Overview

Dataset statistics

Number of variables7
Number of observations2398
Missing cells2398
Missing cells (%)14.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory143.0 KiB
Average record size in memory61.1 B

Variable types

Numeric4
Text2
Unsupported1

Dataset

Description참고 - 2019년 버스정류장 위치
Author경상남도 창원시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15069002

Alerts

ID is highly overall correlated with 모바일_ID and 1 other fieldsHigh correlation
모바일_ID is highly overall correlated with ID and 1 other fieldsHigh correlation
경도 is highly overall correlated with ID and 1 other fieldsHigh correlation
주소 has 2398 (100.0%) missing valuesMissing
ID has unique valuesUnique
주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 23:19:57.714354
Analysis finished2023-12-10 23:20:00.396383
Duration2.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

ID
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2398
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1199.5
Minimum1
Maximum2398
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2023-12-11T08:20:00.478659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile120.85
Q1600.25
median1199.5
Q31798.75
95-th percentile2278.15
Maximum2398
Range2397
Interquartile range (IQR)1198.5

Descriptive statistics

Standard deviation692.3873
Coefficient of variation (CV)0.57722993
Kurtosis-1.2
Mean1199.5
Median Absolute Deviation (MAD)599.5
Skewness0
Sum2876401
Variance479400.17
MonotonicityStrictly increasing
2023-12-11T08:20:00.656784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1595 1
 
< 0.1%
1597 1
 
< 0.1%
1598 1
 
< 0.1%
1599 1
 
< 0.1%
1600 1
 
< 0.1%
1601 1
 
< 0.1%
1602 1
 
< 0.1%
1603 1
 
< 0.1%
1604 1
 
< 0.1%
Other values (2388) 2388
99.6%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
2398 1
< 0.1%
2397 1
< 0.1%
2396 1
< 0.1%
2395 1
< 0.1%
2394 1
< 0.1%
2393 1
< 0.1%
2392 1
< 0.1%
2391 1
< 0.1%
2390 1
< 0.1%
2389 1
< 0.1%

모바일_ID
Real number (ℝ)

HIGH CORRELATION 

Distinct2397
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean299275.66
Minimum100201
Maximum630373
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2023-12-11T08:20:00.814252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100201
5-th percentile104601.85
Q1119304.25
median307403.5
Q3409907.75
95-th percentile630014.15
Maximum630373
Range530172
Interquartile range (IQR)290603.5

Descriptive statistics

Standard deviation162333.97
Coefficient of variation (CV)0.54242289
Kurtosis-1.0029435
Mean299275.66
Median Absolute Deviation (MAD)186352.5
Skewness0.35393191
Sum7.1766303 × 108
Variance2.6352317 × 1010
MonotonicityIncreasing
2023-12-11T08:20:00.975229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
321411 2
 
0.1%
100201 1
 
< 0.1%
400108 1
 
< 0.1%
400102 1
 
< 0.1%
400103 1
 
< 0.1%
400104 1
 
< 0.1%
400105 1
 
< 0.1%
400106 1
 
< 0.1%
400107 1
 
< 0.1%
400109 1
 
< 0.1%
Other values (2387) 2387
99.5%
ValueCountFrequency (%)
100201 1
< 0.1%
100202 1
< 0.1%
100203 1
< 0.1%
100204 1
< 0.1%
100205 1
< 0.1%
100206 1
< 0.1%
100207 1
< 0.1%
100208 1
< 0.1%
100701 1
< 0.1%
100702 1
< 0.1%
ValueCountFrequency (%)
630373 1
< 0.1%
630372 1
< 0.1%
630362 1
< 0.1%
630361 1
< 0.1%
630360 1
< 0.1%
630359 1
< 0.1%
630358 1
< 0.1%
630357 1
< 0.1%
630356 1
< 0.1%
630355 1
< 0.1%

행정구역
Text

Distinct133
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size18.9 KiB
2023-12-11T08:20:01.385340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.8436197
Min length2

Characters and Unicode

Total characters6819
Distinct characters107
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)0.5%

Sample

1st row동읍
2nd row동읍
3rd row동읍
4th row동읍
5th row대산면
ValueCountFrequency (%)
북면 203
 
8.5%
동읍 154
 
6.4%
내서읍 149
 
6.2%
진전면 110
 
4.6%
구산면 105
 
4.4%
대산면 103
 
4.3%
진북면 94
 
3.9%
팔용동 69
 
2.9%
진동면 63
 
2.6%
용원동 47
 
2.0%
Other values (123) 1301
54.3%
2023-12-11T08:20:01.964660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 1677
24.6%
면 678
 
9.9%
읍 303
 
4.4%
북 300
 
4.4%
산 278
 
4.1%
진 267
 
3.9%
서 193
 
2.8%
내 166
 
2.4%
용 144
 
2.1%
대 140
 
2.1%
Other values (97) 2673
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6790
99.6%
Decimal Number 29
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1677
24.7%
면 678
 
10.0%
읍 303
 
4.5%
북 300
 
4.4%
산 278
 
4.1%
진 267
 
3.9%
서 193
 
2.8%
내 166
 
2.4%
용 144
 
2.1%
대 140
 
2.1%
Other values (92) 2644
38.9%
Decimal Number
ValueCountFrequency (%)
1 10
34.5%
3 8
27.6%
2 8
27.6%
4 2
 
6.9%
5 1
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6790
99.6%
Common 29
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1677
24.7%
면 678
 
10.0%
읍 303
 
4.5%
북 300
 
4.4%
산 278
 
4.1%
진 267
 
3.9%
서 193
 
2.8%
내 166
 
2.4%
용 144
 
2.1%
대 140
 
2.1%
Other values (92) 2644
38.9%
Common
ValueCountFrequency (%)
1 10
34.5%
3 8
27.6%
2 8
27.6%
4 2
 
6.9%
5 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6790
99.6%
ASCII 29
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 1677
24.7%
면 678
 
10.0%
읍 303
 
4.5%
북 300
 
4.4%
산 278
 
4.1%
진 267
 
3.9%
서 193
 
2.8%
내 166
 
2.4%
용 144
 
2.1%
대 140
 
2.1%
Other values (92) 2644
38.9%
ASCII
ValueCountFrequency (%)
1 10
34.5%
3 8
27.6%
2 8
27.6%
4 2
 
6.9%
5 1
 
3.4%

정류장명
Text

Distinct1343
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Memory size18.9 KiB
2023-12-11T08:20:02.390768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length4.9637198
Min length2

Characters and Unicode

Total characters11903
Distinct characters442
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique375 ?
Unique (%)15.6%

Sample

1st row합산
2nd row합산
3rd row용산입구
4th row용산입구
5th row백양마을
ValueCountFrequency (%)
입구 7
 
0.3%
어시장 6
 
0.2%
금산마을 6
 
0.2%
마산시외버스터미널 5
 
0.2%
우성아파트 5
 
0.2%
예곡마을 4
 
0.2%
마산역 4
 
0.2%
세몰마을 4
 
0.2%
이마트 4
 
0.2%
예곡 4
 
0.2%
Other values (1347) 2385
98.0%
2023-12-11T08:20:02.846796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 391
 
3.3%
동 388
 
3.3%
구 290
 
2.4%
원 277
 
2.3%
을 276
 
2.3%
아 273
 
2.3%
트 253
 
2.1%
파 249
 
2.1%
교 238
 
2.0%
산 238
 
2.0%
Other values (432) 9030
75.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11509
96.7%
Decimal Number 158
 
1.3%
Uppercase Letter 107
 
0.9%
Other Punctuation 55
 
0.5%
Space Separator 36
 
0.3%
Close Punctuation 17
 
0.1%
Open Punctuation 15
 
0.1%
Other Symbol 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 391
 
3.4%
동 388
 
3.4%
구 290
 
2.5%
원 277
 
2.4%
을 276
 
2.4%
아 273
 
2.4%
트 253
 
2.2%
파 249
 
2.2%
교 238
 
2.1%
산 238
 
2.1%
Other values (400) 8636
75.0%
Uppercase Letter
ValueCountFrequency (%)
T 24
22.4%
S 22
20.6%
X 14
13.1%
K 8
 
7.5%
G 6
 
5.6%
A 6
 
5.6%
H 6
 
5.6%
L 6
 
5.6%
P 5
 
4.7%
M 2
 
1.9%
Other values (5) 8
 
7.5%
Decimal Number
ValueCountFrequency (%)
1 60
38.0%
2 35
22.2%
3 22
 
13.9%
9 9
 
5.7%
4 9
 
5.7%
6 8
 
5.1%
5 7
 
4.4%
7 5
 
3.2%
8 3
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 49
89.1%
/ 4
 
7.3%
& 1
 
1.8%
, 1
 
1.8%
Space Separator
ValueCountFrequency (%)
36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11515
96.7%
Common 281
 
2.4%
Latin 107
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 391
 
3.4%
동 388
 
3.4%
구 290
 
2.5%
원 277
 
2.4%
을 276
 
2.4%
아 273
 
2.4%
트 253
 
2.2%
파 249
 
2.2%
교 238
 
2.1%
산 238
 
2.1%
Other values (401) 8642
75.0%
Common
ValueCountFrequency (%)
1 60
21.4%
. 49
17.4%
36
12.8%
2 35
12.5%
3 22
 
7.8%
) 17
 
6.0%
( 15
 
5.3%
9 9
 
3.2%
4 9
 
3.2%
6 8
 
2.8%
Other values (6) 21
 
7.5%
Latin
ValueCountFrequency (%)
T 24
22.4%
S 22
20.6%
X 14
13.1%
K 8
 
7.5%
G 6
 
5.6%
A 6
 
5.6%
H 6
 
5.6%
L 6
 
5.6%
P 5
 
4.7%
M 2
 
1.9%
Other values (5) 8
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11509
96.7%
ASCII 388
 
3.3%
None 6
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 391
 
3.4%
동 388
 
3.4%
구 290
 
2.5%
원 277
 
2.4%
을 276
 
2.4%
아 273
 
2.4%
트 253
 
2.2%
파 249
 
2.2%
교 238
 
2.1%
산 238
 
2.1%
Other values (400) 8636
75.0%
ASCII
ValueCountFrequency (%)
1 60
15.5%
. 49
12.6%
36
 
9.3%
2 35
 
9.0%
T 24
 
6.2%
3 22
 
5.7%
S 22
 
5.7%
) 17
 
4.4%
( 15
 
3.9%
X 14
 
3.6%
Other values (21) 94
24.2%
None
ValueCountFrequency (%)
㈜ 6
100.0%

주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2398
Missing (%)100.0%
Memory size21.2 KiB

위도
Real number (ℝ)

Distinct2396
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.619
Minimum128.36996
Maximum128.83846
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2023-12-11T08:20:03.005335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.36996
5-th percentile128.44772
Q1128.5665
median128.62065
Q3128.68741
95-th percentile128.76536
Maximum128.83846
Range0.4685015
Interquartile range (IQR)0.12091598

Descriptive statistics

Standard deviation0.091533735
Coefficient of variation (CV)0.00071166573
Kurtosis-0.04956778
Mean128.619
Median Absolute Deviation (MAD)0.0604827
Skewness-0.3324765
Sum308428.37
Variance0.0083784247
MonotonicityNot monotonic
2023-12-11T08:20:03.139726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.6885504 2
 
0.1%
128.5796292 2
 
0.1%
128.5745036 1
 
< 0.1%
128.5734731 1
 
< 0.1%
128.5735855 1
 
< 0.1%
128.5731882 1
 
< 0.1%
128.5741788 1
 
< 0.1%
128.5767179 1
 
< 0.1%
128.5762928 1
 
< 0.1%
128.5790683 1
 
< 0.1%
Other values (2386) 2386
99.5%
ValueCountFrequency (%)
128.3699567 1
< 0.1%
128.3700704 1
< 0.1%
128.3701934 1
< 0.1%
128.3703447 1
< 0.1%
128.3718383 1
< 0.1%
128.3719444 1
< 0.1%
128.3723671 1
< 0.1%
128.3725061 1
< 0.1%
128.3742915 1
< 0.1%
128.3743426 1
< 0.1%
ValueCountFrequency (%)
128.8384582 1
< 0.1%
128.8373885 1
< 0.1%
128.835746 1
< 0.1%
128.8239831 1
< 0.1%
128.8238372 1
< 0.1%
128.8220687 1
< 0.1%
128.821885 1
< 0.1%
128.8212631 1
< 0.1%
128.821258 1
< 0.1%
128.8205994 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct2397
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.209036
Minimum35.060011
Maximum35.388209
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2023-12-11T08:20:03.282435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.060011
5-th percentile35.093571
Q135.146524
median35.211933
Q335.254613
95-th percentile35.352226
Maximum35.388209
Range0.32819803
Interquartile range (IQR)0.10808822

Descriptive statistics

Standard deviation0.078037491
Coefficient of variation (CV)0.0022164052
Kurtosis-0.7440768
Mean35.209036
Median Absolute Deviation (MAD)0.056776065
Skewness0.21361227
Sum84431.268
Variance0.00608985
MonotonicityNot monotonic
2023-12-11T08:20:03.438295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.15260143 2
 
0.1%
35.3375815 1
 
< 0.1%
35.22731232 1
 
< 0.1%
35.21647022 1
 
< 0.1%
35.21891053 1
 
< 0.1%
35.2192542 1
 
< 0.1%
35.22168028 1
 
< 0.1%
35.22243691 1
 
< 0.1%
35.22661843 1
 
< 0.1%
35.23061781 1
 
< 0.1%
Other values (2387) 2387
99.5%
ValueCountFrequency (%)
35.06001085 1
< 0.1%
35.06003284 1
< 0.1%
35.06070516 1
< 0.1%
35.06081827 1
< 0.1%
35.06263599 1
< 0.1%
35.06272569 1
< 0.1%
35.06563931 1
< 0.1%
35.06566438 1
< 0.1%
35.06668889 1
< 0.1%
35.06675604 1
< 0.1%
ValueCountFrequency (%)
35.38820888 1
< 0.1%
35.38813166 1
< 0.1%
35.38216583 1
< 0.1%
35.38206838 1
< 0.1%
35.37822153 1
< 0.1%
35.37790263 1
< 0.1%
35.37570888 1
< 0.1%
35.37558459 1
< 0.1%
35.37519086 1
< 0.1%
35.37334261 1
< 0.1%

Interactions

2023-12-11T08:19:59.493984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:58.219557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:58.586546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:58.980902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:59.851607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:58.305960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:58.678423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:59.135309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:59.944117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:58.402900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:58.770622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:59.243086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:20:00.062089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:58.492761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:58.872144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:19:59.363157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:20:03.551479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ID모바일_ID위도경도
ID1.0000.9160.8270.838
모바일_ID0.9161.0000.6950.738
위도0.8270.6951.0000.708
경도0.8380.7380.7081.000
2023-12-11T08:20:03.650457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ID모바일_ID위도경도
ID1.0001.000-0.018-0.633
모바일_ID1.0001.000-0.018-0.633
위도-0.018-0.0181.0000.054
경도-0.633-0.6330.0541.000

Missing values

2023-12-11T08:20:00.217418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:20:00.339286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

ID모바일_ID행정구역정류장명주소위도경도
01100201동읍합산<NA>128.67738735.337581
12100202동읍합산<NA>128.67729135.337657
23100203동읍용산입구<NA>128.6788835.332786
34100204동읍용산입구<NA>128.67876935.332731
45100205대산면백양마을<NA>128.68734935.327622
56100206대산면백양마을<NA>128.6873335.327495
67100207대산면신등마을<NA>128.69503635.322866
78100208대산면신등마을<NA>128.69502135.322734
89100701대산면신전<NA>128.67400635.367144
910100702대산면상리<NA>128.67779735.36602
ID모바일_ID행정구역정류장명주소위도경도
23882389630355남문동경일글로벌로지스틱스<NA>128.76784635.08699
23892390630356남문동국제물류<NA>128.76528835.090831
23902391630357남문동㈜HND로지스틱스<NA>128.76908535.094001
23912392630358남문동페어허브물류<NA>128.77496735.093999
23922393630359남문동칼트로지스/SKU<NA>128.77866335.093492
23932394630360남문동동영로지스틱스(주)<NA>128.7742335.088324
23942395630361용원동말무교<NA>128.82383735.091914
23952396630362용원동말무교<NA>128.82398335.091702
23962397630372죽곡동진해구 어은입구<NA>128.72650535.113459
23972398630373죽곡동진해구 어은입구<NA>128.72658935.113399