000	2	3.1%
1168011000004950000	1	1.6%
1130510400000160027	1	1.6%
Other values (44)	44	68.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1130510100000660001	1	1.6%
1130510100001940001	1	1.6%
1130510100007912244	1	1.6%
1130510100007914755	1	1.6%
1130510100013530029	1	1.6%
1130510300001400000	1	1.6%
1130510300003710001	1	1.6%
1130510300004720678	1	1.6%
1130510400000160027	1	1.6%
1130510400000570018	1	1.6%

Value	Count	Frequency (%)
1168011800003390002	1	1.6%
1168011800001790002	1	1.6%
1168011500007280000	2	3.1%
1168011400007170000	1	1.6%
1168011400007000009	1	1.6%
1168011400007000001	1	1.6%
1168011000004950000	1	1.6%
1168010800002790165	1	1.6%
1168010800002790067	2	3.1%
1168010700006680000	1	1.6%

1168011800103390002000001
Real number (ℝ)

HIGH CORRELATION

Distinct	47
Distinct (%)	73.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.155659 × 10²⁴

Minimum	1.1305101 × 10²⁴
Maximum	1.1680118 × 10²⁴
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	708.0 B

Quantile statistics

Minimum	1.1305101 × 10²⁴
5-th percentile	1.1305101 × 10²⁴
Q1	1.1500103 × 10²⁴
median	1.1590106 × 10²⁴
Q3	1.1680106 × 10²⁴
95-th percentile	1.1680115 × 10²⁴
Maximum	1.1680118 × 10²⁴
Range	3.75017 × 10²²
Interquartile range (IQR)	1.80003 × 10²²

Descriptive statistics

Standard deviation	1.4091059 × 10²²
Coefficient of variation (CV)	0.012193094
Kurtosis	-0.86043877
Mean	1.155659 × 10²⁴
Median Absolute Deviation (MAD)	9.00015 × 10²¹
Skewness	-0.69363954
Sum	7.3962178 × 10²⁵
Variance	1.9855795 × 10⁴⁴
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=47)

Value	Count	Frequency (%)
1.16801050010111e+24	5	7.8%
1.16801010010804e+24	5	7.8%
1.15001090010886e+24	3	4.7%
1.16801080010279e+24	3	4.7%
1.168011400107e+24	2	3.1%
1.16801050010172e+24	2	3.1%
1.15001080010029e+24	2	3.1%
1.16801150010728e+24	2	3.1%
1.15001020010666e+24	2	3.1%
1.15001050010367e+24	1	1.6%
Other values (37)	37	57.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1.13051010010066e+24	1	1.6%
1.13051010010194e+24	1	1.6%
1.1305101001079122e+24	1	1.6%
1.1305101001079149e+24	1	1.6%
1.13051010011353e+24	1	1.6%
1.1305103001014e+24	1	1.6%
1.13051030010371e+24	1	1.6%
1.1305103001047206e+24	1	1.6%
1.13051040010016e+24	1	1.6%
1.13051040010057e+24	1	1.6%

Value	Count	Frequency (%)
1.16801180010339e+24	1	1.6%
1.16801180010179e+24	1	1.6%
1.16801150010728e+24	2	3.1%
1.16801140010717e+24	1	1.6%
1.168011400107e+24	2	3.1%
1.16801100010495e+24	1	1.6%
1.16801100010435e+24	1	1.6%
1.1680108001028e+24	1	1.6%
1.16801080010279e+24	3	4.7%
1.16801070010667e+24	1	1.6%

서울특별시 강남구 도곡동 339-2번지
Text

Distinct	54
Distinct (%)	84.4%
Missing	0
Missing (%)	0.0%
Memory size	644.0 B

Length

Max length	24
Median length	23
Mean length	21.03125
Min length	19

Characters and Unicode

Total characters	1346
Distinct characters	61
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	46 ?
Unique (%)	71.9%

Sample

1st row	서울특별시 강남구 대치동 514-3번지
2nd row	서울특별시 강남구 신사동 667번지
3rd row	서울특별시 강남구 도곡동 339-2번지
4th row	서울특별시 강서구 화곡동 662-5번지
5th row	서울특별시 강남구 도곡동 179-2번지

Value	Count	Frequency (%)
서울특별시	64	25.0%
강남구	32	12.5%
강서구	21	8.2%
강북구	11	4.3%
삼성동	9	3.5%
방화동	6	2.3%
미아동	5	2.0%
역삼동	4	1.6%
공항동	3	1.2%
대치동	3	1.2%
Other values (70)	98	38.3%

Most occurring characters

Value	Count	Frequency (%)
	192	14.3%
서	87	6.5%
구	65	4.8%
특	64	4.8%
별	64	4.8%
시	64	4.8%
강	64	4.8%
지	64	4.8%
번	64	4.8%
동	64	4.8%
Other values (51)	554	41.2%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	834	62.0%
Decimal Number	274	20.4%
Space Separator	192	14.3%
Dash Punctuation	46	3.4%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
서	87	10.4%
구	65	7.8%
특	64	7.7%
별	64	7.7%
시	64	7.7%
강	64	7.7%
지	64	7.7%
번	64	7.7%
동	64	7.7%
울	64	7.7%
Other values (39)	170	20.4%

Decimal Number

Value	Count	Frequency (%)
1	56	20.4%
6	37	13.5%
7	37	13.5%
2	28	10.2%
8	25	9.1%
4	25	9.1%
9	21	7.7%
5	18	6.6%
0	14	5.1%
3	13	4.7%

Space Separator

Value	Count	Frequency (%)
	192	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	46	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	834	62.0%
Common	512	38.0%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
서	87	10.4%
구	65	7.8%
특	64	7.7%
별	64	7.7%
시	64	7.7%
강	64	7.7%
지	64	7.7%
번	64	7.7%
동	64	7.7%
울	64	7.7%
Other values (39)	170	20.4%

Common

Value	Count	Frequency (%)
	192	37.5%
1	56	10.9%
-	46	9.0%
6	37	7.2%
7	37	7.2%
2	28	5.5%
8	25	4.9%
4	25	4.9%
9	21	4.1%
5	18	3.5%
Other values (2)	27	5.3%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	834	62.0%
ASCII	512	38.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	192	37.5%
1	56	10.9%
-	46	9.0%
6	37	7.2%
7	37	7.2%
2	28	5.5%
8	25	4.9%
4	25	4.9%
9	21	4.1%
5	18	3.5%
Other values (2)	27	5.3%

Hangul

Value	Count	Frequency (%)
서	87	10.4%
구	65	7.8%
특	64	7.7%
별	64	7.7%
시	64	7.7%
강	64	7.7%
지	64	7.7%
번	64	7.7%
동	64	7.7%
울	64	7.7%
Other values (39)	170	20.4%

서울특별시 강남구 남부순환로 지하 2814
Text

Distinct	56
Distinct (%)	87.5%
Missing	0
Missing (%)	0.0%
Memory size	644.0 B

Length

Max length	23
Median length	21
Mean length	20.078125
Min length	16

Characters and Unicode

Total characters	1285
Distinct characters	64
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	49 ?
Unique (%)	76.6%

Sample

1st row	서울특별시 강남구 남부순환로 지하 3104
2nd row	서울특별시 강남구 도산대로 지하 102
3rd row	서울특별시 강남구 남부순환로 지하 2814
4th row	서울특별시 강서구 강서로 지하 54
5th row	서울특별시 강남구 남부순환로 지하 2744

Value	Count	Frequency (%)
서울특별시	64	20.4%
지하	57	18.2%
강남구	32	10.2%
강서구	21	6.7%
강북구	11	3.5%
삼양로	7	2.2%
공항대로	6	1.9%
학동로	5	1.6%
테헤란로	4	1.3%
봉은사로	4	1.3%
Other values (71)	102	32.6%

Most occurring characters

Value	Count	Frequency (%)
	249	19.4%
서	87	6.8%
강	68	5.3%
구	66	5.1%
울	64	5.0%
시	64	5.0%
별	64	5.0%
특	64	5.0%
로	61	4.7%
하	60	4.7%
Other values (54)	438	34.1%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	852	66.3%
Space Separator	249	19.4%
Decimal Number	184	14.3%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
서	87	10.2%
강	68	8.0%
구	66	7.7%
울	64	7.5%
시	64	7.5%
별	64	7.5%
특	64	7.5%
로	61	7.2%
하	60	7.0%
지	57	6.7%
Other values (43)	197	23.1%

Decimal Number

Value	Count	Frequency (%)
2	29	15.8%
1	25	13.6%
0	22	12.0%
3	22	12.0%
5	18	9.8%
4	16	8.7%
6	15	8.2%
8	13	7.1%
7	13	7.1%
9	11	6.0%

Space Separator

Value	Count	Frequency (%)
	249	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	852	66.3%
Common	433	33.7%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
서	87	10.2%
강	68	8.0%
구	66	7.7%
울	64	7.5%
시	64	7.5%
별	64	7.5%
특	64	7.5%
로	61	7.2%
하	60	7.0%
지	57	6.7%
Other values (43)	197	23.1%

Common

Value	Count	Frequency (%)
	249	57.5%
2	29	6.7%
1	25	5.8%
0	22	5.1%
3	22	5.1%
5	18	4.2%
4	16	3.7%
6	15	3.5%
8	13	3.0%
7	13	3.0%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	852	66.3%
ASCII	433	33.7%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	249	57.5%
2	29	6.7%
1	25	5.8%
0	22	5.1%
3	22	5.1%
5	18	4.2%
4	16	3.7%
6	15	3.5%
8	13	3.0%
7	13	3.0%

Hangul

Value	Count	Frequency (%)
서	87	10.2%
강	68	8.0%
구	66	7.7%
울	64	7.5%
시	64	7.5%
별	64	7.5%
특	64	7.5%
로	61	7.2%
하	60	7.0%
지	57	6.7%
Other values (43)	197	23.1%

Heatmap
Table

	296	도곡	316657	543608	8614	서울교통공사	서울3호선	8476	서울 강남구 남부순환로 지하 2814	1168011800003390002	1168011800103390002000001	서울특별시 강남구 도곡동 339-2번지	서울특별시 강남구 남부순환로 지하 2814
296	1.000	0.000	0.540	0.554	0.655	0.860	0.954	0.706	0.000	0.724	0.724	0.000	0.000
도곡	0.000	1.000	1.000	1.000	1.000	0.000	0.000	0.856	1.000	1.000	1.000	1.000	1.000
316657	0.540	1.000	1.000	0.816	0.685	0.379	0.711	0.212	1.000	0.974	0.974	1.000	1.000
543608	0.554	1.000	0.816	1.000	0.663	0.571	0.683	0.342	1.000	1.000	1.000	1.000	1.000
8614	0.655	1.000	0.685	0.663	1.000	0.654	0.673	0.520	1.000	0.860	0.860	1.000	1.000
서울교통공사	0.860	0.000	0.379	0.571	0.654	1.000	1.000	0.126	0.000	0.674	0.674	0.000	0.000
서울3호선	0.954	0.000	0.711	0.683	0.673	1.000	1.000	0.869	0.000	0.942	0.942	0.000	0.000
8476	0.706	0.856	0.212	0.342	0.520	0.126	0.869	1.000	0.856	0.137	0.137	0.875	0.856
서울 강남구 남부순환로 지하 2814	0.000	1.000	1.000	1.000	1.000	0.000	0.000	0.856	1.000	1.000	1.000	1.000	1.000
1168011800003390002	0.724	1.000	0.974	1.000	0.860	0.674	0.942	0.137	1.000	1.000	1.000	1.000	1.000
1168011800103390002000001	0.724	1.000	0.974	1.000	0.860	0.674	0.942	0.137	1.000	1.000	1.000	1.000	1.000
서울특별시 강남구 도곡동 339-2번지	0.000	1.000	1.000	1.000	1.000	0.000	0.000	0.875	1.000	1.000	1.000	1.000	1.000
서울특별시 강남구 남부순환로 지하 2814	0.000	1.000	1.000	1.000	1.000	0.000	0.000	0.856	1.000	1.000	1.000	1.000	1.000

Heatmap
Table

	서울3호선	서울교통공사
서울3호선	1.000	0.948
서울교통공사	0.948	1.000

Heatmap
Table

	296	316657	543608	8614	8476	1168011800003390002	1168011800103390002000001	서울교통공사	서울3호선
296	1.000	0.212	0.095	-0.103	-0.480	-0.072	-0.090	0.735	0.841
316657	0.212	1.000	-0.746	0.052	0.061	0.646	0.634	0.265	0.440
543608	0.095	-0.746	1.000	-0.137	-0.176	-0.842	-0.837	0.355	0.390
8614	-0.103	0.052	-0.137	1.000	-0.012	0.110	0.119	0.464	0.384
8476	-0.480	0.061	-0.176	-0.012	1.000	0.121	0.123	0.182	0.503
1168011800003390002	-0.072	0.646	-0.842	0.110	0.121	1.000	0.983	0.604	0.856
1168011800103390002000001	-0.090	0.634	-0.837	0.119	0.123	0.983	1.000	0.000	0.000
서울교통공사	0.735	0.265	0.355	0.464	0.182	0.604	0.000	1.000	0.948
서울3호선	0.841	0.440	0.390	0.384	0.503	0.856	0.000	0.948	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

	296	도곡	316657	543608	8614	서울특별시	서울교통공사	서울3호선	8476	서울 강남구 남부순환로 지하 2814	1168011800003390002	1168011800103390002000001	서울특별시 강남구 도곡동 339-2번지	서울특별시 강남구 남부순환로 지하 2814
0	298	학여울	318113	544243	274478	서울특별시	서울교통공사	서울3호선	3204	서울 강남구 남부순환로 지하 3104	1168010600005140003	1168010600105140003000001	서울특별시 강남구 대치동 514-3번지	서울특별시 강남구 남부순환로 지하 3104
1	289	신사	313592	546477	27192	서울특별시	서울교통공사	서울3호선	51001	서울 강남구 도산대로 지하 102	1168010700006670000	1168010700106670000000001	서울특별시 강남구 신사동 667번지	서울특별시 강남구 도산대로 지하 102
2	653	도곡	316657	543608	8614	서울특별시	KORAIL	분당선	10389	서울 강남구 남부순환로 지하 2814	1168011800003390002	1168011800103390002000001	서울특별시 강남구 도곡동 339-2번지	서울특별시 강남구 남부순환로 지하 2814
3	339	까치산	298256	548374	16192	서울특별시	서울교통공사	서울5호선	47444	서울 강서구 강서로 지하 54	1150010300006620005	1150010300106620005000001	서울특별시 강서구 화곡동 662-5번지	서울특별시 강서구 강서로 지하 54
4	295	매봉	315882	543182	420271	서울특별시	서울교통공사	서울3호선	17888	서울 강남구 남부순환로 지하 2744	1168011800001790002	1168011800101790002000001	서울특별시 강남구 도곡동 179-2번지	서울특별시 강남구 남부순환로 지하 2744
5	299	대청	318797	543904	281000	서울특별시	서울교통공사	서울3호선	14884	서울 강남구 일원로 지하 2	1168011400007000009	1168011400107000009000001	서울특별시 강남구 일원동 700-9번지	서울특별시 강남구 일원로 지하 2
6	1047	솔밭공원	313115	561990	221003	서울특별시	우이신설경전철	우이신설경전철	3553	서울 강북구 삼양로 595	1130510400000570018	1130510400100570018004087	서울특별시 강북구 우이동 57-18번지	서울특별시 강북구 삼양로 595
7	654	구룡	317001	543185	24597	서울특별시	KORAIL	분당선	2494	서울 강남구 개포로 지하 403	1168010300001750003	1168010300101750003021083	서울특별시 강남구 개포동 175-3번지	서울특별시 강남구 개포로 지하 403
8	651	선릉	316108	545127	270896	서울특별시	KORAIL	분당선	38227	서울 강남구 테헤란로 지하 340	1168010500001720066	1168010100108040000000003	서울특별시 강남구 삼성동 172-66번지	서울특별시 강남구 테헤란로 지하 340
9	336	발산	297471	551388	414556	서울특별시	서울교통공사	서울5호선	30536	서울 강서구 공항대로 지하 267	1150010500007271496	1150010400109670003000001	서울특별시 강서구 마곡동 727-1496번지	서울특별시 강서구 공항대로 지하 267

	296	도곡	316657	543608	8614	서울특별시	서울교통공사	서울3호선	8476	서울 강남구 남부순환로 지하 2814	1168011800003390002	1168011800103390002000001	서울특별시 강남구 도곡동 339-2번지	서울특별시 강남구 남부순환로 지하 2814
54	332	개화산	294740	552893	16887	서울특별시	서울교통공사	서울5호선	8666	서울 강서구 양천로 22	1150010900008460000	1150010900108460000001473	서울특별시 강서구 방화동 846번지	서울특별시 강서구 양천로 22
55	1045	가오리	313438	560384	216345	서울특별시	우이신설경전철	우이신설경전철	6020	서울 강북구 삼양로 426	1130510300003710001	1130510300103710001000001	서울특별시 강북구 수유동 371-1번지	서울특별시 강북구 삼양로 426
56	442	학동	314574	546220	31206	서울특별시	서울교통공사	서울7호선	37418	서울 강남구 학동로 지하 180	1168010800002790067	1168010800102790101000001	서울특별시 강남구 논현동 279-67번지	서울특별시 강남구 학동로 지하 180
57	61	김포공항	294389	551774	508825	서울특별시	서울교통공사	서울9호선	15322	서울 강서구 하늘길 지하 77	1150010900008860000	1150010900108860000000002	서울특별시 강서구 방화동 886번지	서울특별시 강서구 하늘길 지하 77
58	297	대치	317379	544011	273279	서울특별시	서울교통공사	서울3호선	17454	서울 강남구 남부순환로 지하 2952	1168010600003170003	1168010600103170003000001	서울특별시 강남구 대치동 317-3번지	서울특별시 강남구 남부순환로 지하 2952
59	243	강남	314276	544442	350504	서울특별시	서울교통공사	서울2호선	142563	서울 강남구 강남대로 지하 396	1168010100008580000	1168010100108040000000001	서울특별시 강남구 역삼동 858번지	서울특별시 강남구 강남대로 지하 396
60	66	가양	298983	551650	16484	서울특별시	서울교통공사	서울9호선	32693	서울 강서구 양천로 지하 485	1150010400000140061	1150010400100140061000001	서울특별시 강서구 가양동 14-61번지	서울특별시 강서구 양천로 지하 485
61	652	한티	316447	544207	265703	서울특별시	KORAIL	분당선	22691	서울 강남구 선릉로 지하 228	1168010600010110028	1168010600110110028000001	서울특별시 강남구 대치동 1011-28번지	서울특별시 강남구 선릉로 지하 228
62	1042	삼양사거리	313705	558130	220348	서울특별시	우이신설경전철	우이신설경전철	3677	서울 강북구 삼양로 197	1130510100007912244	1130510100107912244034713	서울특별시 강북구 미아동 791-2244번지	서울특별시 강북구 삼양로 197
63	333	김포공항	294389	551774	508825	서울특별시	서울교통공사	서울5호선	11488	서울 강서구 하늘길 지하 77	1150010900008860000	1150010900108860000000002	서울특별시 강서구 방화동 886번지	서울특별시 강서구 하늘길 지하 77

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Other Letter

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Hangul

Common

Most occurring blocks

Most frequent character per block

Hangul

ASCII

Common Values

Length

Common Values (Plot)

Common Values

Length

Common Values (Plot)

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Other Letter

Decimal Number

Space Separator

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

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

Most occurring scripts

Most frequent character per script

Hangul

Common

Most occurring blocks

Most frequent character per block

ASCII

Hangul

Interactions

Correlations

Missing values

Sample