Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells11280
Missing cells (%)7.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory136.0 B

Variable types

Text7
Numeric7
Unsupported1

Dataset

Description전기차 충전소 현황(제공표준)
Author환경부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=K9O004K6055A8ZC1M72T12756075&infSeq=1

Alerts

충전기타입 is highly overall correlated with 충전기용량High correlation
충전기용량 is highly overall correlated with 충전기타입High correlation
이용가능시간 has 220 (2.2%) missing valuesMissing
관리업체전화번호 has 184 (1.8%) missing valuesMissing
충전기용량 has 428 (4.3%) missing valuesMissing
상태갱신일자 has 448 (4.5%) missing valuesMissing
데이터기준일자 has 10000 (100.0%) missing valuesMissing
데이터기준일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-12 23:30:59.886596
Analysis finished2024-03-12 23:31:06.502490
Duration6.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

충전소명
Text

Distinct6027
Distinct (%)60.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T08:31:06.678063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length28
Mean length11.8988
Min length2

Characters and Unicode

Total characters118988
Distinct characters693
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4019 ?
Unique (%)40.2%

Sample

1st row경기화성 동탄시범반도유보라아이비파크아파트4
2nd row부천체육관
3rd row양주옥정신도시 제일풍경채레이크시티1단지
4th row경기남부보훈지청
5th row신원마을5단지삼송우림필유1
ValueCountFrequency (%)
경기용인 161
 
1.0%
경기고양 130
 
0.8%
아파트 126
 
0.8%
경기남양주 105
 
0.6%
경기수원 105
 
0.6%
1 100
 
0.6%
경기화성 96
 
0.6%
충전소 85
 
0.5%
지하1층 85
 
0.5%
용인시 84
 
0.5%
Other values (6570) 15134
93.4%
2024-03-13T08:31:07.054145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6217
 
5.2%
트 4279
 
3.6%
아 4113
 
3.5%
파 4084
 
3.4%
지 3058
 
2.6%
스 2588
 
2.2%
1 2401
 
2.0%
주 2021
 
1.7%
이 2008
 
1.7%
동 1930
 
1.6%
Other values (683) 86289
72.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 101282
85.1%
Decimal Number 7708
 
6.5%
Space Separator 6217
 
5.2%
Uppercase Letter 2077
 
1.7%
Open Punctuation 536
 
0.5%
Close Punctuation 536
 
0.5%
Lowercase Letter 217
 
0.2%
Dash Punctuation 211
 
0.2%
Connector Punctuation 154
 
0.1%
Other Symbol 29
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 4279
 
4.2%
아 4113
 
4.1%
파 4084
 
4.0%
지 3058
 
3.0%
스 2588
 
2.6%
주 2021
 
2.0%
이 2008
 
2.0%
동 1930
 
1.9%
단 1807
 
1.8%
시 1748
 
1.7%
Other values (621) 73646
72.7%
Uppercase Letter
ValueCountFrequency (%)
B 342
16.5%
S 229
11.0%
L 190
 
9.1%
C 176
 
8.5%
H 136
 
6.5%
K 128
 
6.2%
G 122
 
5.9%
A 119
 
5.7%
E 87
 
4.2%
D 73
 
3.5%
Other values (15) 475
22.9%
Lowercase Letter
ValueCountFrequency (%)
e 88
40.6%
c 26
 
12.0%
s 15
 
6.9%
k 14
 
6.5%
n 10
 
4.6%
i 9
 
4.1%
t 8
 
3.7%
u 7
 
3.2%
o 6
 
2.8%
p 5
 
2.3%
Other values (8) 29
 
13.4%
Decimal Number
ValueCountFrequency (%)
1 2401
31.1%
2 1770
23.0%
3 874
 
11.3%
0 701
 
9.1%
4 513
 
6.7%
5 506
 
6.6%
6 318
 
4.1%
7 256
 
3.3%
8 218
 
2.8%
9 151
 
2.0%
Other Punctuation
ValueCountFrequency (%)
/ 19
90.5%
, 1
 
4.8%
. 1
 
4.8%
Space Separator
ValueCountFrequency (%)
6217
100.0%
Open Punctuation
ValueCountFrequency (%)
( 536
100.0%
Close Punctuation
ValueCountFrequency (%)
) 536
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 211
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 154
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 101310
85.1%
Common 15383
 
12.9%
Latin 2294
 
1.9%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 4279
 
4.2%
아 4113
 
4.1%
파 4084
 
4.0%
지 3058
 
3.0%
스 2588
 
2.6%
주 2021
 
2.0%
이 2008
 
2.0%
동 1930
 
1.9%
단 1807
 
1.8%
시 1748
 
1.7%
Other values (621) 73674
72.7%
Latin
ValueCountFrequency (%)
B 342
14.9%
S 229
 
10.0%
L 190
 
8.3%
C 176
 
7.7%
H 136
 
5.9%
K 128
 
5.6%
G 122
 
5.3%
A 119
 
5.2%
e 88
 
3.8%
E 87
 
3.8%
Other values (33) 677
29.5%
Common
ValueCountFrequency (%)
6217
40.4%
1 2401
 
15.6%
2 1770
 
11.5%
3 874
 
5.7%
0 701
 
4.6%
( 536
 
3.5%
) 536
 
3.5%
4 513
 
3.3%
5 506
 
3.3%
6 318
 
2.1%
Other values (8) 1011
 
6.6%
Han
ValueCountFrequency (%)
愛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 101281
85.1%
ASCII 17677
 
14.9%
None 29
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6217
35.2%
1 2401
 
13.6%
2 1770
 
10.0%
3 874
 
4.9%
0 701
 
4.0%
( 536
 
3.0%
) 536
 
3.0%
4 513
 
2.9%
5 506
 
2.9%
B 342
 
1.9%
Other values (51) 3281
18.6%
Hangul
ValueCountFrequency (%)
트 4279
 
4.2%
아 4113
 
4.1%
파 4084
 
4.0%
지 3058
 
3.0%
스 2588
 
2.6%
주 2021
 
2.0%
이 2008
 
2.0%
동 1930
 
1.9%
단 1807
 
1.8%
시 1748
 
1.7%
Other values (620) 73645
72.7%
None
ValueCountFrequency (%)
㈜ 29
100.0%
CJK
ValueCountFrequency (%)
愛 1
100.0%

이용가능시간
Text

MISSING 

Distinct102
Distinct (%)1.0%
Missing220
Missing (%)2.2%
Memory size156.2 KiB
2024-03-13T08:31:07.274846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length9
Mean length10.253272
Min length1

Characters and Unicode

Total characters100277
Distinct characters115
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)0.4%

Sample

1st row24시간 이용가능
2nd row24시간 이용가능
3rd row24시간 이용가능
4th row24시간 이용가능
5th row24시간 이용가능,입주민만 사용가능 거주자외출입제한
ValueCountFrequency (%)
24시간 8533
42.8%
이용가능 7960
39.9%
사용가능 437
 
2.2%
이용가능,입주민만 431
 
2.2%
거주자외출입제한 412
 
2.1%
09:00~18:00 313
 
1.6%
08:00~20:00 239
 
1.2%
08:00~22:00 233
 
1.2%
133
 
0.7%
평일 109
 
0.5%
Other values (126) 1151
 
5.8%
2024-03-13T08:31:07.579803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10171
10.1%
2 9590
9.6%
용 8980
9.0%
가 8926
8.9%
능 8903
8.9%
시 8708
8.7%
4 8655
8.6%
이 8566
8.5%
간 8551
8.5%
0 5717
5.7%
Other values (105) 13510
13.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60258
60.1%
Decimal Number 25862
25.8%
Space Separator 10171
 
10.1%
Other Punctuation 2747
 
2.7%
Math Symbol 1133
 
1.1%
Open Punctuation 40
 
< 0.1%
Close Punctuation 39
 
< 0.1%
Uppercase Letter 21
 
< 0.1%
Dash Punctuation 5
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 8980
14.9%
가 8926
14.8%
능 8903
14.8%
시 8708
14.5%
이 8566
14.2%
간 8551
14.2%
주 1013
 
1.7%
입 921
 
1.5%
제 508
 
0.8%
한 504
 
0.8%
Other values (81) 4678
7.8%
Decimal Number
ValueCountFrequency (%)
2 9590
37.1%
4 8655
33.5%
0 5717
22.1%
8 850
 
3.3%
1 536
 
2.1%
9 362
 
1.4%
3 94
 
0.4%
6 34
 
0.1%
5 14
 
0.1%
7 10
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
: 2183
79.5%
, 452
 
16.5%
/ 109
 
4.0%
. 2
 
0.1%
% 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
W 7
33.3%
M 7
33.3%
B 7
33.3%
Space Separator
ValueCountFrequency (%)
10171
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1133
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60258
60.1%
Common 39998
39.9%
Latin 21
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 8980
14.9%
가 8926
14.8%
능 8903
14.8%
시 8708
14.5%
이 8566
14.2%
간 8551
14.2%
주 1013
 
1.7%
입 921
 
1.5%
제 508
 
0.8%
한 504
 
0.8%
Other values (81) 4678
7.8%
Common
ValueCountFrequency (%)
10171
25.4%
2 9590
24.0%
4 8655
21.6%
0 5717
14.3%
: 2183
 
5.5%
~ 1133
 
2.8%
8 850
 
2.1%
1 536
 
1.3%
, 452
 
1.1%
9 362
 
0.9%
Other values (11) 349
 
0.9%
Latin
ValueCountFrequency (%)
W 7
33.3%
M 7
33.3%
B 7
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60258
60.1%
ASCII 40019
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10171
25.4%
2 9590
24.0%
4 8655
21.6%
0 5717
14.3%
: 2183
 
5.5%
~ 1133
 
2.8%
8 850
 
2.1%
1 536
 
1.3%
, 452
 
1.1%
9 362
 
0.9%
Other values (14) 370
 
0.9%
Hangul
ValueCountFrequency (%)
용 8980
14.9%
가 8926
14.8%
능 8903
14.8%
시 8708
14.5%
이 8566
14.2%
간 8551
14.2%
주 1013
 
1.7%
입 921
 
1.5%
제 508
 
0.8%
한 504
 
0.8%
Other values (81) 4678
7.8%

충전기상태
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7523
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T08:31:07.680761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median2
Q33
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.9443185
Coefficient of variation (CV)0.78467034
Kurtosis-0.5330924
Mean3.7523
Median Absolute Deviation (MAD)0
Skewness1.1799106
Sum37523
Variance8.6690116
MonotonicityNot monotonic
2024-03-13T08:31:07.781034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 6565
65.6%
9 2350
 
23.5%
3 785
 
7.8%
1 151
 
1.5%
5 141
 
1.4%
4 8
 
0.1%
ValueCountFrequency (%)
1 151
 
1.5%
2 6565
65.6%
3 785
 
7.8%
4 8
 
0.1%
5 141
 
1.4%
9 2350
 
23.5%
ValueCountFrequency (%)
9 2350
 
23.5%
5 141
 
1.4%
4 8
 
0.1%
3 785
 
7.8%
2 6565
65.6%
1 151
 
1.5%

충전기타입
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2281
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T08:31:07.870903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median2
Q32
95-th percentile4
Maximum8
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.77803016
Coefficient of variation (CV)0.34918996
Kurtosis13.940146
Mean2.2281
Median Absolute Deviation (MAD)0
Skewness3.6779007
Sum22281
Variance0.60533092
MonotonicityNot monotonic
2024-03-13T08:31:07.953131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 9098
91.0%
4 647
 
6.5%
6 193
 
1.9%
5 41
 
0.4%
8 9
 
0.1%
7 8
 
0.1%
1 3
 
< 0.1%
3 1
 
< 0.1%
ValueCountFrequency (%)
1 3
 
< 0.1%
2 9098
91.0%
3 1
 
< 0.1%
4 647
 
6.5%
5 41
 
0.4%
6 193
 
1.9%
7 8
 
0.1%
8 9
 
0.1%
ValueCountFrequency (%)
8 9
 
0.1%
7 8
 
0.1%
6 193
 
1.9%
5 41
 
0.4%
4 647
 
6.5%
3 1
 
< 0.1%
2 9098
91.0%
1 3
 
< 0.1%

소재지도로명주소
Text

Distinct4833
Distinct (%)48.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T08:31:08.205545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length53
Mean length19.881
Min length6

Characters and Unicode

Total characters198810
Distinct characters490
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2656 ?
Unique (%)26.6%

Sample

1st row경기도 화성시 동탄대로시범길 168
2nd row경기도 부천시 석천로
3rd row경기 양주시 옥정동 1043
4th row경기도 수원시 장안구 조원로 8
5th row경기도 고양시 덕양구 신원로 55 (신원동, 신원마을5단지 우림필유아파트)
ValueCountFrequency (%)
경기도 9877
 
21.1%
용인시 947
 
2.0%
고양시 832
 
1.8%
수원시 800
 
1.7%
화성시 769
 
1.6%
성남시 699
 
1.5%
남양주시 623
 
1.3%
김포시 463
 
1.0%
분당구 448
 
1.0%
평택시 443
 
0.9%
Other values (4541) 30802
66.0%
2024-03-13T08:31:08.596539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36731
18.5%
기 10611
 
5.3%
시 10609
 
5.3%
경 10314
 
5.2%
도 10255
 
5.2%
로 9308
 
4.7%
1 7091
 
3.6%
2 4866
 
2.4%
구 4196
 
2.1%
3 3501
 
1.8%
Other values (480) 91328
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125217
63.0%
Space Separator 36731
 
18.5%
Decimal Number 33975
 
17.1%
Dash Punctuation 1296
 
0.7%
Open Punctuation 522
 
0.3%
Close Punctuation 522
 
0.3%
Other Punctuation 403
 
0.2%
Uppercase Letter 93
 
< 0.1%
Math Symbol 32
 
< 0.1%
Lowercase Letter 19
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 10611
 
8.5%
시 10609
 
8.5%
경 10314
 
8.2%
도 10255
 
8.2%
로 9308
 
7.4%
구 4196
 
3.4%
양 2850
 
2.3%
길 2784
 
2.2%
동 2607
 
2.1%
남 2178
 
1.7%
Other values (440) 59505
47.5%
Uppercase Letter
ValueCountFrequency (%)
K 31
33.3%
T 30
32.3%
B 12
 
12.9%
L 5
 
5.4%
H 3
 
3.2%
S 2
 
2.2%
E 2
 
2.2%
P 2
 
2.2%
C 1
 
1.1%
M 1
 
1.1%
Other values (4) 4
 
4.3%
Decimal Number
ValueCountFrequency (%)
1 7091
20.9%
2 4866
14.3%
3 3501
10.3%
5 3074
9.0%
0 2915
8.6%
4 2861
8.4%
6 2779
 
8.2%
7 2679
 
7.9%
9 2113
 
6.2%
8 2096
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
e 5
26.3%
a 4
21.1%
t 2
 
10.5%
u 2
 
10.5%
l 2
 
10.5%
z 2
 
10.5%
h 1
 
5.3%
k 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 391
97.0%
. 7
 
1.7%
？ 5
 
1.2%
Space Separator
ValueCountFrequency (%)
36731
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1296
100.0%
Open Punctuation
ValueCountFrequency (%)
( 522
100.0%
Close Punctuation
ValueCountFrequency (%)
) 522
100.0%
Math Symbol
ValueCountFrequency (%)
~ 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125217
63.0%
Common 73481
37.0%
Latin 112
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 10611
 
8.5%
시 10609
 
8.5%
경 10314
 
8.2%
도 10255
 
8.2%
로 9308
 
7.4%
구 4196
 
3.4%
양 2850
 
2.3%
길 2784
 
2.2%
동 2607
 
2.1%
남 2178
 
1.7%
Other values (440) 59505
47.5%
Latin
ValueCountFrequency (%)
K 31
27.7%
T 30
26.8%
B 12
 
10.7%
L 5
 
4.5%
e 5
 
4.5%
a 4
 
3.6%
H 3
 
2.7%
S 2
 
1.8%
t 2
 
1.8%
E 2
 
1.8%
Other values (12) 16
14.3%
Common
ValueCountFrequency (%)
36731
50.0%
1 7091
 
9.7%
2 4866
 
6.6%
3 3501
 
4.8%
5 3074
 
4.2%
0 2915
 
4.0%
4 2861
 
3.9%
6 2779
 
3.8%
7 2679
 
3.6%
9 2113
 
2.9%
Other values (8) 4871
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125217
63.0%
ASCII 73588
37.0%
None 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36731
49.9%
1 7091
 
9.6%
2 4866
 
6.6%
3 3501
 
4.8%
5 3074
 
4.2%
0 2915
 
4.0%
4 2861
 
3.9%
6 2779
 
3.8%
7 2679
 
3.6%
9 2113
 
2.9%
Other values (29) 4978
 
6.8%
Hangul
ValueCountFrequency (%)
기 10611
 
8.5%
시 10609
 
8.5%
경 10314
 
8.2%
도 10255
 
8.2%
로 9308
 
7.4%
구 4196
 
3.4%
양 2850
 
2.3%
길 2784
 
2.2%
동 2607
 
2.1%
남 2178
 
1.7%
Other values (440) 59505
47.5%
None
ValueCountFrequency (%)
？ 5
100.0%

관리업체명
Text

Distinct91
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T08:31:08.794123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length5.1392
Min length2

Characters and Unicode

Total characters51392
Distinct characters167
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)0.1%

Sample

1st row에버온
2nd row한국전기차충전서비스
3rd row플러그링크
4th row휴맥스이브이
5th row에버온
ValueCountFrequency (%)
에버온 1546
 
14.8%
차지비 823
 
7.9%
플러그링크 735
 
7.1%
지에스커넥트 709
 
6.8%
홈앤서비스 474
 
4.6%
휴맥스이브이 447
 
4.3%
지커넥트 418
 
4.0%
이지차저 405
 
3.9%
한국전자금융 360
 
3.5%
파워큐브 343
 
3.3%
Other values (86) 4153
39.9%
2024-03-13T08:31:09.087908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 2744
 
5.3%
스 2635
 
5.1%
에 2303
 
4.5%
이 2250
 
4.4%
비 1994
 
3.9%
차 1826
 
3.6%
온 1558
 
3.0%
버 1547
 
3.0%
전 1462
 
2.8%
트 1331
 
2.6%
Other values (157) 31742
61.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47581
92.6%
Uppercase Letter 2262
 
4.4%
Close Punctuation 547
 
1.1%
Open Punctuation 547
 
1.1%
Space Separator 413
 
0.8%
Decimal Number 18
 
< 0.1%
Lowercase Letter 15
 
< 0.1%
Dash Punctuation 7
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 2744
 
5.8%
스 2635
 
5.5%
에 2303
 
4.8%
이 2250
 
4.7%
비 1994
 
4.2%
차 1826
 
3.8%
온 1558
 
3.3%
버 1547
 
3.3%
전 1462
 
3.1%
트 1331
 
2.8%
Other values (128) 27931
58.7%
Uppercase Letter
ValueCountFrequency (%)
S 310
13.7%
G 288
12.7%
E 217
9.6%
V 211
9.3%
A 194
8.6%
X 194
8.6%
H 194
8.6%
U 194
8.6%
M 194
8.6%
P 137
6.1%
Other values (6) 129
5.7%
Decimal Number
ValueCountFrequency (%)
1 6
33.3%
3 4
22.2%
8 4
22.2%
0 2
 
11.1%
7 2
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
t 5
33.3%
i 5
33.3%
p 5
33.3%
Close Punctuation
ValueCountFrequency (%)
) 547
100.0%
Open Punctuation
ValueCountFrequency (%)
( 547
100.0%
Space Separator
ValueCountFrequency (%)
413
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47583
92.6%
Latin 2277
 
4.4%
Common 1532
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 2744
 
5.8%
스 2635
 
5.5%
에 2303
 
4.8%
이 2250
 
4.7%
비 1994
 
4.2%
차 1826
 
3.8%
온 1558
 
3.3%
버 1547
 
3.3%
전 1462
 
3.1%
트 1331
 
2.8%
Other values (129) 27933
58.7%
Latin
ValueCountFrequency (%)
S 310
13.6%
G 288
12.6%
E 217
9.5%
V 211
9.3%
A 194
8.5%
X 194
8.5%
H 194
8.5%
U 194
8.5%
M 194
8.5%
P 137
6.0%
Other values (9) 144
6.3%
Common
ValueCountFrequency (%)
) 547
35.7%
( 547
35.7%
413
27.0%
- 7
 
0.5%
1 6
 
0.4%
3 4
 
0.3%
8 4
 
0.3%
0 2
 
0.1%
7 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47581
92.6%
ASCII 3809
 
7.4%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 2744
 
5.8%
스 2635
 
5.5%
에 2303
 
4.8%
이 2250
 
4.7%
비 1994
 
4.2%
차 1826
 
3.8%
온 1558
 
3.3%
버 1547
 
3.3%
전 1462
 
3.1%
트 1331
 
2.8%
Other values (128) 27931
58.7%
ASCII
ValueCountFrequency (%)
) 547
14.4%
( 547
14.4%
413
10.8%
S 310
8.1%
G 288
7.6%
E 217
 
5.7%
V 211
 
5.5%
A 194
 
5.1%
X 194
 
5.1%
H 194
 
5.1%
Other values (18) 694
18.2%
None
ValueCountFrequency (%)
㈜ 2
100.0%

관리업체전화번호
Text

MISSING 

Distinct111
Distinct (%)1.1%
Missing184
Missing (%)1.8%
Memory size156.2 KiB
2024-03-13T08:31:09.283763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length9
Mean length9.0295436
Min length4

Characters and Unicode

Total characters88634
Distinct characters47
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)0.3%

Sample

1st row1661-7766
2nd row1522-1782
3rd row1533-0702
4th row1800-3188
5th row1661-7766
ValueCountFrequency (%)
1661-7766 1546
15.7%
1544-4279 1219
12.4%
1600-4047 820
 
8.3%
1533-0702 735
 
7.5%
1833-8017 599
 
6.1%
1800-3188 574
 
5.8%
16700-119 426
 
4.3%
1533-2522 419
 
4.3%
1544-3332 411
 
4.2%
1522-2573 295
 
3.0%
Other values (104) 2783
28.3%
2024-03-13T08:31:09.595003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15168
17.1%
7 9715
11.0%
- 9690
10.9%
6 9413
10.6%
0 8400
9.5%
3 8066
9.1%
4 7565
8.5%
5 6306
7.1%
2 5690
 
6.4%
8 5176
 
5.8%
Other values (37) 3445
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78848
89.0%
Dash Punctuation 9690
 
10.9%
Other Letter 44
 
< 0.1%
Other Punctuation 39
 
< 0.1%
Space Separator 11
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 2
 
4.5%
장 2
 
4.5%
차 2
 
4.5%
주 2
 
4.5%
큐 2
 
4.5%
워 2
 
4.5%
브 2
 
4.5%
러 2
 
4.5%
이 2
 
4.5%
카 2
 
4.5%
Other values (22) 24
54.5%
Decimal Number
ValueCountFrequency (%)
1 15168
19.2%
7 9715
12.3%
6 9413
11.9%
0 8400
10.7%
3 8066
10.2%
4 7565
9.6%
5 6306
8.0%
2 5690
 
7.2%
8 5176
 
6.6%
9 3349
 
4.2%
Other Punctuation
ValueCountFrequency (%)
* 33
84.6%
. 6
 
15.4%
Dash Punctuation
ValueCountFrequency (%)
- 9690
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88590
> 99.9%
Hangul 44
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 2
 
4.5%
장 2
 
4.5%
차 2
 
4.5%
주 2
 
4.5%
큐 2
 
4.5%
워 2
 
4.5%
브 2
 
4.5%
러 2
 
4.5%
이 2
 
4.5%
카 2
 
4.5%
Other values (22) 24
54.5%
Common
ValueCountFrequency (%)
1 15168
17.1%
7 9715
11.0%
- 9690
10.9%
6 9413
10.6%
0 8400
9.5%
3 8066
9.1%
4 7565
8.5%
5 6306
7.1%
2 5690
 
6.4%
8 5176
 
5.8%
Other values (5) 3401
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88590
> 99.9%
Hangul 44
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15168
17.1%
7 9715
11.0%
- 9690
10.9%
6 9413
10.6%
0 8400
9.5%
3 8066
9.1%
4 7565
8.5%
5 6306
7.1%
2 5690
 
6.4%
8 5176
 
5.8%
Other values (5) 3401
 
3.8%
Hangul
ValueCountFrequency (%)
파 2
 
4.5%
장 2
 
4.5%
차 2
 
4.5%
주 2
 
4.5%
큐 2
 
4.5%
워 2
 
4.5%
브 2
 
4.5%
러 2
 
4.5%
이 2
 
4.5%
카 2
 
4.5%
Other values (22) 24
54.5%

위도
Real number (ℝ)

Distinct5902
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.42708
Minimum33
Maximum38.98209
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T08:31:09.710969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33
5-th percentile37.036717
Q137.27658
median37.389931
Q337.6384
95-th percentile37.772943
Maximum38.98209
Range5.98209
Interquartile range (IQR)0.36182012

Descriptive statistics

Standard deviation0.23981944
Coefficient of variation (CV)0.006407645
Kurtosis20.285319
Mean37.42708
Median Absolute Deviation (MAD)0.1582959
Skewness-1.5093244
Sum374270.8
Variance0.057513364
MonotonicityNot monotonic
2024-03-13T08:31:09.855927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.564386 23
 
0.2%
37.01775728 23
 
0.2%
37.6074172 20
 
0.2%
37.0540708 19
 
0.2%
37.5455 16
 
0.2%
37.6471 16
 
0.2%
37.62015536 16
 
0.2%
37.6416942 16
 
0.2%
37.3642 16
 
0.2%
37.244658628 15
 
0.1%
Other values (5892) 9820
98.2%
ValueCountFrequency (%)
33.0 1
 
< 0.1%
35.0108191 1
 
< 0.1%
35.0174778 4
< 0.1%
35.0176686 2
< 0.1%
35.1244671 1
 
< 0.1%
35.16406769 1
 
< 0.1%
35.5757833 1
 
< 0.1%
35.8088267 1
 
< 0.1%
36.1286084 3
< 0.1%
36.2245029 2
< 0.1%
ValueCountFrequency (%)
38.98209 1
< 0.1%
38.107122692 1
< 0.1%
38.106265599 1
< 0.1%
38.1015919 1
< 0.1%
38.0990795 1
< 0.1%
38.0983603 1
< 0.1%
38.09811034 1
< 0.1%
38.08474219 1
< 0.1%
38.077284 2
< 0.1%
38.0760751 2
< 0.1%

경도
Real number (ℝ)

Distinct5904
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.01069
Minimum125
Maximum129.30456
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T08:31:09.979888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum125
5-th percentile126.72381
Q1126.83422
median127.05387
Q3127.12143
95-th percentile127.29921
Maximum129.30456
Range4.3045637
Interquartile range (IQR)0.28720353

Descriptive statistics

Standard deviation0.19681004
Coefficient of variation (CV)0.001549555
Kurtosis4.1420659
Mean127.01069
Median Absolute Deviation (MAD)0.11827855
Skewness0.44037497
Sum1270106.9
Variance0.038734194
MonotonicityNot monotonic
2024-03-13T08:31:10.085121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0919213 23
 
0.2%
127.19416 23
 
0.2%
126.7322886 20
 
0.2%
127.0414263 19
 
0.2%
126.7124 16
 
0.2%
126.8948 16
 
0.2%
127.1522666 16
 
0.2%
127.2236 16
 
0.2%
126.8342239 16
 
0.2%
127.12151533 15
 
0.1%
Other values (5894) 9820
98.2%
ValueCountFrequency (%)
125.0 1
 
< 0.1%
126.5522059537 1
 
< 0.1%
126.558782 1
 
< 0.1%
126.56094525 3
< 0.1%
126.5609453 1
 
< 0.1%
126.5815031 1
 
< 0.1%
126.58181339999 1
 
< 0.1%
126.587739 1
 
< 0.1%
126.5927886 1
 
< 0.1%
126.5929629 1
 
< 0.1%
ValueCountFrequency (%)
129.3045637 1
 
< 0.1%
128.82432259 1
 
< 0.1%
128.3179478 3
< 0.1%
127.7506485 1
 
< 0.1%
127.7310347 1
 
< 0.1%
127.7265926 3
< 0.1%
127.72659256 2
< 0.1%
127.7240649 2
< 0.1%
127.722636 1
 
< 0.1%
127.7201378 2
< 0.1%

충전소ID
Text

Distinct6173
Distinct (%)61.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T08:31:10.333177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters80000
Distinct characters35
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4180 ?
Unique (%)41.8%

Sample

1st rowEV010476
2nd rowHE000181
3rd rowPL100149
4th rowHM001304
5th rowEV001462
ValueCountFrequency (%)
pl005175 23
 
0.2%
pc000175 23
 
0.2%
pl100068 20
 
0.2%
pl000813 19
 
0.2%
in031042 16
 
0.2%
pl005354 16
 
0.2%
in031080 16
 
0.2%
in031081 16
 
0.2%
pl000428 15
 
0.1%
hsh01219 15
 
0.1%
Other values (6163) 9821
98.2%
2024-03-13T08:31:10.885606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21466
26.8%
1 8599
10.7%
2 5389
 
6.7%
3 5007
 
6.3%
6 3425
 
4.3%
4 3407
 
4.3%
5 3288
 
4.1%
P 3031
 
3.8%
8 2967
 
3.7%
E 2955
 
3.7%
Other values (25) 20466
25.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59211
74.0%
Uppercase Letter 20789
 
26.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 3031
14.6%
E 2955
14.2%
H 2027
9.8%
N 2005
9.6%
V 1847
8.9%
G 1331
 
6.4%
L 1221
 
5.9%
I 1151
 
5.5%
C 945
 
4.5%
M 867
 
4.2%
Other values (15) 3409
16.4%
Decimal Number
ValueCountFrequency (%)
0 21466
36.3%
1 8599
14.5%
2 5389
 
9.1%
3 5007
 
8.5%
6 3425
 
5.8%
4 3407
 
5.8%
5 3288
 
5.6%
8 2967
 
5.0%
7 2844
 
4.8%
9 2819
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common 59211
74.0%
Latin 20789
 
26.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 3031
14.6%
E 2955
14.2%
H 2027
9.8%
N 2005
9.6%
V 1847
8.9%
G 1331
 
6.4%
L 1221
 
5.9%
I 1151
 
5.5%
C 945
 
4.5%
M 867
 
4.2%
Other values (15) 3409
16.4%
Common
ValueCountFrequency (%)
0 21466
36.3%
1 8599
14.5%
2 5389
 
9.1%
3 5007
 
8.5%
6 3425
 
5.8%
4 3407
 
5.8%
5 3288
 
5.6%
8 2967
 
5.0%
7 2844
 
4.8%
9 2819
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21466
26.8%
1 8599
10.7%
2 5389
 
6.7%
3 5007
 
6.3%
6 3425
 
4.3%
4 3407
 
4.3%
5 3288
 
4.1%
P 3031
 
3.8%
8 2967
 
3.7%
E 2955
 
3.7%
Other values (25) 20466
25.6%

충전기ID
Real number (ℝ)

Distinct94
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4584
Minimum0
Maximum97
Zeros15
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T08:31:11.022260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q38
95-th percentile29
Maximum97
Range97
Interquartile range (IQR)6

Descriptive statistics

Standard deviation11.411568
Coefficient of variation (CV)1.530029
Kurtosis16.856295
Mean7.4584
Median Absolute Deviation (MAD)2
Skewness3.666423
Sum74584
Variance130.22389
MonotonicityNot monotonic
2024-03-13T08:31:11.182331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2229
22.3%
2 1775
17.8%
3 1132
11.3%
4 783
 
7.8%
5 618
 
6.2%
6 457
 
4.6%
7 325
 
3.2%
8 278
 
2.8%
9 257
 
2.6%
11 233
 
2.3%
Other values (84) 1913
19.1%
ValueCountFrequency (%)
0 15
 
0.1%
1 2229
22.3%
2 1775
17.8%
3 1132
11.3%
4 783
 
7.8%
5 618
 
6.2%
6 457
 
4.6%
7 325
 
3.2%
8 278
 
2.8%
9 257
 
2.6%
ValueCountFrequency (%)
97 1
 
< 0.1%
96 3
< 0.1%
94 3
< 0.1%
93 1
 
< 0.1%
92 3
< 0.1%
91 7
0.1%
90 2
 
< 0.1%
89 2
 
< 0.1%
87 1
 
< 0.1%
86 1
 
< 0.1%

충전기용량
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct18
Distinct (%)0.2%
Missing428
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean15.425512
Minimum3
Maximum360
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T08:31:11.324123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile7
Q17
median7
Q37
95-th percentile100
Maximum360
Range357
Interquartile range (IQR)0

Descriptive statistics

Standard deviation32.45174
Coefficient of variation (CV)2.1037707
Kurtosis33.880096
Mean15.425512
Median Absolute Deviation (MAD)0
Skewness5.2518622
Sum147653
Variance1053.1154
MonotonicityNot monotonic
2024-03-13T08:31:11.435962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
7 8198
82.0%
100 347
 
3.5%
50 268
 
2.7%
11 203
 
2.0%
3 181
 
1.8%
14 125
 
1.2%
200 93
 
0.9%
120 57
 
0.6%
30 44
 
0.4%
25 13
 
0.1%
Other values (8) 43
 
0.4%
(Missing) 428
 
4.3%
ValueCountFrequency (%)
3 181
 
1.8%
7 8198
82.0%
11 203
 
2.0%
14 125
 
1.2%
22 8
 
0.1%
25 13
 
0.1%
30 44
 
0.4%
50 268
 
2.7%
100 347
 
3.5%
120 57
 
0.6%
ValueCountFrequency (%)
360 2
 
< 0.1%
350 8
 
0.1%
320 5
 
0.1%
300 8
 
0.1%
260 8
 
0.1%
240 2
 
< 0.1%
200 93
 
0.9%
150 2
 
< 0.1%
120 57
 
0.6%
100 347
3.5%

기관ID
Text

Distinct58
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T08:31:11.593794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters20000
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowEV
2nd rowHE
3rd rowPL
4th rowHM
5th rowEV
ValueCountFrequency (%)
ev 1547
15.5%
gn 1290
12.9%
pi 827
 
8.3%
pl 735
 
7.3%
hm 641
 
6.4%
pw 606
 
6.1%
hs 474
 
4.7%
nt 419
 
4.2%
ec 411
 
4.1%
kp 369
 
3.7%
Other values (48) 2681
26.8%
2024-03-13T08:31:11.855394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 3023
15.1%
E 2935
14.7%
N 1998
10.0%
V 1844
9.2%
H 1553
7.8%
G 1322
6.6%
L 1212
 
6.1%
I 1148
 
5.7%
C 907
 
4.5%
M 867
 
4.3%
Other values (13) 3191
16.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 20000
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 3023
15.1%
E 2935
14.7%
N 1998
10.0%
V 1844
9.2%
H 1553
7.8%
G 1322
6.6%
L 1212
 
6.1%
I 1148
 
5.7%
C 907
 
4.5%
M 867
 
4.3%
Other values (13) 3191
16.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 3023
15.1%
E 2935
14.7%
N 1998
10.0%
V 1844
9.2%
H 1553
7.8%
G 1322
6.6%
L 1212
 
6.1%
I 1148
 
5.7%
C 907
 
4.5%
M 867
 
4.3%
Other values (13) 3191
16.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 3023
15.1%
E 2935
14.7%
N 1998
10.0%
V 1844
9.2%
H 1553
7.8%
G 1322
6.6%
L 1212
 
6.1%
I 1148
 
5.7%
C 907
 
4.5%
M 867
 
4.3%
Other values (13) 3191
16.0%

상태갱신일자
Real number (ℝ)

MISSING 

Distinct6932
Distinct (%)72.6%
Missing448
Missing (%)4.5%
Infinite0
Infinite (%)0.0%
Mean2.0236446 × 1013
Minimum2.0200326 × 1013
Maximum2.0240102 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T08:31:11.970567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0200326 × 1013
5-th percentile2.0231212 × 1013
Q12.0231229 × 1013
median2.0240101 × 1013
Q32.0240102 × 1013
95-th percentile2.0240102 × 1013
Maximum2.0240102 × 1013
Range3.9776003 × 1010
Interquartile range (IQR)8.8731112 × 109

Descriptive statistics

Standard deviation4.5325079 × 109
Coefficient of variation (CV)0.00022397746
Kurtosis-0.29832689
Mean2.0236446 × 1013
Median Absolute Deviation (MAD)950939.5
Skewness-0.64899031
Sum1.9329854 × 1017
Variance2.0543628 × 1019
MonotonicityNot monotonic
2024-03-13T08:31:12.123774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20240102152810 498
 
5.0%
20240102152310 307
 
3.1%
20240102151310 277
 
2.8%
20240102151810 212
 
2.1%
20240102150810 208
 
2.1%
20240102104810 36
 
0.4%
20231229202137 28
 
0.3%
20231226154252 25
 
0.2%
20231212164057 24
 
0.2%
20231226154251 21
 
0.2%
Other values (6922) 7916
79.2%
(Missing) 448
 
4.5%
ValueCountFrequency (%)
20200326150310 1
 
< 0.1%
20200724131310 1
 
< 0.1%
20210722060810 1
 
< 0.1%
20210731174810 1
 
< 0.1%
20220208162310 1
 
< 0.1%
20220318113810 1
 
< 0.1%
20220421151810 1
 
< 0.1%
20220711104810 1
 
< 0.1%
20220805172310 3
< 0.1%
20220828034310 1
 
< 0.1%
ValueCountFrequency (%)
20240102153324 1
 
< 0.1%
20240102153306 1
 
< 0.1%
20240102153214 1
 
< 0.1%
20240102153209 1
 
< 0.1%
20240102153200 3
< 0.1%
20240102153159 4
< 0.1%
20240102153124 1
 
< 0.1%
20240102153123 1
 
< 0.1%
20240102153109 1
 
< 0.1%
20240102153101 1
 
< 0.1%

데이터기준일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Interactions

2024-03-13T08:31:05.515590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:01.864154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:02.430400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:02.985395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:03.565624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:04.119324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:04.921181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:05.618948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:01.943583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:02.520331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:03.062372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:03.649182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:04.220850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:05.002044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:05.706659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:02.021463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:02.609176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:03.140822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:03.727190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:04.318794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:05.091177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:05.794654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:02.096063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:02.684642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:03.217962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:03.802785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:04.398246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:05.169485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:05.872979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:02.189481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:02.752515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:03.299477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:03.871829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:04.674541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:05.246110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:05.952358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:02.262488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:02.825548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:03.393602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:03.938657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:04.745725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:05.323886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:06.038433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:02.341217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:02.901072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:03.481031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:04.019255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:04.836119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:31:05.412393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:31:12.223452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
충전기상태충전기타입관리업체명위도경도충전기ID충전기용량기관ID상태갱신일자
충전기상태1.0000.0590.7830.0430.0330.1590.1330.7740.462
충전기타입0.0591.0000.7180.1090.0570.1080.7260.6990.118
관리업체명0.7830.7181.0000.2350.2570.4770.9411.0000.512
위도0.0430.1090.2351.0000.9120.1370.0710.2120.053
경도0.0330.0570.2570.9121.0000.1440.0560.2290.000
충전기ID0.1590.1080.4770.1370.1441.0000.2650.4610.112
충전기용량0.1330.7260.9410.0710.0560.2651.0000.9040.061
기관ID0.7740.6991.0000.2120.2290.4610.9041.0000.492
상태갱신일자0.4620.1180.5120.0530.0000.1120.0610.4921.000
2024-03-13T08:31:12.317885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
충전기상태충전기타입위도경도충전기ID충전기용량상태갱신일자
충전기상태1.0000.025-0.006-0.010-0.1450.0210.489
충전기타입0.0251.000-0.0260.013-0.0900.7970.058
위도-0.006-0.0261.000-0.188-0.0130.006-0.008
경도-0.0100.013-0.1881.000-0.049-0.0050.015
충전기ID-0.145-0.090-0.013-0.0491.000-0.098-0.213
충전기용량0.0210.7970.006-0.005-0.0981.0000.086
상태갱신일자0.4890.058-0.0080.015-0.2130.0861.000

Missing values

2024-03-13T08:31:06.170858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:31:06.328930image/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.
2024-03-13T08:31:06.443504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

충전소명이용가능시간충전기상태충전기타입소재지도로명주소관리업체명관리업체전화번호위도경도충전소ID충전기ID충전기용량기관ID상태갱신일자데이터기준일자
15913경기화성 동탄시범반도유보라아이비파크아파트424시간 이용가능92경기도 화성시 동탄대로시범길 168에버온1661-776637.202598127.111191EV01047667EV20240102152310<NA>
24122부천체육관24시간 이용가능26경기도 부천시 석천로한국전기차충전서비스1522-178237.514703126.763746HE000181150HE20240102152622<NA>
54811양주옥정신도시 제일풍경채레이크시티1단지24시간 이용가능92경기 양주시 옥정동 1043플러그링크1533-070237.825702127.100605PL100149587PL<NA><NA>
28105경기남부보훈지청24시간 이용가능22경기도 수원시 장안구 조원로 8휴맥스이브이1800-318837.295865127.02264HM00130417HM20240102130618<NA>
9277신원마을5단지삼송우림필유124시간 이용가능,입주민만 사용가능 거주자외출입제한92경기도 고양시 덕양구 신원로 55 (신원동, 신원마을5단지 우림필유아파트)에버온1661-776637.665213126.886241EV0014623<NA>EV20240102152810<NA>
36893럭스나인은계오피스텔24시간 이용가능22경기도 시흥시 은계중앙로 247홈앤서비스16700-11937.445865126.80325HSH0036877HS20240102112612<NA>
16834민락청구1차08:00~20:0022경기도 의정부시 오목로 110지커넥트1544427937.737392127.093004GN00818527GN20231229181154<NA>
47078석수아이파크<NA>26경기도 안양시 만안구 석수동 충훈로 51한국전기차충전서비스<NA>37.405684126.902251KP0013221<NA>KP20240101175402<NA>
56657성남분당SG타워24시간 이용가능22경기도 성남시 분당구 대왕판교로606번길 47플러그링크1533-070237.396934127.112532PL00041717PL20240102114104<NA>
8551중동대림아파트24시간 이용가능,입주민만 사용가능 거주자외출입제한92경기도 부천시 계남로 261 (중동, 중동대림아파트)에버온1661-776637.506671126.778578EV0017281<NA>EV20240102152810<NA>
충전소명이용가능시간충전기상태충전기타입소재지도로명주소관리업체명관리업체전화번호위도경도충전소ID충전기ID충전기용량기관ID상태갱신일자데이터기준일자
25612부천시_소사본3주민지원센터평일 09:00~18:0022경기도 부천시 은성로68번길 56한국전기차충전서비스1522-178237.4727126.798HE00038217HE20240102150622<NA>
46121청산면사무소(100kw)24시간 이용가능24경기도 연천군 청산면 청신로 71한국전력1899-210037.98209127.06772KP0046201100KP20240102131504<NA>
4236송정신일아파트 101동 뒤편 지상주차장24시간 이용가능22경기도 이천시 증신로291번길 149이지차저1544-333237.295687127.432432EC00032827EC20231231104005<NA>
25201율정마을8단지24시간 이용가능22경기도 양주시 옥정동로 258지에스커넥트1544-427937.830948127.099485GN01092197GN20240102132150<NA>
5485고현아이파크 101동 지하1층주차장 02기둥24시간 이용가능22경기도 오산시 남부대로 430-12이지차저1544-333237.133942127.081287EC004439211EC20240102095427<NA>
34202휴먼시아하늘빛마을24시간 이용가능52경기도 양주시 고암길 223신세계아이앤씨1899-749537.8336127.0737IN03111157IN20231229182128<NA>
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