Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells2
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory121.0 B

Variable types

DateTime1
Numeric4
Categorical7
Text1

Dataset

Description경상북도 구미시의 가상계좌거래내역으로 입금일자, 세입회계코드, 거래금액, 응답코드, 응답일시, 취급은행코드의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15117316/fileData.do

Alerts

수표금액 has constant value ""Constant
취급은행코드 is highly overall correlated with 중계번호 and 2 other fieldsHigh correlation
기관코드 is highly overall correlated with 중계번호 and 4 other fieldsHigh correlation
중계번호 is highly overall correlated with 취급은행코드 and 2 other fieldsHigh correlation
세입회계코드 is highly overall correlated with 중계순번 and 1 other fieldsHigh correlation
중계순번 is highly overall correlated with 세입회계코드 and 1 other fieldsHigh correlation
거래구분 is highly overall correlated with 거래구분코드High correlation
거래구분코드 is highly overall correlated with 중계번호 and 3 other fieldsHigh correlation
중계순번 is highly imbalanced (78.0%)Imbalance
응답코드 is highly imbalanced (70.2%)Imbalance
거래금액 is highly skewed (γ1 = 70.5477136)Skewed
취급은행 has 183 (1.8%) zerosZeros

Reproduction

Analysis started2023-12-11 23:12:24.728096
Analysis finished2023-12-11 23:12:27.946528
Duration3.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

중계일자
Date

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-06-01 00:00:00
Maximum2023-06-19 00:00:00
2023-12-12T08:12:28.027677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:12:28.487486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

중계번호
Real number (ℝ)

HIGH CORRELATION 

Distinct8731
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30695920
Minimum10026705
Maximum1.0413094 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T08:12:28.661756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10026705
5-th percentile10300073
Q111518322
median13116592
Q350000484
95-th percentile91493016
Maximum1.0413094 × 108
Range94104232
Interquartile range (IQR)38482162

Descriptive statistics

Standard deviation25771010
Coefficient of variation (CV)0.83955817
Kurtosis0.1127232
Mean30695920
Median Absolute Deviation (MAD)2524535
Skewness1.0700617
Sum3.069592 × 1011
Variance6.6414497 × 1014
MonotonicityNot monotonic
2023-12-12T08:12:28.829679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000113 10
 
0.1%
50000035 9
 
0.1%
50000011 9
 
0.1%
50000112 8
 
0.1%
50000096 8
 
0.1%
50000055 8
 
0.1%
50000014 8
 
0.1%
50000043 8
 
0.1%
50000015 8
 
0.1%
50000004 8
 
0.1%
Other values (8721) 9916
99.2%
ValueCountFrequency (%)
10026705 1
< 0.1%
10028301 1
< 0.1%
10028442 1
< 0.1%
10028443 1
< 0.1%
10030768 1
< 0.1%
10038589 1
< 0.1%
10041245 1
< 0.1%
10043743 1
< 0.1%
10046699 1
< 0.1%
10048352 1
< 0.1%
ValueCountFrequency (%)
104130937 1
< 0.1%
103956485 1
< 0.1%
103915831 1
< 0.1%
103866844 1
< 0.1%
103639113 1
< 0.1%
103626508 1
< 0.1%
103582914 1
< 0.1%
103505685 1
< 0.1%
103499685 1
< 0.1%
103499237 1
< 0.1%

중계순번
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9268 
2
 
554
3
 
171
4
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 9268
92.7%
2 554
 
5.5%
3 171
 
1.7%
4 7
 
0.1%

Length

2023-12-12T08:12:28.957230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:12:29.043134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9268
92.7%
2 554
 
5.5%
3 171
 
1.7%
4 7
 
0.1%

세입회계코드
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)0.4%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean120940.81
Minimum100000
Maximum500000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T08:12:29.156849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100000
5-th percentile100000
Q1100000
median100000
Q3100000
95-th percentile300000
Maximum500000
Range400000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation58503.597
Coefficient of variation (CV)0.48373744
Kurtosis5.8995783
Mean120940.81
Median Absolute Deviation (MAD)0
Skewness2.6610225
Sum1.2091662 × 109
Variance3.4226709 × 109
MonotonicityNot monotonic
2023-12-12T08:12:29.281109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
100000 8779
87.8%
300000 805
 
8.1%
204800 137
 
1.4%
212400 73
 
0.7%
216400 33
 
0.3%
214800 24
 
0.2%
216600 23
 
0.2%
216700 12
 
0.1%
217300 10
 
0.1%
208200 10
 
0.1%
Other values (32) 92
 
0.9%
ValueCountFrequency (%)
100000 8779
87.8%
200600 3
 
< 0.1%
201100 2
 
< 0.1%
201200 2
 
< 0.1%
201300 5
 
0.1%
201400 1
 
< 0.1%
201600 1
 
< 0.1%
201700 3
 
< 0.1%
201801 2
 
< 0.1%
203201 1
 
< 0.1%
ValueCountFrequency (%)
500000 9
 
0.1%
300000 805
8.1%
219300 10
 
0.1%
219000 4
 
< 0.1%
218600 2
 
< 0.1%
218400 1
 
< 0.1%
218200 3
 
< 0.1%
218000 1
 
< 0.1%
217900 1
 
< 0.1%
217300 10
 
0.1%

거래구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
6932 
2
3067 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 6932
69.3%
2 3067
30.7%
3 1
 
< 0.1%

Length

2023-12-12T08:12:29.423991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:12:29.510277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 6932
69.3%
2 3067
30.7%
3 1
 
< 0.1%

거래금액
Real number (ℝ)

SKEWED 

Distinct2271
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2041012.9
Minimum0
Maximum9 × 109
Zeros54
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T08:12:29.614759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q132000
median72925
Q3145410
95-th percentile301955
Maximum9 × 109
Range9 × 109
Interquartile range (IQR)113410

Descriptive statistics

Standard deviation1.2736338 × 108
Coefficient of variation (CV)62.402045
Kurtosis4982.7763
Mean2041012.9
Median Absolute Deviation (MAD)54485
Skewness70.547714
Sum2.0410129 × 1010
Variance1.622143 × 1016
MonotonicityNot monotonic
2023-12-12T08:12:29.734634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27490 784
 
7.8%
1 627
 
6.3%
32000 501
 
5.0%
129870 318
 
3.2%
62700 219
 
2.2%
72380 214
 
2.1%
50110 131
 
1.3%
145410 120
 
1.2%
129670 111
 
1.1%
129410 97
 
1.0%
Other values (2261) 6878
68.8%
ValueCountFrequency (%)
0 54
 
0.5%
1 627
6.3%
7 1
 
< 0.1%
8 1
 
< 0.1%
10 8
 
0.1%
90 1
 
< 0.1%
100 13
 
0.1%
190 1
 
< 0.1%
200 2
 
< 0.1%
210 1
 
< 0.1%
ValueCountFrequency (%)
9000000000 2
< 0.1%
423678000 1
< 0.1%
171000000 1
< 0.1%
98252000 1
< 0.1%
75000000 1
< 0.1%
65000000 1
< 0.1%
60384000 1
< 0.1%
42861000 1
< 0.1%
39600000 1
< 0.1%
29750000 1
< 0.1%

응답코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
8997 
V713
1001 
V817
 
2

Length

Max length4
Median length1
Mean length1.3009
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th rowV713
5th row0

Common Values

ValueCountFrequency (%)
0 8997
90.0%
V713 1001
 
10.0%
V817 2
 
< 0.1%

Length

2023-12-12T08:12:29.882286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:12:29.977492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8997
90.0%
v713 1001
 
10.0%
v817 2
 
< 0.1%

취급은행코드
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
11
6101 
31
2545 
20
634 
81
 
563
71
 
157

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11
2nd row31
3rd row11
4th row11
5th row11

Common Values

ValueCountFrequency (%)
11 6101
61.0%
31 2545
25.4%
20 634
 
6.3%
81 563
 
5.6%
71 157
 
1.6%

Length

2023-12-12T08:12:30.089517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:12:30.189732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 6101
61.0%
31 2545
25.4%
20 634
 
6.3%
81 563
 
5.6%
71 157
 
1.6%

취급은행
Real number (ℝ)

ZEROS 

Distinct55
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.2142
Minimum0
Maximum247
Zeros183
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T08:12:30.296376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q111
median15
Q346
95-th percentile90
Maximum247
Range247
Interquartile range (IQR)35

Descriptive statistics

Standard deviation32.861916
Coefficient of variation (CV)0.98939357
Kurtosis1.1622669
Mean33.2142
Median Absolute Deviation (MAD)11
Skewness1.2075266
Sum332142
Variance1079.9055
MonotonicityNot monotonic
2023-12-12T08:12:30.424163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11 999
 
10.0%
31 870
 
8.7%
15 797
 
8.0%
3 672
 
6.7%
88 670
 
6.7%
90 624
 
6.2%
81 552
 
5.5%
13 535
 
5.3%
12 525
 
5.2%
4 461
 
4.6%
Other values (45) 3295
33.0%
ValueCountFrequency (%)
0 183
 
1.8%
2 6
 
0.1%
3 672
6.7%
4 461
4.6%
6 227
 
2.3%
7 1
 
< 0.1%
9 4
 
< 0.1%
10 350
 
3.5%
11 999
10.0%
12 525
5.2%
ValueCountFrequency (%)
247 2
 
< 0.1%
243 1
 
< 0.1%
240 6
 
0.1%
238 3
 
< 0.1%
209 4
 
< 0.1%
99 15
 
0.1%
96 5
 
0.1%
92 213
 
2.1%
91 2
 
< 0.1%
90 624
6.2%

취급은행지점
Text

Distinct982
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T08:12:30.744623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.4904
Min length1

Characters and Unicode

Total characters34904
Distinct characters12
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

Unique560 ?
Unique (%)5.6%

Sample

1st row8396
2nd row0
3rd row3181
4th row8125
5th row9178
ValueCountFrequency (%)
0 900
 
9.0%
32 624
 
6.2%
6310 279
 
2.8%
8125 276
 
2.8%
7715 198
 
2.0%
7786 183
 
1.8%
8180 181
 
1.8%
2256 176
 
1.8%
1574 168
 
1.7%
4005 164
 
1.6%
Other values (972) 6851
68.5%
2023-12-12T08:12:31.209973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4537
13.0%
7 4315
12.4%
0 4013
11.5%
5 3693
10.6%
2 3442
9.9%
3 3420
9.8%
8 3332
9.5%
4 2935
8.4%
9 2737
7.8%
6 2478
7.1%
Other values (2) 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34902
> 99.9%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4537
13.0%
7 4315
12.4%
0 4013
11.5%
5 3693
10.6%
2 3442
9.9%
3 3420
9.8%
8 3332
9.5%
4 2935
8.4%
9 2737
7.8%
6 2478
7.1%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
Z 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34902
> 99.9%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4537
13.0%
7 4315
12.4%
0 4013
11.5%
5 3693
10.6%
2 3442
9.9%
3 3420
9.8%
8 3332
9.5%
4 2935
8.4%
9 2737
7.8%
6 2478
7.1%
Latin
ValueCountFrequency (%)
B 1
50.0%
Z 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34904
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4537
13.0%
7 4315
12.4%
0 4013
11.5%
5 3693
10.6%
2 3442
9.9%
3 3420
9.8%
8 3332
9.5%
4 2935
8.4%
9 2737
7.8%
6 2478
7.1%
Other values (2) 2
 
< 0.1%

기관코드
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20000527
5918 
EZMA0088
1553 
EZMA0053
805 
20030665
618 
20030663
 
540
Other values (7)
 
566

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20000527
2nd rowEZMA0088
3rd row20000527
4th row20000527
5th row20000527

Common Values

ValueCountFrequency (%)
20000527 5918
59.2%
EZMA0088 1553
 
15.5%
EZMA0053 805
 
8.1%
20030665 618
 
6.2%
20030663 540
 
5.4%
31000168 183
 
1.8%
EZMA0052 178
 
1.8%
20030667 152
 
1.5%
20030664 23
 
0.2%
20030666 16
 
0.2%
Other values (2) 14
 
0.1%

Length

2023-12-12T08:12:31.338790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20000527 5918
59.2%
ezma0088 1553
 
15.5%
ezma0053 805
 
8.1%
20030665 618
 
6.2%
20030663 540
 
5.4%
31000168 183
 
1.8%
ezma0052 178
 
1.8%
20030667 152
 
1.5%
20030664 23
 
0.2%
20030666 16
 
0.2%
Other values (2) 14
 
0.1%

거래구분코드
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2000
5305 
3000
1901 
1200
1627 
1300
918 
1000
 
249

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2000
2nd row1300
3rd row2000
4th row2000
5th row2000

Common Values

ValueCountFrequency (%)
2000 5305
53.0%
3000 1901
 
19.0%
1200 1627
 
16.3%
1300 918
 
9.2%
1000 249
 
2.5%

Length

2023-12-12T08:12:31.500503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:12:31.606251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2000 5305
53.0%
3000 1901
 
19.0%
1200 1627
 
16.3%
1300 918
 
9.2%
1000 249
 
2.5%

수표금액
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2023-12-12T08:12:31.726387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:12:31.815050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

Interactions

2023-12-12T08:12:27.068117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:12:25.722548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:12:26.131056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:12:26.584970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:12:27.192194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:12:25.841017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:12:26.225324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:12:26.704065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:12:27.330467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:12:25.943298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:12:26.341491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:12:26.809510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:12:27.467565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:12:26.039907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:12:26.444710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:12:26.966427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:12:31.889616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
중계일자중계번호중계순번세입회계코드거래구분거래금액응답코드취급은행코드취급은행기관코드거래구분코드
중계일자1.0000.2760.2930.2230.0240.0000.1320.2760.0890.4180.280
중계번호0.2761.0000.3320.5370.0650.0110.1221.0000.5491.0000.885
중계순번0.2930.3321.0000.6710.0690.1600.0570.3320.1780.9710.343
세입회계코드0.2230.5370.6711.0000.0290.0250.0320.5370.3771.0000.544
거래구분0.0240.0650.0690.0291.0000.0100.4100.0650.0310.1440.718
거래금액0.0000.0110.1600.0250.0101.0000.0000.0110.0250.1290.032
응답코드0.1320.1220.0570.0320.4100.0001.0000.1220.2690.2000.240
취급은행코드0.2761.0000.3320.5370.0650.0110.1221.0000.5491.0000.885
취급은행0.0890.5490.1780.3770.0310.0250.2690.5491.0000.5910.334
기관코드0.4181.0000.9711.0000.1440.1290.2001.0000.5911.0000.767
거래구분코드0.2800.8850.3430.5440.7180.0320.2400.8850.3340.7671.000
2023-12-12T08:12:32.009730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
취급은행코드기관코드거래구분중계순번응답코드거래구분코드
취급은행코드1.0001.0000.0480.2770.0910.541
기관코드1.0001.0000.0650.7790.0910.562
거래구분0.0480.0651.0000.0650.1520.707
중계순번0.2770.7790.0651.0000.0530.286
응답코드0.0910.0910.1520.0531.0000.186
거래구분코드0.5410.5620.7070.2860.1861.000
2023-12-12T08:12:32.124788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
중계번호세입회계코드거래금액취급은행중계순번거래구분응답코드취급은행코드기관코드거래구분코드
중계번호1.0000.140-0.0520.3120.2770.0480.0911.0001.0000.541
세입회계코드0.1401.000-0.175-0.0110.6540.0440.0850.3021.0000.325
거래금액-0.052-0.1751.000-0.0950.1060.0160.0000.0140.1000.040
취급은행0.312-0.011-0.0951.0000.1230.0200.1870.3930.3380.221
중계순번0.2770.6540.1060.1231.0000.0650.0530.2770.7790.286
거래구분0.0480.0440.0160.0200.0651.0000.1520.0480.0650.707
응답코드0.0910.0850.0000.1870.0530.1521.0000.0910.0910.186
취급은행코드1.0000.3020.0140.3930.2770.0480.0911.0001.0000.541
기관코드1.0001.0000.1000.3380.7790.0650.0911.0001.0000.562
거래구분코드0.5410.3250.0400.2210.2860.7070.1860.5410.5621.000

Missing values

2023-12-12T08:12:27.639222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:12:27.846277image/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

중계일자중계번호중계순번세입회계코드거래구분거래금액응답코드취급은행코드취급은행취급은행지점기관코드거래구분코드수표금액
691952023-06-1611478212110000011298700111383962000052720000
201652023-06-13500008861100000227490031310EZMA008813000
302312023-06-141224579511000001627000111231812000052720000
681842023-06-1611190709110000011V713118881252000052720000
936752023-06-1811714073110000011298700111491782000052720000
151802023-06-12500005431100000257130031466424EZMA008813000
93072023-06-0813114686110000024148001190322000052730000
304002023-06-14500014771100000112987003146310EZMA008812000
471472023-06-1591491455110000011V713818881252003066320000
367582023-06-146304030611000001479360V713202015082003066520000
중계일자중계번호중계순번세입회계코드거래구분거래금액응답코드취급은행코드취급은행취급은행지점기관코드거래구분코드수표금액
701672023-06-161179294011000001500600111177312000052720000
74192023-06-071030012912122001300000011003100016820000
804222023-06-171025989311000002600700112181802000052730000
290712023-06-14500012631100000145490V7133139987EZMA008812000
612672023-06-1514147438110000011067500118881252000052720000
892642023-06-181043248511000001129870011462422000052720000
176592023-06-1311904047110000022299900111820832000052730000
186902023-06-139231851511000002210300081340052003066330000
138962023-06-125000028911000002232170003143227EZMA008813000
404032023-06-156012294111000001806000202070522003066520000