Overview

Dataset statistics

Number of variables10
Number of observations500
Missing cells495
Missing cells (%)9.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory40.7 KiB
Average record size in memory83.3 B

Variable types

Text4
Categorical4
Boolean1
Numeric1

Dataset

Description해당 파일 데이터는 신용보증기금의 고객기타정보고객세무사관계에 대한 정보를 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15093110/fileData.do

Alerts

고객세무사회계사관계코드 has constant value ""Constant
삭제여부 has constant value ""Constant
사무소담당자전화번호 is highly overall correlated with 사무소담당자휴대폰번호High correlation
사무소담당자휴대폰번호 is highly overall correlated with 사무소담당자전화번호High correlation
사무소담당자전화번호 is highly imbalanced (84.3%)Imbalance
사무소담당자휴대폰번호 is highly imbalanced (91.5%)Imbalance
최종수정수 is highly imbalanced (70.0%)Imbalance
사무소담당자이메일 has 495 (99.0%) missing valuesMissing
고객아이디(ID) has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:03:35.556436
Analysis finished2023-12-12 08:03:36.508520
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고객아이디(ID)
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T17:03:36.783389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters5000
Distinct characters62
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique500 ?
Unique (%)100.0%

Sample

1st row9b6FkYxlLn
2nd row9dnAtcpIHp
3rd row9b9djdJvTG
4th row9bnM1hpqkD
5th row9cNTe1Ty2w
ValueCountFrequency (%)
9b6fkyxlln 1
 
0.2%
9bydhou8wn 1
 
0.2%
9dnjhmvif1 1
 
0.2%
9ddvvglzec 1
 
0.2%
9c41dr6tvi 1
 
0.2%
9bhe16hwoy 1
 
0.2%
9czxefe9wo 1
 
0.2%
9dlabqisy6 1
 
0.2%
9dfkcrx6zr 1
 
0.2%
9dnqj8kfpr 1
 
0.2%
Other values (490) 490
98.0%
2023-12-12T17:03:37.321895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 527
 
10.5%
d 361
 
7.2%
a 234
 
4.7%
c 220
 
4.4%
n 207
 
4.1%
m 105
 
2.1%
b 96
 
1.9%
B 76
 
1.5%
q 75
 
1.5%
y 75
 
1.5%
Other values (52) 3024
60.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2425
48.5%
Uppercase Letter 1524
30.5%
Decimal Number 1051
21.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 361
 
14.9%
a 234
 
9.6%
c 220
 
9.1%
n 207
 
8.5%
m 105
 
4.3%
b 96
 
4.0%
q 75
 
3.1%
y 75
 
3.1%
l 71
 
2.9%
k 68
 
2.8%
Other values (16) 913
37.6%
Uppercase Letter
ValueCountFrequency (%)
B 76
 
5.0%
J 70
 
4.6%
D 69
 
4.5%
S 68
 
4.5%
V 66
 
4.3%
X 64
 
4.2%
N 62
 
4.1%
C 62
 
4.1%
A 61
 
4.0%
M 61
 
4.0%
Other values (16) 865
56.8%
Decimal Number
ValueCountFrequency (%)
9 527
50.1%
6 74
 
7.0%
2 64
 
6.1%
1 63
 
6.0%
4 62
 
5.9%
0 59
 
5.6%
5 59
 
5.6%
8 56
 
5.3%
7 49
 
4.7%
3 38
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 3949
79.0%
Common 1051
 
21.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 361
 
9.1%
a 234
 
5.9%
c 220
 
5.6%
n 207
 
5.2%
m 105
 
2.7%
b 96
 
2.4%
B 76
 
1.9%
q 75
 
1.9%
y 75
 
1.9%
l 71
 
1.8%
Other values (42) 2429
61.5%
Common
ValueCountFrequency (%)
9 527
50.1%
6 74
 
7.0%
2 64
 
6.1%
1 63
 
6.0%
4 62
 
5.9%
0 59
 
5.6%
5 59
 
5.6%
8 56
 
5.3%
7 49
 
4.7%
3 38
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 527
 
10.5%
d 361
 
7.2%
a 234
 
4.7%
c 220
 
4.4%
n 207
 
4.1%
m 105
 
2.1%
b 96
 
1.9%
B 76
 
1.5%
q 75
 
1.5%
y 75
 
1.5%
Other values (52) 3024
60.5%

고객세무사회계사관계코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
101
500 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row101
2nd row101
3rd row101
4th row101
5th row101

Common Values

ValueCountFrequency (%)
101 500
100.0%

Length

2023-12-12T17:03:37.853725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:03:37.949270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
101 500
100.0%

세무사회계사아이디(ID)
Text

Distinct486
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T17:03:38.190225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters5000
Distinct characters62
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique472 ?
Unique (%)94.4%

Sample

1st row9bnEWvjXzQ
2nd row9bnEWvhYUS
3rd row9cRTqjQv8Z
4th row9buGByzGqA
5th row9cZBkv1TBZ
ValueCountFrequency (%)
9cmymveofv 2
 
0.4%
9dnoa5t5gc 2
 
0.4%
9c87pxsvox 2
 
0.4%
9cq2gnggnw 2
 
0.4%
9b6afar985 2
 
0.4%
9bxjajfhve 2
 
0.4%
9djqy0jsfx 2
 
0.4%
9ccnv7wcrw 2
 
0.4%
9c1lfsqx0d 2
 
0.4%
9btsr967jn 2
 
0.4%
Other values (476) 480
96.0%
2023-12-12T17:03:38.591250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 551
 
11.0%
b 248
 
5.0%
c 245
 
4.9%
n 204
 
4.1%
d 193
 
3.9%
v 164
 
3.3%
E 157
 
3.1%
W 149
 
3.0%
r 74
 
1.5%
Z 73
 
1.5%
Other values (52) 2942
58.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2277
45.5%
Uppercase Letter 1666
33.3%
Decimal Number 1057
21.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
b 248
 
10.9%
c 245
 
10.8%
n 204
 
9.0%
d 193
 
8.5%
v 164
 
7.2%
r 74
 
3.2%
t 71
 
3.1%
f 69
 
3.0%
z 65
 
2.9%
j 64
 
2.8%
Other values (16) 880
38.6%
Uppercase Letter
ValueCountFrequency (%)
E 157
 
9.4%
W 149
 
8.9%
Z 73
 
4.4%
S 71
 
4.3%
O 71
 
4.3%
H 66
 
4.0%
A 64
 
3.8%
C 63
 
3.8%
B 63
 
3.8%
K 60
 
3.6%
Other values (16) 829
49.8%
Decimal Number
ValueCountFrequency (%)
9 551
52.1%
0 70
 
6.6%
2 68
 
6.4%
8 62
 
5.9%
6 59
 
5.6%
3 54
 
5.1%
1 50
 
4.7%
7 49
 
4.6%
4 47
 
4.4%
5 47
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 3943
78.9%
Common 1057
 
21.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
b 248
 
6.3%
c 245
 
6.2%
n 204
 
5.2%
d 193
 
4.9%
v 164
 
4.2%
E 157
 
4.0%
W 149
 
3.8%
r 74
 
1.9%
Z 73
 
1.9%
t 71
 
1.8%
Other values (42) 2365
60.0%
Common
ValueCountFrequency (%)
9 551
52.1%
0 70
 
6.6%
2 68
 
6.4%
8 62
 
5.9%
6 59
 
5.6%
3 54
 
5.1%
1 50
 
4.7%
7 49
 
4.6%
4 47
 
4.4%
5 47
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 551
 
11.0%
b 248
 
5.0%
c 245
 
4.9%
n 204
 
4.1%
d 193
 
3.9%
v 164
 
3.3%
E 157
 
3.1%
W 149
 
3.0%
r 74
 
1.5%
Z 73
 
1.5%
Other values (52) 2942
58.8%

사무소담당자전화번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct42
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
AAFDk2mgRCGK0tkuJ2UqjjHi
459 
AAHETolVAkPcgVkHD9acyV3M
 
1
AAFfQHKWkbvI14ehDjtotfcl
 
1
AAFCkglzyMCDBjj36ZeuvQZl
 
1
AAG8ynjrgoYUVB+dXMDlVrm5
 
1
Other values (37)
 
37

Length

Max length24
Median length24
Mean length24
Min length24

Unique

Unique41 ?
Unique (%)8.2%

Sample

1st rowAAFDk2mgRCGK0tkuJ2UqjjHi
2nd rowAAFDk2mgRCGK0tkuJ2UqjjHi
3rd rowAAFmEbODBeanBpxTiW4GPnLW
4th rowAAFDk2mgRCGK0tkuJ2UqjjHi
5th rowAAFDk2mgRCGK0tkuJ2UqjjHi

Common Values

ValueCountFrequency (%)
AAFDk2mgRCGK0tkuJ2UqjjHi 459
91.8%
AAHETolVAkPcgVkHD9acyV3M 1
 
0.2%
AAFfQHKWkbvI14ehDjtotfcl 1
 
0.2%
AAFCkglzyMCDBjj36ZeuvQZl 1
 
0.2%
AAG8ynjrgoYUVB+dXMDlVrm5 1
 
0.2%
AAHsBcHgyt+0AeZg3t72FTnP 1
 
0.2%
AAFaC//+nqZpp0CsxyOr7Mn+ 1
 
0.2%
AAFodaWbCakFVKJdGN2sjriu 1
 
0.2%
AAHJq09gikOSOxem6JwLkVuD 1
 
0.2%
AAF0bcVkdD48S9CdrSdpIeVX 1
 
0.2%
Other values (32) 32
 
6.4%

Length

2023-12-12T17:03:38.720132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
aafdk2mgrcgk0tkuj2uqjjhi 459
91.8%
aahfjc1md5p2urgzbftcypc8 1
 
0.2%
aaeioa7pbtdl4lnvkijpoig2 1
 
0.2%
aafdkk2refm2wrdblp9afmcd 1
 
0.2%
aahq0ndpj/luxgwwi2pzxopg 1
 
0.2%
aaehf+59beihkhk0q699f83z 1
 
0.2%
aago+d8ecm81n0ricsl5kez9 1
 
0.2%
aagwt59cig4oiputxd1e8eqw 1
 
0.2%
aaf5fssfezqybl0j0ip3jq/x 1
 
0.2%
aah0za8yttw1dcayn2fnc/9o 1
 
0.2%
Other values (32) 32
 
6.4%

사무소담당자휴대폰번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct18
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
AAFDk2mgRCGK0tkuJ2UqjjHi
483 
AAFJEvaQg+vXGxrzbSe7X1KP
 
1
AAGlgMC/HPQYeDHgHTUBoL3S
 
1
AAFr4cOmt3UBLNcAyBX4Usvz
 
1
AAHiPRjVP22nQcH/o94Tg3ad
 
1
Other values (13)
 
13

Length

Max length24
Median length24
Mean length24
Min length24

Unique

Unique17 ?
Unique (%)3.4%

Sample

1st rowAAFDk2mgRCGK0tkuJ2UqjjHi
2nd rowAAFDk2mgRCGK0tkuJ2UqjjHi
3rd rowAAFDk2mgRCGK0tkuJ2UqjjHi
4th rowAAFDk2mgRCGK0tkuJ2UqjjHi
5th rowAAFDk2mgRCGK0tkuJ2UqjjHi

Common Values

ValueCountFrequency (%)
AAFDk2mgRCGK0tkuJ2UqjjHi 483
96.6%
AAFJEvaQg+vXGxrzbSe7X1KP 1
 
0.2%
AAGlgMC/HPQYeDHgHTUBoL3S 1
 
0.2%
AAFr4cOmt3UBLNcAyBX4Usvz 1
 
0.2%
AAHiPRjVP22nQcH/o94Tg3ad 1
 
0.2%
AAH+1UaaBy/diYGk8rkJvxZw 1
 
0.2%
AAErQf9PiDi0jGx+272NGaoG 1
 
0.2%
AAHFSRzDfuo49Zvp1bklX9oy 1
 
0.2%
AAH7UG8/B0zZL+ByBUoLdf7N 1
 
0.2%
AAGU54t+Bjjt1VRQVDGJAPUp 1
 
0.2%
Other values (8) 8
 
1.6%

Length

2023-12-12T17:03:38.842990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
aafdk2mgrcgk0tkuj2uqjjhi 483
96.6%
aafjevaqg+vxgxrzbse7x1kp 1
 
0.2%
aafjf0jmbextkdqbiyk13mjn 1
 
0.2%
aaet0z6h0hs4zhxr0cboygcm 1
 
0.2%
aaengqego0pmkuxcd/czisal 1
 
0.2%
aafvhx9ahdhccp1ajg7aurwz 1
 
0.2%
aagtdvlpwoxx+zqoosyfjduu 1
 
0.2%
aahfjc1md5p2urgzbftcypc8 1
 
0.2%
aae+r8rpk4ydtkyyv/2mda3i 1
 
0.2%
aagu54t+bjjt1vrqvdgjapup 1
 
0.2%
Other values (8) 8
 
1.6%

사무소담당자이메일
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing495
Missing (%)99.0%
Memory size4.0 KiB
2023-12-12T17:03:39.035205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length48
Mean length48
Min length48

Characters and Unicode

Total characters240
Distinct characters62
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowAAH4aGHv42y7zOGiYnQhYmjh+Tx4aqD5lFpQMMdWK9vgsQ==
2nd rowAAGwbvxz4W3GwFAihH3WaSSZukUK48oB4FHmqbkmXh48hg==
3rd rowAAHolVhF/NLBfOddPzKGnFjpndw1nYCNJK/DDkufl/FUGg==
4th rowAAG9NI/Hb42HCNjB/w71Izg9S8bwzGQKKPd13fqd+Dkw5w==
5th rowAAFHVKFelPL72fhceff0tAfD2CY4NVQq5axBSB6aCT2XJw==
ValueCountFrequency (%)
aah4aghv42y7zogiynqhymjh+tx4aqd5lfpqmmdwk9vgsq 1
20.0%
aagwbvxz4w3gwfaihh3wasszukuk48ob4fhmqbkmxh48hg 1
20.0%
aaholvhf/nlbfoddpzkgnfjpndw1nycnjk/ddkufl/fugg 1
20.0%
aag9ni/hb42hcnjb/w71izg9s8bwzgqkkpd13fqd+dkw5w 1
20.0%
aafhvkfelpl72fhceff0tafd2cy4nvqq5axbsb6act2xjw 1
20.0%
2023-12-12T17:03:39.391306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 12
 
5.0%
= 10
 
4.2%
4 9
 
3.8%
H 8
 
3.3%
G 8
 
3.3%
w 8
 
3.3%
F 8
 
3.3%
K 7
 
2.9%
f 7
 
2.9%
h 7
 
2.9%
Other values (52) 156
65.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 101
42.1%
Lowercase Letter 88
36.7%
Decimal Number 34
 
14.2%
Math Symbol 12
 
5.0%
Other Punctuation 5
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 8
 
9.1%
f 7
 
8.0%
h 7
 
8.0%
d 6
 
6.8%
a 5
 
5.7%
z 5
 
5.7%
n 4
 
4.5%
b 4
 
4.5%
l 4
 
4.5%
q 4
 
4.5%
Other values (15) 34
38.6%
Uppercase Letter
ValueCountFrequency (%)
A 12
 
11.9%
H 8
 
7.9%
G 8
 
7.9%
F 8
 
7.9%
K 7
 
6.9%
Q 5
 
5.0%
D 5
 
5.0%
B 5
 
5.0%
N 5
 
5.0%
Y 4
 
4.0%
Other values (14) 34
33.7%
Decimal Number
ValueCountFrequency (%)
4 9
26.5%
2 5
14.7%
3 3
 
8.8%
1 3
 
8.8%
8 3
 
8.8%
9 3
 
8.8%
5 3
 
8.8%
7 3
 
8.8%
0 1
 
2.9%
6 1
 
2.9%
Math Symbol
ValueCountFrequency (%)
= 10
83.3%
+ 2
 
16.7%
Other Punctuation
ValueCountFrequency (%)
/ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 189
78.8%
Common 51
 
21.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 12
 
6.3%
H 8
 
4.2%
G 8
 
4.2%
w 8
 
4.2%
F 8
 
4.2%
K 7
 
3.7%
f 7
 
3.7%
h 7
 
3.7%
d 6
 
3.2%
Q 5
 
2.6%
Other values (39) 113
59.8%
Common
ValueCountFrequency (%)
= 10
19.6%
4 9
17.6%
/ 5
9.8%
2 5
9.8%
3 3
 
5.9%
1 3
 
5.9%
8 3
 
5.9%
9 3
 
5.9%
5 3
 
5.9%
7 3
 
5.9%
Other values (3) 4
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 240
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 12
 
5.0%
= 10
 
4.2%
4 9
 
3.8%
H 8
 
3.3%
G 8
 
3.3%
w 8
 
3.3%
F 8
 
3.3%
K 7
 
2.9%
f 7
 
2.9%
h 7
 
2.9%
Other values (52) 156
65.0%

등록부점코드
Text

Distinct117
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T17:03:39.710452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1500
Distinct characters25
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

Unique18 ?
Unique (%)3.6%

Sample

1st rowTHT
2nd rowTNC
3rd rowTAH
4th rowTBA
5th rowTMJ
ValueCountFrequency (%)
toj 13
 
2.6%
taz 12
 
2.4%
tme 12
 
2.4%
tbh 12
 
2.4%
tba 12
 
2.4%
tho 10
 
2.0%
taw 10
 
2.0%
tqd 10
 
2.0%
tpa 9
 
1.8%
thy 9
 
1.8%
Other values (107) 391
78.2%
2023-12-12T17:03:40.169912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 491
32.7%
A 174
 
11.6%
H 129
 
8.6%
I 70
 
4.7%
B 68
 
4.5%
Q 63
 
4.2%
O 59
 
3.9%
P 48
 
3.2%
M 48
 
3.2%
D 42
 
2.8%
Other values (15) 308
20.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1500
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 491
32.7%
A 174
 
11.6%
H 129
 
8.6%
I 70
 
4.7%
B 68
 
4.5%
Q 63
 
4.2%
O 59
 
3.9%
P 48
 
3.2%
M 48
 
3.2%
D 42
 
2.8%
Other values (15) 308
20.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 1500
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 491
32.7%
A 174
 
11.6%
H 129
 
8.6%
I 70
 
4.7%
B 68
 
4.5%
Q 63
 
4.2%
O 59
 
3.9%
P 48
 
3.2%
M 48
 
3.2%
D 42
 
2.8%
Other values (15) 308
20.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 491
32.7%
A 174
 
11.6%
H 129
 
8.6%
I 70
 
4.7%
B 68
 
4.5%
Q 63
 
4.2%
O 59
 
3.9%
P 48
 
3.2%
M 48
 
3.2%
D 42
 
2.8%
Other values (15) 308
20.5%

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
500 
ValueCountFrequency (%)
False 500
100.0%
2023-12-12T17:03:40.310503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최종수정수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
440 
2
53 
3
 
6
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 440
88.0%
2 53
 
10.6%
3 6
 
1.2%
4 1
 
0.2%

Length

2023-12-12T17:03:40.417998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:03:40.525909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 440
88.0%
2 53
 
10.6%
3 6
 
1.2%
4 1
 
0.2%

처리직원번호
Real number (ℝ)

Distinct379
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5159.52
Minimum2398
Maximum6207
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T17:03:40.654492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2398
5-th percentile3608.95
Q14658
median5186.5
Q35845
95-th percentile6155.05
Maximum6207
Range3809
Interquartile range (IQR)1187

Descriptive statistics

Standard deviation779.09581
Coefficient of variation (CV)0.15100161
Kurtosis0.14314133
Mean5159.52
Median Absolute Deviation (MAD)588.5
Skewness-0.71417894
Sum2579760
Variance606990.28
MonotonicityNot monotonic
2023-12-12T17:03:40.829080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3489 7
 
1.4%
3912 5
 
1.0%
5061 4
 
0.8%
4525 4
 
0.8%
5080 3
 
0.6%
5483 3
 
0.6%
4005 3
 
0.6%
2687 3
 
0.6%
4481 3
 
0.6%
4629 3
 
0.6%
Other values (369) 462
92.4%
ValueCountFrequency (%)
2398 1
 
0.2%
2687 3
0.6%
2846 1
 
0.2%
3071 1
 
0.2%
3280 1
 
0.2%
3283 1
 
0.2%
3348 1
 
0.2%
3399 1
 
0.2%
3432 2
 
0.4%
3489 7
1.4%
ValueCountFrequency (%)
6207 2
0.4%
6205 1
0.2%
6203 1
0.2%
6201 1
0.2%
6195 1
0.2%
6193 1
0.2%
6192 1
0.2%
6189 2
0.4%
6184 1
0.2%
6180 1
0.2%

Interactions

2023-12-12T17:03:36.022456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:03:40.945460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사무소담당자전화번호사무소담당자휴대폰번호사무소담당자이메일최종수정수처리직원번호
사무소담당자전화번호1.0000.9281.0000.7440.534
사무소담당자휴대폰번호0.9281.0001.0000.3990.000
사무소담당자이메일1.0001.0001.0001.0001.000
최종수정수0.7440.3991.0001.0000.000
처리직원번호0.5340.0001.0000.0001.000
2023-12-12T17:03:41.070136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최종수정수사무소담당자휴대폰번호사무소담당자전화번호
최종수정수1.0000.2250.459
사무소담당자휴대폰번호0.2251.0000.530
사무소담당자전화번호0.4590.5301.000
2023-12-12T17:03:41.192022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처리직원번호사무소담당자전화번호사무소담당자휴대폰번호최종수정수
처리직원번호1.0000.2070.0000.000
사무소담당자전화번호0.2071.0000.5300.459
사무소담당자휴대폰번호0.0000.5301.0000.225
최종수정수0.0000.4590.2251.000

Missing values

2023-12-12T17:03:36.214358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:03:36.431624image/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

고객아이디(ID)고객세무사회계사관계코드세무사회계사아이디(ID)사무소담당자전화번호사무소담당자휴대폰번호사무소담당자이메일등록부점코드삭제여부최종수정수처리직원번호
09b6FkYxlLn1019bnEWvjXzQAAFDk2mgRCGK0tkuJ2UqjjHiAAFDk2mgRCGK0tkuJ2UqjjHi<NA>THTN25820
19dnAtcpIHp1019bnEWvhYUSAAFDk2mgRCGK0tkuJ2UqjjHiAAFDk2mgRCGK0tkuJ2UqjjHi<NA>TNCN15073
29b9djdJvTG1019cRTqjQv8ZAAFmEbODBeanBpxTiW4GPnLWAAFDk2mgRCGK0tkuJ2UqjjHi<NA>TAHN15407
39bnM1hpqkD1019buGByzGqAAAFDk2mgRCGK0tkuJ2UqjjHiAAFDk2mgRCGK0tkuJ2UqjjHi<NA>TBAN15075
49cNTe1Ty2w1019cZBkv1TBZAAFDk2mgRCGK0tkuJ2UqjjHiAAFDk2mgRCGK0tkuJ2UqjjHi<NA>TMJN16018
59dnOFjToNz1019bnEWvraeCAAFDk2mgRCGK0tkuJ2UqjjHiAAFDk2mgRCGK0tkuJ2UqjjHi<NA>TMEN25539
69dnDYVaELu1019cwTaR3zxyAAFDk2mgRCGK0tkuJ2UqjjHiAAFDk2mgRCGK0tkuJ2UqjjHi<NA>TOJN16036
79cE6LLCcKo1019dnSX9ueMMAAFDk2mgRCGK0tkuJ2UqjjHiAAFDk2mgRCGK0tkuJ2UqjjHi<NA>THUN26086
89c2PBQUR8l1019bnEWvJsGEAAFDk2mgRCGK0tkuJ2UqjjHiAAFDk2mgRCGK0tkuJ2UqjjHi<NA>THVN15922
99c0ZMmv1r81019c4jidAZ0cAAFDk2mgRCGK0tkuJ2UqjjHiAAFDk2mgRCGK0tkuJ2UqjjHi<NA>TPPN26038
고객아이디(ID)고객세무사회계사관계코드세무사회계사아이디(ID)사무소담당자전화번호사무소담당자휴대폰번호사무소담당자이메일등록부점코드삭제여부최종수정수처리직원번호
4909dnqq9bIIQ1019dnDyVwnLuAAFDk2mgRCGK0tkuJ2UqjjHiAAFDk2mgRCGK0tkuJ2UqjjHi<NA>TMEN14853
4919cHxHXp5m51019ceAPS3ukuAAFDk2mgRCGK0tkuJ2UqjjHiAAFDk2mgRCGK0tkuJ2UqjjHi<NA>THGN14951
4929cc7nEd3BI1019bwZcB8MY4AAFDk2mgRCGK0tkuJ2UqjjHiAAFDk2mgRCGK0tkuJ2UqjjHi<NA>TAPN25567
4939dnza9rgm81019bwhhA2iQ1AAFDk2mgRCGK0tkuJ2UqjjHiAAFDk2mgRCGK0tkuJ2UqjjHi<NA>THGN15473
494aaaaaaAd2G1019da9kMOO8BAAFDk2mgRCGK0tkuJ2UqjjHiAAFDk2mgRCGK0tkuJ2UqjjHi<NA>TAWN14918
4959dm0qc2s551019cv3t8B3OrAAFDk2mgRCGK0tkuJ2UqjjHiAAFDk2mgRCGK0tkuJ2UqjjHi<NA>TOGN24222
4969cQXrZX5we1019bnEWvcDEyAAFDk2mgRCGK0tkuJ2UqjjHiAAFDk2mgRCGK0tkuJ2UqjjHi<NA>TAON15171
4979czG8fSHqO1019cXhPuieqyAAFDk2mgRCGK0tkuJ2UqjjHiAAFDk2mgRCGK0tkuJ2UqjjHi<NA>THSN15455
4989dgx7Rwo4Q1019bnEWvnP0QAAEIoa7pbTDl4LnvkIJpOig2AAFDk2mgRCGK0tkuJ2UqjjHiAAFHVKFelPL72fhceff0tAfD2CY4NVQq5axBSB6aCT2XJw==JANN14431
4999dg5MrZOn61019cd1DsuC24AAEIehwXi6gg+swyakXsd9fzAAFDk2mgRCGK0tkuJ2UqjjHi<NA>TMAN16207