Overview

Dataset statistics

Number of variables12
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 MiB
Average record size in memory109.0 B

Variable types

Numeric5
Categorical1
Text5
DateTime1

Dataset

Description서울시에서 소유한 전기차충전소의 충전량 데이터입니다. 충전구분, 충전소명, 주소, 충전기최대용량, 충전량, 충전시간, 날짜, 충전시작시간, 충전종료시간 데이터입니다.문의 : 기후변화대응과(02-2133-9777)
Author서울특별시
URLhttps://www.data.go.kr/data/15098661/fileData.do

Alerts

충전기 최대용량 is highly overall correlated with 충전구분High correlation
충전구분 is highly overall correlated with 충전기 최대용량High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 20:20:31.933366
Analysis finished2024-03-14 20:20:40.340958
Duration8.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32492.088
Minimum3
Maximum64952
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T05:20:40.534701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3168.95
Q116544.25
median32488.5
Q348601.75
95-th percentile61586.65
Maximum64952
Range64949
Interquartile range (IQR)32057.5

Descriptive statistics

Standard deviation18667.976
Coefficient of variation (CV)0.57453912
Kurtosis-1.1926301
Mean32492.088
Median Absolute Deviation (MAD)16054.5
Skewness0.00013135786
Sum3.2492088 × 108
Variance3.4849331 × 108
MonotonicityNot monotonic
2024-03-15T05:20:40.874886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22764 1
 
< 0.1%
9392 1
 
< 0.1%
52775 1
 
< 0.1%
31699 1
 
< 0.1%
13515 1
 
< 0.1%
58578 1
 
< 0.1%
16036 1
 
< 0.1%
41045 1
 
< 0.1%
10453 1
 
< 0.1%
42807 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
3 1
< 0.1%
12 1
< 0.1%
16 1
< 0.1%
27 1
< 0.1%
41 1
< 0.1%
42 1
< 0.1%
49 1
< 0.1%
50 1
< 0.1%
52 1
< 0.1%
54 1
< 0.1%
ValueCountFrequency (%)
64952 1
< 0.1%
64949 1
< 0.1%
64938 1
< 0.1%
64937 1
< 0.1%
64933 1
< 0.1%
64931 1
< 0.1%
64929 1
< 0.1%
64924 1
< 0.1%
64922 1
< 0.1%
64917 1
< 0.1%

충전구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
급속
8694 
완속
1306 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row급속
2nd row급속
3rd row급속
4th row급속
5th row완속

Common Values

ValueCountFrequency (%)
급속 8694
86.9%
완속 1306
 
13.1%

Length

2024-03-15T05:20:41.237958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:20:41.491993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
급속 8694
86.9%
완속 1306
 
13.1%
Distinct108
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-15T05:20:42.326302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length23
Mean length14.2502
Min length4

Characters and Unicode

Total characters142502
Distinct characters216
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row개화산역 공영주차장
2nd row중랑구청(변압기 6월 교체예정)
3rd row홍제1동 제1공영주차장
4th row천호역 공영주차장
5th row서울시 본관청사
ValueCountFrequency (%)
충전소 2423
 
8.8%
1913
 
7.0%
공영주차장 1539
 
5.6%
가로등형 1279
 
4.7%
양재솔라스테이션 1240
 
4.5%
전기차 1190
 
4.3%
복합충전소 1065
 
3.9%
주차장 778
 
2.8%
어린이대공원 624
 
2.3%
제1공영주차장 607
 
2.2%
Other values (150) 14836
54.0%
2024-03-15T05:20:43.963066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17494
 
12.3%
6453
 
4.5%
5856
 
4.1%
5205
 
3.7%
5153
 
3.6%
4155
 
2.9%
4111
 
2.9%
4009
 
2.8%
3340
 
2.3%
3243
 
2.3%
Other values (206) 83483
58.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117550
82.5%
Space Separator 17494
 
12.3%
Decimal Number 2632
 
1.8%
Close Punctuation 1998
 
1.4%
Open Punctuation 1998
 
1.4%
Uppercase Letter 437
 
0.3%
Other Punctuation 393
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6453
 
5.5%
5856
 
5.0%
5205
 
4.4%
5153
 
4.4%
4155
 
3.5%
4111
 
3.5%
4009
 
3.4%
3340
 
2.8%
3243
 
2.8%
2952
 
2.5%
Other values (190) 73073
62.2%
Decimal Number
ValueCountFrequency (%)
1 1370
52.1%
2 309
 
11.7%
8 279
 
10.6%
6 263
 
10.0%
3 138
 
5.2%
5 126
 
4.8%
4 105
 
4.0%
0 42
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
K 171
39.1%
S 171
39.1%
B 95
21.7%
Other Punctuation
ValueCountFrequency (%)
, 372
94.7%
/ 21
 
5.3%
Space Separator
ValueCountFrequency (%)
17494
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1998
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1998
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117550
82.5%
Common 24515
 
17.2%
Latin 437
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6453
 
5.5%
5856
 
5.0%
5205
 
4.4%
5153
 
4.4%
4155
 
3.5%
4111
 
3.5%
4009
 
3.4%
3340
 
2.8%
3243
 
2.8%
2952
 
2.5%
Other values (190) 73073
62.2%
Common
ValueCountFrequency (%)
17494
71.4%
) 1998
 
8.2%
( 1998
 
8.2%
1 1370
 
5.6%
, 372
 
1.5%
2 309
 
1.3%
8 279
 
1.1%
6 263
 
1.1%
3 138
 
0.6%
5 126
 
0.5%
Other values (3) 168
 
0.7%
Latin
ValueCountFrequency (%)
K 171
39.1%
S 171
39.1%
B 95
21.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117550
82.5%
ASCII 24952
 
17.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17494
70.1%
) 1998
 
8.0%
( 1998
 
8.0%
1 1370
 
5.5%
, 372
 
1.5%
2 309
 
1.2%
8 279
 
1.1%
6 263
 
1.1%
K 171
 
0.7%
S 171
 
0.7%
Other values (6) 527
 
2.1%
Hangul
ValueCountFrequency (%)
6453
 
5.5%
5856
 
5.0%
5205
 
4.4%
5153
 
4.4%
4155
 
3.5%
4111
 
3.5%
4009
 
3.4%
3340
 
2.8%
3243
 
2.8%
2952
 
2.5%
Other values (190) 73073
62.2%

주소
Text

Distinct130
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-15T05:20:45.015415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length59
Mean length24.0401
Min length14

Characters and Unicode

Total characters240401
Distinct characters268
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row서울 강서구 양천로 22(개화산역)
2nd row서울 중랑구 봉화산로 179(중랑구청)
3rd row서울 서대문구 홍제내2바길 18(이안휴빌A동)
4th row서울 강동구 천호대로 지하 997(천호역)
5th row서울 중구 세종대로 110(서울특별시청)
ValueCountFrequency (%)
서울 9855
22.0%
중구 1578
 
3.5%
서초구 1300
 
2.9%
바우뫼로12길 1240
 
2.8%
73(현대기아차 1201
 
2.7%
그린에너지 1201
 
2.7%
스테이션 1201
 
2.7%
강남구 1091
 
2.4%
서대문구 985
 
2.2%
광진구 966
 
2.2%
Other values (306) 24154
53.9%
2024-03-15T05:20:46.394648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34779
 
14.5%
14138
 
5.9%
11773
 
4.9%
10784
 
4.5%
) 9046
 
3.8%
( 9046
 
3.8%
8882
 
3.7%
1 8658
 
3.6%
2 5923
 
2.5%
4995
 
2.1%
Other values (258) 122377
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 151297
62.9%
Space Separator 34779
 
14.5%
Decimal Number 33151
 
13.8%
Close Punctuation 9046
 
3.8%
Open Punctuation 9046
 
3.8%
Uppercase Letter 2017
 
0.8%
Dash Punctuation 881
 
0.4%
Other Punctuation 184
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
14138
 
9.3%
11773
 
7.8%
10784
 
7.1%
8882
 
5.9%
4995
 
3.3%
4668
 
3.1%
4381
 
2.9%
2975
 
2.0%
2710
 
1.8%
2167
 
1.4%
Other values (233) 83824
55.4%
Decimal Number
ValueCountFrequency (%)
1 8658
26.1%
2 5923
17.9%
7 4101
12.4%
3 3184
 
9.6%
5 2572
 
7.8%
8 2329
 
7.0%
6 2086
 
6.3%
4 1762
 
5.3%
0 1497
 
4.5%
9 1039
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
A 601
29.8%
K 580
28.8%
T 504
25.0%
M 120
 
5.9%
S 76
 
3.8%
U 44
 
2.2%
I 44
 
2.2%
C 44
 
2.2%
F 4
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 179
97.3%
/ 5
 
2.7%
Space Separator
ValueCountFrequency (%)
34779
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9046
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9046
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 881
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 151297
62.9%
Common 87087
36.2%
Latin 2017
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
14138
 
9.3%
11773
 
7.8%
10784
 
7.1%
8882
 
5.9%
4995
 
3.3%
4668
 
3.1%
4381
 
2.9%
2975
 
2.0%
2710
 
1.8%
2167
 
1.4%
Other values (233) 83824
55.4%
Common
ValueCountFrequency (%)
34779
39.9%
) 9046
 
10.4%
( 9046
 
10.4%
1 8658
 
9.9%
2 5923
 
6.8%
7 4101
 
4.7%
3 3184
 
3.7%
5 2572
 
3.0%
8 2329
 
2.7%
6 2086
 
2.4%
Other values (6) 5363
 
6.2%
Latin
ValueCountFrequency (%)
A 601
29.8%
K 580
28.8%
T 504
25.0%
M 120
 
5.9%
S 76
 
3.8%
U 44
 
2.2%
I 44
 
2.2%
C 44
 
2.2%
F 4
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 151297
62.9%
ASCII 89104
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34779
39.0%
) 9046
 
10.2%
( 9046
 
10.2%
1 8658
 
9.7%
2 5923
 
6.6%
7 4101
 
4.6%
3 3184
 
3.6%
5 2572
 
2.9%
8 2329
 
2.6%
6 2086
 
2.3%
Other values (15) 7380
 
8.3%
Hangul
ValueCountFrequency (%)
14138
 
9.3%
11773
 
7.8%
10784
 
7.1%
8882
 
5.9%
4995
 
3.3%
4668
 
3.1%
4381
 
2.9%
2975
 
2.0%
2710
 
1.8%
2167
 
1.4%
Other values (233) 83824
55.4%

위도
Real number (ℝ)

Distinct101
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.540509
Minimum37.467922
Maximum37.681781
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T05:20:46.750435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.467922
5-th percentile37.467922
Q137.506097
median37.545392
Q337.570547
95-th percentile37.606906
Maximum37.681781
Range0.21385893
Interquartile range (IQR)0.06444961

Descriptive statistics

Standard deviation0.046633704
Coefficient of variation (CV)0.0012422235
Kurtosis-0.44199877
Mean37.540509
Median Absolute Deviation (MAD)0.03316891
Skewness0.11085677
Sum375405.09
Variance0.0021747023
MonotonicityNot monotonic
2024-03-15T05:20:47.177065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.46792238 1240
 
12.4%
37.58494049 597
 
6.0%
37.54539249 561
 
5.6%
37.48756711 504
 
5.0%
37.60690598 272
 
2.7%
37.530745 262
 
2.6%
37.51252777 256
 
2.6%
37.56631742 244
 
2.4%
37.563278 236
 
2.4%
37.60315527 230
 
2.3%
Other values (91) 5598
56.0%
ValueCountFrequency (%)
37.46792238 1240
12.4%
37.46885375 1
 
< 0.1%
37.47016465 76
 
0.8%
37.47667701 60
 
0.6%
37.48347063 44
 
0.4%
37.48511944 57
 
0.6%
37.48536368 3
 
< 0.1%
37.48683958 56
 
0.6%
37.48756711 504
5.0%
37.4883103 163
 
1.6%
ValueCountFrequency (%)
37.68178131 23
 
0.2%
37.67816656 65
0.7%
37.67585042 7
 
0.1%
37.66430371 13
 
0.1%
37.6552808 8
 
0.1%
37.65445096 23
 
0.2%
37.65347451 2
 
< 0.1%
37.64351151 28
0.3%
37.6414134 16
 
0.2%
37.63823677 12
 
0.1%

경도
Real number (ℝ)

Distinct101
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.0117
Minimum126.80483
Maximum127.12809
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T05:20:47.592878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.80483
5-th percentile126.87227
Q1126.94031
median127.03474
Q3127.08032
95-th percentile127.10411
Maximum127.12809
Range0.3232629
Interquartile range (IQR)0.1400047

Descriptive statistics

Standard deviation0.072752742
Coefficient of variation (CV)0.00057280345
Kurtosis-0.28382781
Mean127.0117
Median Absolute Deviation (MAD)0.0583176
Skewness-0.51423749
Sum1270117
Variance0.0052929615
MonotonicityNot monotonic
2024-03-15T05:20:48.063791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0347376 1240
 
12.4%
126.9375235 597
 
6.0%
127.0847951 561
 
5.6%
127.1007235 504
 
5.0%
127.0932737 272
 
2.7%
127.041305 262
 
2.6%
126.9399421 256
 
2.6%
126.9778292 244
 
2.4%
126.97642 236
 
2.4%
127.1018644 230
 
2.3%
Other values (91) 5598
56.0%
ValueCountFrequency (%)
126.804828 143
1.4%
126.8163489 4
 
< 0.1%
126.8261173 41
 
0.4%
126.8282389 13
 
0.1%
126.833992 12
 
0.1%
126.8555457 89
0.9%
126.8663651 67
0.7%
126.8673959 71
0.7%
126.8722666 76
0.8%
126.8750971 21
 
0.2%
ValueCountFrequency (%)
127.1280909 76
 
0.8%
127.1251054 56
 
0.6%
127.1240656 50
 
0.5%
127.1237424 141
 
1.4%
127.1201527 72
 
0.7%
127.1120462 4
 
< 0.1%
127.1101254 22
 
0.2%
127.1041149 172
 
1.7%
127.1018644 230
2.3%
127.1007235 504
5.0%

충전기 최대용량
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.4952
Minimum7
Maximum240
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T05:20:48.403964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile7
Q150
median50
Q3100
95-th percentile200
Maximum240
Range233
Interquartile range (IQR)50

Descriptive statistics

Standard deviation56.815637
Coefficient of variation (CV)0.74273466
Kurtosis0.54367607
Mean76.4952
Median Absolute Deviation (MAD)0
Skewness1.1744257
Sum764952
Variance3228.0166
MonotonicityNot monotonic
2024-03-15T05:20:48.763382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
50 5025
50.2%
100 2299
23.0%
7 1306
 
13.1%
200 1247
 
12.5%
180 71
 
0.7%
240 52
 
0.5%
ValueCountFrequency (%)
7 1306
 
13.1%
50 5025
50.2%
100 2299
23.0%
180 71
 
0.7%
200 1247
 
12.5%
240 52
 
0.5%
ValueCountFrequency (%)
240 52
 
0.5%
200 1247
 
12.5%
180 71
 
0.7%
100 2299
23.0%
50 5025
50.2%
7 1306
 
13.1%

충전량(kWh)
Real number (ℝ)

Distinct4360
Distinct (%)43.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.668658
Minimum0.31
Maximum120.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T05:20:49.154922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.31
5-th percentile1.8995
Q110.17
median19.785
Q330.92
95-th percentile53.31
Maximum120.66
Range120.35
Interquartile range (IQR)20.75

Descriptive statistics

Standard deviation15.941117
Coefficient of variation (CV)0.70322279
Kurtosis0.64225882
Mean22.668658
Median Absolute Deviation (MAD)10.535
Skewness0.87943037
Sum226686.58
Variance254.11921
MonotonicityNot monotonic
2024-03-15T05:20:49.610649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.42 132
 
1.3%
30.83 93
 
0.9%
9.25 65
 
0.7%
30.84 48
 
0.5%
15.43 40
 
0.4%
21.58 38
 
0.4%
6.17 37
 
0.4%
46.24 30
 
0.3%
3.09 28
 
0.3%
18.5 26
 
0.3%
Other values (4350) 9463
94.6%
ValueCountFrequency (%)
0.31 7
0.1%
0.32 4
< 0.1%
0.33 1
 
< 0.1%
0.34 1
 
< 0.1%
0.35 5
0.1%
0.36 2
 
< 0.1%
0.37 2
 
< 0.1%
0.38 2
 
< 0.1%
0.39 2
 
< 0.1%
0.4 5
0.1%
ValueCountFrequency (%)
120.66 1
< 0.1%
119.45 1
< 0.1%
107.64 1
< 0.1%
99.03 1
< 0.1%
98.07 1
< 0.1%
96.92 1
< 0.1%
94.73 1
< 0.1%
93.34 1
< 0.1%
92.12 1
< 0.1%
91.32 1
< 0.1%
Distinct5271
Distinct (%)52.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-15T05:20:50.858999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length6.3684
Min length2

Characters and Unicode

Total characters63684
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3083 ?
Unique (%)30.8%

Sample

1st row17분33초
2nd row1시간6분45초
3rd row52분42초
4th row40분31초
5th row2시간21분56초
ValueCountFrequency (%)
40분1초 322
 
3.2%
40분5초 187
 
1.9%
40분2초 156
 
1.6%
40분6초 97
 
1.0%
40분7초 77
 
0.8%
40분4초 46
 
0.5%
40분8초 45
 
0.4%
41분 37
 
0.4%
40분3초 30
 
0.3%
40분0초 18
 
0.2%
Other values (5261) 8985
89.8%
2024-03-15T05:20:52.664998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9868
15.5%
9728
15.3%
1 7173
11.3%
4 5780
9.1%
2 5519
8.7%
3 5163
8.1%
5 4562
7.2%
2899
 
4.6%
2899
 
4.6%
0 2675
 
4.2%
Other values (5) 7418
11.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38289
60.1%
Other Letter 25394
39.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7173
18.7%
4 5780
15.1%
2 5519
14.4%
3 5163
13.5%
5 4562
11.9%
0 2675
 
7.0%
6 1975
 
5.2%
7 1872
 
4.9%
8 1797
 
4.7%
9 1773
 
4.6%
Other Letter
ValueCountFrequency (%)
9868
38.9%
9728
38.3%
2899
 
11.4%
2899
 
11.4%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38290
60.1%
Hangul 25394
39.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7173
18.7%
4 5780
15.1%
2 5519
14.4%
3 5163
13.5%
5 4562
11.9%
0 2675
 
7.0%
6 1975
 
5.2%
7 1872
 
4.9%
8 1797
 
4.7%
9 1773
 
4.6%
Hangul
ValueCountFrequency (%)
9868
38.9%
9728
38.3%
2899
 
11.4%
2899
 
11.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38290
60.1%
Hangul 25394
39.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
9868
38.9%
9728
38.3%
2899
 
11.4%
2899
 
11.4%
ASCII
ValueCountFrequency (%)
1 7173
18.7%
4 5780
15.1%
2 5519
14.4%
3 5163
13.5%
5 4562
11.9%
0 2675
 
7.0%
6 1975
 
5.2%
7 1872
 
4.9%
8 1797
 
4.7%
9 1773
 
4.6%
Distinct297
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-05-09 00:00:00
Maximum2024-02-29 00:00:00
2024-03-15T05:20:53.142763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:53.630706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct9321
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-15T05:20:55.138656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length7.9993
Min length6

Characters and Unicode

Total characters79993
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8677 ?
Unique (%)86.8%

Sample

1st row20:05:02
2nd row08:56:14
3rd row00:57:08
4th row20:08:21
5th row09:20:56
ValueCountFrequency (%)
14:47:54 5
 
< 0.1%
13:11:37 4
 
< 0.1%
20:16:50 3
 
< 0.1%
12:26:00 3
 
< 0.1%
16:31:00 3
 
< 0.1%
18:54:09 3
 
< 0.1%
14:25:41 3
 
< 0.1%
09:09:12 3
 
< 0.1%
16:19:20 3
 
< 0.1%
12:04:00 3
 
< 0.1%
Other values (9311) 9967
99.7%
2024-03-15T05:20:56.945237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 19964
25.0%
1 12530
15.7%
0 9564
12.0%
2 7776
 
9.7%
3 6311
 
7.9%
4 6096
 
7.6%
5 5942
 
7.4%
9 3019
 
3.8%
8 2939
 
3.7%
7 2921
 
3.7%
Other values (2) 2931
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60011
75.0%
Other Punctuation 19982
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12530
20.9%
0 9564
15.9%
2 7776
13.0%
3 6311
10.5%
4 6096
10.2%
5 5942
9.9%
9 3019
 
5.0%
8 2939
 
4.9%
7 2921
 
4.9%
6 2913
 
4.9%
Other Punctuation
ValueCountFrequency (%)
: 19964
99.9%
. 18
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 79993
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 19964
25.0%
1 12530
15.7%
0 9564
12.0%
2 7776
 
9.7%
3 6311
 
7.9%
4 6096
 
7.6%
5 5942
 
7.4%
9 3019
 
3.8%
8 2939
 
3.7%
7 2921
 
3.7%
Other values (2) 2931
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79993
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 19964
25.0%
1 12530
15.7%
0 9564
12.0%
2 7776
 
9.7%
3 6311
 
7.9%
4 6096
 
7.6%
5 5942
 
7.4%
9 3019
 
3.8%
8 2939
 
3.7%
7 2921
 
3.7%
Other values (2) 2931
 
3.7%
Distinct9322
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-15T05:20:58.479918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.989
Min length5

Characters and Unicode

Total characters79890
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8679 ?
Unique (%)86.8%

Sample

1st row20:22:35
2nd row10:02:59
3rd row01:49:50
4th row20:48:52
5th row11:42:52
ValueCountFrequency (%)
09:18:54 4
 
< 0.1%
21:30:30 4
 
< 0.1%
21:26:39 3
 
< 0.1%
14:16:11 3
 
< 0.1%
12:24:00 3
 
< 0.1%
15:26:33 3
 
< 0.1%
10:45:18 3
 
< 0.1%
10:50:29 3
 
< 0.1%
20:38:02 3
 
< 0.1%
12:37:54 3
 
< 0.1%
Other values (9312) 9968
99.7%
2024-03-15T05:21:00.391123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 19964
25.0%
1 12417
15.5%
0 9420
11.8%
2 8098
10.1%
3 6478
 
8.1%
5 6055
 
7.6%
4 5981
 
7.5%
9 2960
 
3.7%
7 2854
 
3.6%
6 2816
 
3.5%
Other values (3) 2847
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59890
75.0%
Other Punctuation 19982
 
25.0%
Space Separator 18
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12417
20.7%
0 9420
15.7%
2 8098
13.5%
3 6478
10.8%
5 6055
10.1%
4 5981
10.0%
9 2960
 
4.9%
7 2854
 
4.8%
6 2816
 
4.7%
8 2811
 
4.7%
Other Punctuation
ValueCountFrequency (%)
: 19964
99.9%
. 18
 
0.1%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 79890
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 19964
25.0%
1 12417
15.5%
0 9420
11.8%
2 8098
10.1%
3 6478
 
8.1%
5 6055
 
7.6%
4 5981
 
7.5%
9 2960
 
3.7%
7 2854
 
3.6%
6 2816
 
3.5%
Other values (3) 2847
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79890
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 19964
25.0%
1 12417
15.5%
0 9420
11.8%
2 8098
10.1%
3 6478
 
8.1%
5 6055
 
7.6%
4 5981
 
7.5%
9 2960
 
3.7%
7 2854
 
3.6%
6 2816
 
3.5%
Other values (3) 2847
 
3.6%

Interactions

2024-03-15T05:20:38.257289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:33.406196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:34.582923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:35.660862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:36.865264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:38.531296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:33.672260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:34.820403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:35.833018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:37.134374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:38.785827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:33.926467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:34.993998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:36.045868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:37.385555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:39.065425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:34.239944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:35.274160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:36.322739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:37.663957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:39.331539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:34.412107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:35.493007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:36.593111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:20:37.982263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:21:00.592123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번충전구분위도경도충전기 최대용량충전량(kWh)
연번1.0000.0650.1940.2230.1530.068
충전구분0.0651.0000.5190.4801.0000.264
위도0.1940.5191.0000.8880.6400.265
경도0.2230.4800.8881.0000.6370.277
충전기 최대용량0.1531.0000.6400.6371.0000.228
충전량(kWh)0.0680.2640.2650.2770.2281.000
2024-03-15T05:21:00.896413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도충전기 최대용량충전량(kWh)충전구분
연번1.000-0.029-0.013-0.012-0.0220.050
위도-0.0291.000-0.193-0.2220.0510.400
경도-0.013-0.1931.0000.1830.0810.369
충전기 최대용량-0.012-0.2220.1831.0000.2111.000
충전량(kWh)-0.0220.0510.0810.2111.0000.202
충전구분0.0500.4000.3691.0000.2021.000

Missing values

2024-03-15T05:20:39.683354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:20:40.101300image/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

연번충전구분충전소명주소위도경도충전기 최대용량충전량(kWh)충전시간충전날짜충전시작시간충전종료시간
2276322764급속개화산역 공영주차장서울 강서구 양천로 22(개화산역)37.572422126.804828509.1217분33초2023-12-1320:05:0220:22:35
2293822939급속중랑구청(변압기 6월 교체예정)서울 중랑구 봉화산로 179(중랑구청)37.606906127.09327410044.81시간6분45초2023-12-1308:56:1410:02:59
2757327574급속홍제1동 제1공영주차장서울 서대문구 홍제내2바길 18(이안휴빌A동)37.58494126.93752310047.052분42초2023-11-2500:57:0801:49:50
5186151862급속천호역 공영주차장서울 강동구 천호대로 지하 997(천호역)37.538579127.1237425019.7440분31초2023-07-2120:08:2120:48:52
33803381완속서울시 본관청사서울 중구 세종대로 110(서울특별시청)37.566317126.977829715.322시간21분56초2024-02-1909:20:5611:42:52
1030210303급속복정역 공영주차장서울 송파구 송파대로 지하 6(복정역)37.470165127.128091504.7811분38초2024-01-2511:17:2411:29:02
5103951040급속서대문구청 주차장서울 서대문구 연희로 248(서대문구청)37.579155126.9367595024.3840분6초2023-07-2617:00:5017:40:56
4561245613급속중랑구청(변압기 6월 교체예정)서울 중랑구 봉화산로 179(중랑구청)37.606906127.09327410037.5741분21초2023-08-2516:33:0917:14:30
2910929110급속한마음공영주차장서울 양천구 목동 914-6(도로환경관리센터)37.531187126.8778692008.826분19초2023-11-1820:13:4520:20:04
3305533056급속을지로 노상공영주차장(신한은행 앞, 가로등)서울 중구 을지로5가 20-1(정건벨라지오)37.566948127.001721502.786분31초2023-11-0114:37:1714:43:48
연번충전구분충전소명주소위도경도충전기 최대용량충전량(kWh)충전시간충전날짜충전시작시간충전종료시간
5742757428급속서대문구청 주차장서울 서대문구 연희로 248(서대문구청)37.579155126.936759506.8716분46초2023-06-2114:19:1614:36:02
33343335급속양재솔라스테이션서울 서초구 바우뫼로12길 73(현대기아차 그린에너지 스테이션)37.467922127.03473810041.861시간15분54초2024-02-1912:00:2913:16:23
3342233423급속정릉천변 노상공영주차장(가로등)서울 동대문구 정릉천동로 125-137.583633127.036105501.744분15초2023-10-3102:41:1802:45:33
4452044521급속동작구청 후문 가로등형 충전소서울 동작구 장승배기로 161(동작구청)37.512528126.9399425026.5641분54초2023-08-3118:15:5218:57:46
4940649407급속동작구청 후문 가로등형 충전소서울 동작구 장승배기로 161(동작구청)37.512528126.9399425017.335분19초2023-08-0410:31:2411:06:43
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