Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells32
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory117.0 B

Variable types

Text4
Categorical5
Numeric4

Dataset

Description소비자 민원 상담에 대한 사건 처리 결과별 최근 년도에 대한 소비자 민원 상담에 관한 데이터를 보여줍니다. 이 데이터는 사건제목을 포함하고 있습니다.
Author공정거래위원회
URLhttps://www.data.go.kr/data/15098315/fileData.do

Alerts

성별(GENDER) is highly overall correlated with 성별코드(GENDER_CODE)High correlation
성별코드(GENDER_CODE) is highly overall correlated with 성별(GENDER)High correlation
연령대코드(AGE_GROUP_CODE) is highly overall correlated with 연령대명(AGE_GROUP_NAME)High correlation
처리결과코드(PRCS_RESULT_CODE) is highly overall correlated with 처리결과명(PRCS_RESULT_NAME)High correlation
연령대명(AGE_GROUP_NAME) is highly overall correlated with 연령대코드(AGE_GROUP_CODE)High correlation
처리결과명(PRCS_RESULT_NAME) is highly overall correlated with 처리결과코드(PRCS_RESULT_CODE)High correlation
사건번호(ACCIDENT_NO) has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:06:42.872600
Analysis finished2023-12-12 03:06:48.284244
Duration5.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사건번호(ACCIDENT_NO)
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:06:48.497402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters120000
Distinct characters11
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row2020-0002909
2nd row2020-0017064
3rd row2020-0001635
4th row2020-0074875
5th row2020-0086461
ValueCountFrequency (%)
2020-0002909 1
 
< 0.1%
2020-0025725 1
 
< 0.1%
2020-0045193 1
 
< 0.1%
2020-0043416 1
 
< 0.1%
2020-0032751 1
 
< 0.1%
2020-0008670 1
 
< 0.1%
2020-0058916 1
 
< 0.1%
2020-0047894 1
 
< 0.1%
2020-0068091 1
 
< 0.1%
2020-0035191 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-12T12:06:48.957172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 45198
37.7%
2 25205
21.0%
- 10000
 
8.3%
7 5244
 
4.4%
5 5149
 
4.3%
1 5145
 
4.3%
4 5133
 
4.3%
3 5111
 
4.3%
6 5053
 
4.2%
8 4769
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 110000
91.7%
Dash Punctuation 10000
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 45198
41.1%
2 25205
22.9%
7 5244
 
4.8%
5 5149
 
4.7%
1 5145
 
4.7%
4 5133
 
4.7%
3 5111
 
4.6%
6 5053
 
4.6%
8 4769
 
4.3%
9 3993
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 45198
37.7%
2 25205
21.0%
- 10000
 
8.3%
7 5244
 
4.4%
5 5149
 
4.3%
1 5145
 
4.3%
4 5133
 
4.3%
3 5111
 
4.3%
6 5053
 
4.2%
8 4769
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 45198
37.7%
2 25205
21.0%
- 10000
 
8.3%
7 5244
 
4.4%
5 5149
 
4.3%
1 5145
 
4.3%
4 5133
 
4.3%
3 5111
 
4.3%
6 5053
 
4.2%
8 4769
 
4.0%

접수일자(RCPT_YMD)
Categorical

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2020-02-03
 
545
2020-02-04
 
471
2020-01-29
 
459
2020-01-28
 
453
2020-02-05
 
450
Other values (40)
7622 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2020-01-03
2nd row2020-01-09
3rd row2020-01-02
4th row2020-02-06
5th row2020-02-11

Common Values

ValueCountFrequency (%)
2020-02-03 545
 
5.5%
2020-02-04 471
 
4.7%
2020-01-29 459
 
4.6%
2020-01-28 453
 
4.5%
2020-02-05 450
 
4.5%
2020-02-06 450
 
4.5%
2020-01-31 444
 
4.4%
2020-01-30 406
 
4.1%
2020-01-06 399
 
4.0%
2020-02-10 382
 
3.8%
Other values (35) 5541
55.4%

Length

2023-12-12T12:06:49.119165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-02-03 545
 
5.5%
2020-02-04 471
 
4.7%
2020-01-29 459
 
4.6%
2020-01-28 453
 
4.5%
2020-02-05 450
 
4.5%
2020-02-06 450
 
4.5%
2020-01-31 444
 
4.4%
2020-01-30 406
 
4.1%
2020-01-06 399
 
4.0%
2020-02-10 382
 
3.8%
Other values (35) 5541
55.4%

성별코드(GENDER_CODE)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
5672 
1
4254 
<NA>
 
74

Length

Max length4
Median length1
Mean length1.0222
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 5672
56.7%
1 4254
42.5%
<NA> 74
 
0.7%

Length

2023-12-12T12:06:49.262322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:06:49.387484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 5672
56.7%
1 4254
42.5%
na 74
 
0.7%

성별(GENDER)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
여성
5672 
남성
4254 
<NA>
 
74

Length

Max length4
Median length2
Mean length2.0148
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남성
2nd row여성
3rd row여성
4th row여성
5th row여성

Common Values

ValueCountFrequency (%)
여성 5672
56.7%
남성 4254
42.5%
<NA> 74
 
0.7%

Length

2023-12-12T12:06:49.566602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:06:49.721351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여성 5672
56.7%
남성 4254
42.5%
na 74
 
0.7%

연령대코드(AGE_GROUP_CODE)
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)0.1%
Missing8
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean5.4369496
Minimum2
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:06:49.863262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q14
median5
Q36
95-th percentile11
Maximum12
Range10
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.2187064
Coefficient of variation (CV)0.40807927
Kurtosis1.8359674
Mean5.4369496
Median Absolute Deviation (MAD)1
Skewness1.5926598
Sum54326
Variance4.9226582
MonotonicityNot monotonic
2023-12-12T12:06:49.997489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
4 2918
29.2%
5 2756
27.6%
6 1902
19.0%
3 1011
 
10.1%
11 697
 
7.0%
9 262
 
2.6%
12 208
 
2.1%
8 188
 
1.9%
10 38
 
0.4%
2 12
 
0.1%
(Missing) 8
 
0.1%
ValueCountFrequency (%)
2 12
 
0.1%
3 1011
 
10.1%
4 2918
29.2%
5 2756
27.6%
6 1902
19.0%
8 188
 
1.9%
9 262
 
2.6%
10 38
 
0.4%
11 697
 
7.0%
12 208
 
2.1%
ValueCountFrequency (%)
12 208
 
2.1%
11 697
 
7.0%
10 38
 
0.4%
9 262
 
2.6%
8 188
 
1.9%
6 1902
19.0%
5 2756
27.6%
4 2918
29.2%
3 1011
 
10.1%
2 12
 
0.1%

연령대명(AGE_GROUP_NAME)
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
30 - 39세
2918 
40 - 49세
2756 
50 - 59세
1902 
20 - 29세
1011 
60 - 64세
697 
Other values (6)
716 

Length

Max length8
Median length8
Mean length7.8282
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row60 - 64세
2nd row50 - 59세
3rd row20 - 29세
4th row30 - 39세
5th row60 - 64세

Common Values

ValueCountFrequency (%)
30 - 39세 2918
29.2%
40 - 49세 2756
27.6%
50 - 59세 1902
19.0%
20 - 29세 1011
 
10.1%
60 - 64세 697
 
7.0%
불명 262
 
2.6%
65 - 69세 208
 
2.1%
70 - 79세 188
 
1.9%
80세이상 38
 
0.4%
10 - 19세 12
 
0.1%

Length

2023-12-12T12:06:50.155538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9692
33.0%
30 2918
 
9.9%
39세 2918
 
9.9%
40 2756
 
9.4%
49세 2756
 
9.4%
50 1902
 
6.5%
59세 1902
 
6.5%
20 1011
 
3.4%
29세 1011
 
3.4%
64세 697
 
2.4%
Other values (10) 1821
 
6.2%

지역코드(AREA_CODE)
Real number (ℝ)

Distinct240
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean806.2382
Minimum100
Maximum9907
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:06:50.319961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile100
Q1203
median800
Q3828
95-th percentile1507
Maximum9907
Range9807
Interquartile range (IQR)625

Descriptive statistics

Standard deviation1218.3129
Coefficient of variation (CV)1.5111078
Kurtosis44.8815
Mean806.2382
Median Absolute Deviation (MAD)400
Skewness6.3750606
Sum8062382
Variance1484286.2
MonotonicityNot monotonic
2023-12-12T12:06:50.489674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
800 1707
 
17.1%
100 1157
 
11.6%
200 392
 
3.9%
400 344
 
3.4%
300 285
 
2.9%
600 253
 
2.5%
1100 171
 
1.7%
9900 147
 
1.5%
810 145
 
1.5%
1500 138
 
1.4%
Other values (230) 5261
52.6%
ValueCountFrequency (%)
100 1157
11.6%
101 73
 
0.7%
102 33
 
0.3%
103 24
 
0.2%
104 59
 
0.6%
105 42
 
0.4%
106 28
 
0.3%
107 38
 
0.4%
108 24
 
0.2%
109 41
 
0.4%
ValueCountFrequency (%)
9907 4
 
< 0.1%
9903 2
 
< 0.1%
9901 1
 
< 0.1%
9900 147
1.5%
1700 67
0.7%
1604 42
 
0.4%
1603 10
 
0.1%
1600 50
 
0.5%
1520 3
 
< 0.1%
1519 1
 
< 0.1%

지역명(AREA_NAME)
Text

Distinct218
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:06:50.913909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.686
Min length2

Characters and Unicode

Total characters36860
Distinct characters142
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)0.1%

Sample

1st row중구
2nd row부천시
3rd row서구
4th row인천광역시
5th row남구
ValueCountFrequency (%)
경기도 1707
 
16.6%
서울특별시 1157
 
11.2%
부산광역시 392
 
3.8%
인천광역시 344
 
3.3%
대구광역시 285
 
2.8%
대전광역시 253
 
2.5%
충청남도 171
 
1.7%
기타 151
 
1.5%
해외 147
 
1.4%
및 147
 
1.4%
Other values (209) 5540
53.8%
2023-12-12T12:06:51.519017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 5449
 
14.8%
도 2434
 
6.6%
구 2171
 
5.9%
경 1994
 
5.4%
기 1869
 
5.1%
광 1787
 
4.8%
역 1509
 
4.1%
서 1466
 
4.0%
울 1283
 
3.5%
특 1274
 
3.5%
Other values (132) 15624
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36566
99.2%
Space Separator 294
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 5449
 
14.9%
도 2434
 
6.7%
구 2171
 
5.9%
경 1994
 
5.5%
기 1869
 
5.1%
광 1787
 
4.9%
역 1509
 
4.1%
서 1466
 
4.0%
울 1283
 
3.5%
특 1274
 
3.5%
Other values (131) 15330
41.9%
Space Separator
ValueCountFrequency (%)
294
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36566
99.2%
Common 294
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 5449
 
14.9%
도 2434
 
6.7%
구 2171
 
5.9%
경 1994
 
5.5%
기 1869
 
5.1%
광 1787
 
4.9%
역 1509
 
4.1%
서 1466
 
4.0%
울 1283
 
3.5%
특 1274
 
3.5%
Other values (131) 15330
41.9%
Common
ValueCountFrequency (%)
294
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36566
99.2%
ASCII 294
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 5449
 
14.9%
도 2434
 
6.7%
구 2171
 
5.9%
경 1994
 
5.5%
기 1869
 
5.1%
광 1787
 
4.9%
역 1509
 
4.1%
서 1466
 
4.0%
울 1283
 
3.5%
특 1274
 
3.5%
Other values (131) 15330
41.9%
ASCII
ValueCountFrequency (%)
294
100.0%

품목코드(ITEM_CODE)
Real number (ℝ)

Distinct758
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean285202.02
Minimum110101
Maximum510399
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:06:51.767318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110101
5-th percentile120102
Q1179904.75
median241305
Q3370299
95-th percentile499993
Maximum510399
Range400298
Interquartile range (IQR)190394.25

Descriptive statistics

Standard deviation122256.41
Coefficient of variation (CV)0.42866599
Kurtosis-1.1810802
Mean285202.02
Median Absolute Deviation (MAD)108799
Skewness0.30757759
Sum2.8520202 × 109
Variance1.4946629 × 1010
MonotonicityNot monotonic
2023-12-12T12:06:52.021678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
370102 781
 
7.8%
189999 392
 
3.9%
499993 339
 
3.4%
370408 294
 
2.9%
139912 273
 
2.7%
350104 259
 
2.6%
299999 233
 
2.3%
360302 225
 
2.2%
179999 153
 
1.5%
210113 150
 
1.5%
Other values (748) 6901
69.0%
ValueCountFrequency (%)
110101 7
0.1%
110110 1
 
< 0.1%
110122 1
 
< 0.1%
110123 1
 
< 0.1%
110199 7
0.1%
110201 1
 
< 0.1%
110202 6
0.1%
110203 3
< 0.1%
110208 1
 
< 0.1%
110211 1
 
< 0.1%
ValueCountFrequency (%)
510399 2
 
< 0.1%
510303 3
 
< 0.1%
510302 66
0.7%
510301 1
 
< 0.1%
510299 3
 
< 0.1%
510204 2
 
< 0.1%
510203 1
 
< 0.1%
510202 2
 
< 0.1%
510201 1
 
< 0.1%
510199 10
 
0.1%

품목명(ITEM_NAME)
Text

Distinct757
Distinct (%)7.6%
Missing24
Missing (%)0.2%
Memory size156.2 KiB
2023-12-12T12:06:52.369424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length16
Mean length5.9287289
Min length1

Characters and Unicode

Total characters59145
Distinct characters465
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique217 ?
Unique (%)2.2%

Sample

1st row투자자문(컨설팅)
2nd row캐주얼바지
3rd row헬스장
4th row미용서비스
5th row상조서비스
ValueCountFrequency (%)
국외여행 781
 
7.7%
기타보건·위생용품 392
 
3.9%
기타미분류서비스 339
 
3.4%
헬스장 294
 
2.9%
정수기대여(렌트 273
 
2.7%
항공여객운송서비스 259
 
2.6%
기타미분류물품 233
 
2.3%
이동전화서비스 225
 
2.2%
기타의류·섬유 153
 
1.5%
스마트폰 150
 
1.5%
Other values (749) 6989
69.3%
2023-12-12T12:06:52.910432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 3646
 
6.2%
타 2561
 
4.3%
스 2497
 
4.2%
비 1829
 
3.1%
서 1784
 
3.0%
· 1533
 
2.6%
여 1519
 
2.6%
품 1231
 
2.1%
류 1199
 
2.0%
용 1148
 
1.9%
Other values (455) 40198
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55515
93.9%
Other Punctuation 1539
 
2.6%
Open Punctuation 795
 
1.3%
Close Punctuation 795
 
1.3%
Uppercase Letter 368
 
0.6%
Space Separator 112
 
0.2%
Decimal Number 15
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 3646
 
6.6%
타 2561
 
4.6%
스 2497
 
4.5%
비 1829
 
3.3%
서 1784
 
3.2%
여 1519
 
2.7%
품 1231
 
2.2%
류 1199
 
2.2%
용 1148
 
2.1%
외 1006
 
1.8%
Other values (427) 37095
66.8%
Uppercase Letter
ValueCountFrequency (%)
V 116
31.5%
T 111
30.2%
C 35
 
9.5%
D 27
 
7.3%
P 21
 
5.7%
G 15
 
4.1%
L 10
 
2.7%
S 7
 
1.9%
I 7
 
1.9%
E 6
 
1.6%
Other values (6) 13
 
3.5%
Lowercase Letter
ValueCountFrequency (%)
g 1
16.7%
u 1
16.7%
i 1
16.7%
t 1
16.7%
a 1
16.7%
r 1
16.7%
Other Punctuation
ValueCountFrequency (%)
· 1533
99.6%
/ 6
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 795
100.0%
Close Punctuation
ValueCountFrequency (%)
) 795
100.0%
Space Separator
ValueCountFrequency (%)
112
100.0%
Decimal Number
ValueCountFrequency (%)
2 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55515
93.9%
Common 3256
 
5.5%
Latin 374
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 3646
 
6.6%
타 2561
 
4.6%
스 2497
 
4.5%
비 1829
 
3.3%
서 1784
 
3.2%
여 1519
 
2.7%
품 1231
 
2.2%
류 1199
 
2.2%
용 1148
 
2.1%
외 1006
 
1.8%
Other values (427) 37095
66.8%
Latin
ValueCountFrequency (%)
V 116
31.0%
T 111
29.7%
C 35
 
9.4%
D 27
 
7.2%
P 21
 
5.6%
G 15
 
4.0%
L 10
 
2.7%
S 7
 
1.9%
I 7
 
1.9%
E 6
 
1.6%
Other values (12) 19
 
5.1%
Common
ValueCountFrequency (%)
· 1533
47.1%
( 795
24.4%
) 795
24.4%
112
 
3.4%
2 15
 
0.5%
/ 6
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55515
93.9%
ASCII 2097
 
3.5%
None 1533
 
2.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 3646
 
6.6%
타 2561
 
4.6%
스 2497
 
4.5%
비 1829
 
3.3%
서 1784
 
3.2%
여 1519
 
2.7%
품 1231
 
2.2%
류 1199
 
2.2%
용 1148
 
2.1%
외 1006
 
1.8%
Other values (427) 37095
66.8%
None
ValueCountFrequency (%)
· 1533
100.0%
ASCII
ValueCountFrequency (%)
( 795
37.9%
) 795
37.9%
V 116
 
5.5%
112
 
5.3%
T 111
 
5.3%
C 35
 
1.7%
D 27
 
1.3%
P 21
 
1.0%
2 15
 
0.7%
G 15
 
0.7%
Other values (17) 55
 
2.6%

사건제목(ACCIDENT_TITLE)
Text

Distinct9858
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:06:53.528984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length106
Median length64
Mean length21.4869
Min length2

Characters and Unicode

Total characters214869
Distinct characters1122
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9762 ?
Unique (%)97.6%

Sample

1st row주식 유료 추천회사 해지환급금 부당요구및 해지지연
2nd row청바지 심의결과 궁금 문의
3rd row환불관련 문의
4th row미용서비스 선결제 후 사업자 및 디자이너 변경으로 인해 계약해지시 위약금 발생 여부 문의
5th row미래상조119 업체의 생일잔치행사 거절건
ValueCountFrequency (%)
문의 3020
 
5.5%
환불 979
 
1.8%
취소 707
 
1.3%
후 701
 
1.3%
관련 646
 
1.2%
요청 586
 
1.1%
인한 584
 
1.1%
위약금 574
 
1.1%
건 566
 
1.0%
불만 419
 
0.8%
Other values (15026) 45827
83.9%
2023-12-12T12:06:54.072247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47684
 
22.2%
의 5181
 
2.4%
문 4465
 
2.1%
불 3126
 
1.5%
지 2991
 
1.4%
이 2789
 
1.3%
구 2760
 
1.3%
로 2718
 
1.3%
한 2705
 
1.3%
환 2551
 
1.2%
Other values (1112) 137899
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162424
75.6%
Space Separator 47684
 
22.2%
Decimal Number 1546
 
0.7%
Other Punctuation 903
 
0.4%
Uppercase Letter 881
 
0.4%
Lowercase Letter 444
 
0.2%
Close Punctuation 423
 
0.2%
Open Punctuation 389
 
0.2%
Dash Punctuation 102
 
< 0.1%
Math Symbol 71
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 5181
 
3.2%
문 4465
 
2.7%
불 3126
 
1.9%
지 2991
 
1.8%
이 2789
 
1.7%
구 2760
 
1.7%
로 2718
 
1.7%
한 2705
 
1.7%
환 2551
 
1.6%
해 2491
 
1.5%
Other values (1030) 130647
80.4%
Uppercase Letter
ValueCountFrequency (%)
S 146
16.6%
T 145
16.5%
A 130
14.8%
V 69
7.8%
L 66
7.5%
G 54
 
6.1%
K 48
 
5.4%
P 40
 
4.5%
C 31
 
3.5%
X 27
 
3.1%
Other values (15) 125
14.2%
Lowercase Letter
ValueCountFrequency (%)
s 95
21.4%
a 83
18.7%
t 74
16.7%
v 45
10.1%
p 30
 
6.8%
c 25
 
5.6%
l 18
 
4.1%
k 18
 
4.1%
g 13
 
2.9%
o 6
 
1.4%
Other values (13) 37
 
8.3%
Other Punctuation
ValueCountFrequency (%)
. 592
65.6%
/ 195
 
21.6%
* 47
 
5.2%
% 29
 
3.2%
' 18
 
2.0%
‰ 6
 
0.7%
! 5
 
0.6%
& 4
 
0.4%
: 4
 
0.4%
; 2
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 472
30.5%
0 241
15.6%
3 240
15.5%
2 235
15.2%
5 166
 
10.7%
4 48
 
3.1%
6 41
 
2.7%
9 37
 
2.4%
7 35
 
2.3%
8 31
 
2.0%
Math Symbol
ValueCountFrequency (%)
> 22
31.0%
< 21
29.6%
+ 18
25.4%
~ 8
 
11.3%
= 2
 
2.8%
Close Punctuation
ValueCountFrequency (%)
) 360
85.1%
] 63
 
14.9%
Open Punctuation
ValueCountFrequency (%)
( 327
84.1%
[ 62
 
15.9%
Space Separator
ValueCountFrequency (%)
47684
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 102
100.0%
Other Number
ValueCountFrequency (%)
① 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162422
75.6%
Common 51120
 
23.8%
Latin 1325
 
0.6%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 5181
 
3.2%
문 4465
 
2.7%
불 3126
 
1.9%
지 2991
 
1.8%
이 2789
 
1.7%
구 2760
 
1.7%
로 2718
 
1.7%
한 2705
 
1.7%
환 2551
 
1.6%
해 2491
 
1.5%
Other values (1029) 130645
80.4%
Latin
ValueCountFrequency (%)
S 146
 
11.0%
T 145
 
10.9%
A 130
 
9.8%
s 95
 
7.2%
a 83
 
6.3%
t 74
 
5.6%
V 69
 
5.2%
L 66
 
5.0%
G 54
 
4.1%
K 48
 
3.6%
Other values (38) 415
31.3%
Common
ValueCountFrequency (%)
47684
93.3%
. 592
 
1.2%
1 472
 
0.9%
) 360
 
0.7%
( 327
 
0.6%
0 241
 
0.5%
3 240
 
0.5%
2 235
 
0.5%
/ 195
 
0.4%
5 166
 
0.3%
Other values (24) 608
 
1.2%
Han
ValueCountFrequency (%)
件 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 162406
75.6%
ASCII 52438
 
24.4%
Compat Jamo 16
 
< 0.1%
Punctuation 6
 
< 0.1%
CJK 2
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47684
90.9%
. 592
 
1.1%
1 472
 
0.9%
) 360
 
0.7%
( 327
 
0.6%
0 241
 
0.5%
3 240
 
0.5%
2 235
 
0.4%
/ 195
 
0.4%
5 166
 
0.3%
Other values (70) 1926
 
3.7%
Hangul
ValueCountFrequency (%)
의 5181
 
3.2%
문 4465
 
2.7%
불 3126
 
1.9%
지 2991
 
1.8%
이 2789
 
1.7%
구 2760
 
1.7%
로 2718
 
1.7%
한 2705
 
1.7%
환 2551
 
1.6%
해 2491
 
1.5%
Other values (1017) 130629
80.4%
Punctuation
ValueCountFrequency (%)
‰ 6
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅠ 3
18.8%
ㅐ 2
12.5%
ㄴ 2
12.5%
ㅗ 1
 
6.2%
ㅊ 1
 
6.2%
ㅜ 1
 
6.2%
ㅣ 1
 
6.2%
ㅎ 1
 
6.2%
ㄹ 1
 
6.2%
ㅅ 1
 
6.2%
Other values (2) 2
12.5%
CJK
ValueCountFrequency (%)
件 2
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 1
100.0%

처리결과코드(PRCS_RESULT_CODE)
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean528.3966
Minimum401
Maximum612
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:06:54.242873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum401
5-th percentile501
Q1502
median509
Q3527
95-th percentile610
Maximum612
Range211
Interquartile range (IQR)25

Descriptive statistics

Standard deviation40.786356
Coefficient of variation (CV)0.077188908
Kurtosis-0.060880778
Mean528.3966
Median Absolute Deviation (MAD)8
Skewness1.2908754
Sum5283966
Variance1663.5269
MonotonicityNot monotonic
2023-12-12T12:06:54.385226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
501 2405
24.1%
509 2332
23.3%
502 1073
10.7%
527 1072
10.7%
610 660
 
6.6%
603 483
 
4.8%
505 247
 
2.5%
504 238
 
2.4%
605 199
 
2.0%
604 194
 
1.9%
Other values (15) 1097
11.0%
ValueCountFrequency (%)
401 7
 
0.1%
501 2405
24.1%
502 1073
10.7%
504 238
 
2.4%
505 247
 
2.5%
506 18
 
0.2%
507 114
 
1.1%
509 2332
23.3%
510 193
 
1.9%
511 124
 
1.2%
ValueCountFrequency (%)
612 9
 
0.1%
611 4
 
< 0.1%
610 660
6.6%
609 88
 
0.9%
608 82
 
0.8%
607 106
 
1.1%
606 52
 
0.5%
605 199
 
2.0%
604 194
 
1.9%
603 483
4.8%

처리결과명(PRCS_RESULT_NAME)
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
분쟁해결기준설명
2405 
기타정보제공
2332 
법.제도설명
1073 
피해구제접수안내
1072 
합의불성립
660 
Other values (20)
2458 

Length

Max length11
Median length9
Mean length6.4618
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row피해구제접수안내
2nd row시험결과.의류심의의뢰
3rd row분쟁해결기준설명
4th row분쟁해결기준설명
5th row계약이행

Common Values

ValueCountFrequency (%)
분쟁해결기준설명 2405
24.1%
기타정보제공 2332
23.3%
법.제도설명 1073
10.7%
피해구제접수안내 1072
10.7%
합의불성립 660
 
6.6%
환급 483
 
4.8%
시장정보제공 247
 
2.5%
상품정보제공 238
 
2.4%
계약해제.해지 199
 
2.0%
계약이행 194
 
1.9%
Other values (15) 1097
11.0%

Length

2023-12-12T12:06:54.554647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
분쟁해결기준설명 2405
23.6%
기타정보제공 2332
22.9%
법.제도설명 1073
10.5%
피해구제접수안내 1072
10.5%
합의불성립 660
 
6.5%
환급 483
 
4.7%
시장정보제공 247
 
2.4%
상품정보제공 238
 
2.3%
계약해제.해지 199
 
2.0%
계약이행 194
 
1.9%
Other values (16) 1290
12.7%

Interactions

2023-12-12T12:06:47.057693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:45.528109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:45.994922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:46.470738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:47.204596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:45.673012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:46.097800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:46.611233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:47.343494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:45.791766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:46.217460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:46.743460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:47.469589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:45.902324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:46.337910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:46.902801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:06:54.644126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
접수일자(RCPT_YMD)성별코드(GENDER_CODE)성별(GENDER)연령대코드(AGE_GROUP_CODE)연령대명(AGE_GROUP_NAME)지역코드(AREA_CODE)품목코드(ITEM_CODE)처리결과코드(PRCS_RESULT_CODE)처리결과명(PRCS_RESULT_NAME)
접수일자(RCPT_YMD)1.0000.0410.0410.2060.1910.0000.1860.1080.166
성별코드(GENDER_CODE)0.0411.0001.0000.1290.1690.0150.1700.0510.079
성별(GENDER)0.0411.0001.0000.1290.1690.0150.1700.0510.079
연령대코드(AGE_GROUP_CODE)0.2060.1290.1291.0001.0000.6830.2180.1500.210
연령대명(AGE_GROUP_NAME)0.1910.1690.1691.0001.0000.5500.1560.1600.216
지역코드(AREA_CODE)0.0000.0150.0150.6830.5501.0000.2130.0970.207
품목코드(ITEM_CODE)0.1860.1700.1700.2180.1560.2131.0000.2000.327
처리결과코드(PRCS_RESULT_CODE)0.1080.0510.0510.1500.1600.0970.2001.0001.000
처리결과명(PRCS_RESULT_NAME)0.1660.0790.0790.2100.2160.2070.3271.0001.000
2023-12-12T12:06:54.805809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령대명(AGE_GROUP_NAME)성별(GENDER)처리결과명(PRCS_RESULT_NAME)성별코드(GENDER_CODE)접수일자(RCPT_YMD)
연령대명(AGE_GROUP_NAME)1.0000.1290.0780.1290.066
성별(GENDER)0.1291.0000.0691.0000.034
처리결과명(PRCS_RESULT_NAME)0.0780.0691.0000.0690.038
성별코드(GENDER_CODE)0.1291.0000.0691.0000.034
접수일자(RCPT_YMD)0.0660.0340.0380.0341.000
2023-12-12T12:06:54.939111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령대코드(AGE_GROUP_CODE)지역코드(AREA_CODE)품목코드(ITEM_CODE)처리결과코드(PRCS_RESULT_CODE)접수일자(RCPT_YMD)성별코드(GENDER_CODE)성별(GENDER)연령대명(AGE_GROUP_NAME)처리결과명(PRCS_RESULT_NAME)
연령대코드(AGE_GROUP_CODE)1.0000.068-0.0230.0040.0420.1300.1301.0000.083
지역코드(AREA_CODE)0.0681.000-0.0110.0500.0000.0260.0260.3930.107
품목코드(ITEM_CODE)-0.023-0.0111.000-0.1070.0630.1700.1700.0710.131
처리결과코드(PRCS_RESULT_CODE)0.0040.050-0.1071.0000.0480.0330.0330.0820.999
접수일자(RCPT_YMD)0.0420.0000.0630.0481.0000.0340.0340.0660.038
성별코드(GENDER_CODE)0.1300.0260.1700.0330.0341.0001.0000.1290.069
성별(GENDER)0.1300.0260.1700.0330.0341.0001.0000.1290.069
연령대명(AGE_GROUP_NAME)1.0000.3930.0710.0820.0660.1290.1291.0000.078
처리결과명(PRCS_RESULT_NAME)0.0830.1070.1310.9990.0380.0690.0690.0781.000

Missing values

2023-12-12T12:06:47.663251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:06:47.963852image/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.
2023-12-12T12:06:48.175610image/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

사건번호(ACCIDENT_NO)접수일자(RCPT_YMD)성별코드(GENDER_CODE)성별(GENDER)연령대코드(AGE_GROUP_CODE)연령대명(AGE_GROUP_NAME)지역코드(AREA_CODE)지역명(AREA_NAME)품목코드(ITEM_CODE)품목명(ITEM_NAME)사건제목(ACCIDENT_TITLE)처리결과코드(PRCS_RESULT_CODE)처리결과명(PRCS_RESULT_NAME)
23472020-00029092020-01-031남성1160 - 64세705중구500205투자자문(컨설팅)주식 유료 추천회사 해지환급금 부당요구및 해지지연527피해구제접수안내
143832020-00170642020-01-092여성650 - 59세808부천시170304캐주얼바지청바지 심의결과 궁금 문의511시험결과.의류심의의뢰
14092020-00016352020-01-022여성320 - 29세505서구370408헬스장환불관련 문의501분쟁해결기준설명
626022020-00748752020-02-062여성430 - 39세400인천광역시390102미용서비스미용서비스 선결제 후 사업자 및 디자이너 변경으로 인해 계약해지시 위약금 발생 여부 문의501분쟁해결기준설명
729432020-00864612020-02-112여성1160 - 64세701남구510302상조서비스미래상조119 업체의 생일잔치행사 거절건604계약이행
570472020-00689842020-02-042여성1160 - 64세200부산광역시380209피부과해운대에 있는 피부과 병원 폐업하여 문의 3509기타정보제공
290842020-00353712020-01-202여성650 - 59세306수성구370102국외여행국외여행 해지시 계약금 환불 문의 5501분쟁해결기준설명
526392020-00617832020-02-032여성1080세이상108금천구490301외식팔순잔치 예약취소시 위약금이 너무 과함501분쟁해결기준설명
546332020-00638532020-02-032여성540 - 49세823광주시210113스마트폰휴데폰 구입 으로 기존 휴대폰 저장 내용 없어짐505시장정보제공
449742020-00551352020-01-302여성9불명9900해외 및 기타111399기타건강식품건강식품 관련 문의509기타정보제공
사건번호(ACCIDENT_NO)접수일자(RCPT_YMD)성별코드(GENDER_CODE)성별(GENDER)연령대코드(AGE_GROUP_CODE)연령대명(AGE_GROUP_NAME)지역코드(AREA_CODE)지역명(AREA_NAME)품목코드(ITEM_CODE)품목명(ITEM_NAME)사건제목(ACCIDENT_TITLE)처리결과코드(PRCS_RESULT_CODE)처리결과명(PRCS_RESULT_NAME)
692262020-00814782020-02-081남성320 - 29세111동대문구370202호텔여행 상품 취소불가 조건 해결 문의502법.제도설명
34152020-00043182020-01-032여성1265 - 69세500광주광역시111409다이어트식품다이어트 식품 섭취 후 출혈로 인한 환불 요청602교환
735562020-00858062020-02-112여성320 - 29세9900해외 및 기타380206성형외과환불 규정 문의501분쟁해결기준설명
729652020-00852322020-02-102여성430 - 39세200부산광역시350104항공여객운송서비스항공기 예약 취소 환불 규정 문의(공)610합의불성립
35152020-00043442020-01-031남성430 - 39세300대구광역시350211퀵서비스퀵서비스 계약금 환불요청610합의불성립
96552020-00115002020-01-071남성650 - 59세600대전광역시139912정수기대여(렌트)정수기 품질로 인한 불만509기타정보제공
6872020-00009102020-01-022여성540 - 49세827양평군370403종합체육시설회원권학원 수강중 해지시 위약금 문의603환급
105962020-00125482020-01-082여성9불명800경기도299999기타미분류물품네이버 뉴스 구독 취소 문의509기타정보제공
460462020-00546802020-01-302여성650 - 59세400인천광역시370102국외여행인터파크 해외여행 우한폐렴으로 인한 환불 문의610합의불성립
159562020-00181082020-01-102여성540 - 49세1200전라북도370299기타숙박시설팬션에 예약후 위약금501분쟁해결기준설명