Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory654.3 KiB
Average record size in memory67.0 B

Variable types

Text4
Numeric2
Categorical1

Dataset

Description품목,단위(등급),전주평균,금주평균,등락율,해당일자
Author서울시농수산식품공사
URLhttps://data.seoul.go.kr/dataList/OA-13447/S/1/datasetView.do

Alerts

(구분) has constant value ""Constant

Reproduction

Analysis started2024-05-11 06:42:07.958193
Analysis finished2024-05-11 06:42:09.923690
Duration1.97 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품목
Text

Distinct285
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:42:10.264396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length4.5905
Min length1

Characters and Unicode

Total characters45905
Distinct characters275
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)0.1%

Sample

1st row가지
2nd row청상추
3rd row비트 국산
4th row비타민
5th row감자 두백
ValueCountFrequency (%)
딸기 516
 
3.8%
수입 479
 
3.5%
사과 358
 
2.6%
양파 291
 
2.1%
고구마 283
 
2.1%
생표고 253
 
1.8%
토마토 244
 
1.8%
감귤 234
 
1.7%
만감 231
 
1.7%
국산 219
 
1.6%
Other values (284) 10638
77.4%
2024-05-11T15:42:10.985878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3746
 
8.2%
추 1570
 
3.4%
고 1241
 
2.7%
) 1228
 
2.7%
( 1228
 
2.7%
양 1013
 
2.2%
파 880
 
1.9%
기 870
 
1.9%
수 829
 
1.8%
마 822
 
1.8%
Other values (265) 32478
70.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39670
86.4%
Space Separator 3746
 
8.2%
Close Punctuation 1228
 
2.7%
Open Punctuation 1228
 
2.7%
Uppercase Letter 33
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
추 1570
 
4.0%
고 1241
 
3.1%
양 1013
 
2.6%
파 880
 
2.2%
기 870
 
2.2%
수 829
 
2.1%
마 822
 
2.1%
일 820
 
2.1%
감 810
 
2.0%
리 801
 
2.0%
Other values (259) 30014
75.7%
Uppercase Letter
ValueCountFrequency (%)
M 11
33.3%
B 11
33.3%
A 11
33.3%
Space Separator
ValueCountFrequency (%)
3746
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1228
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1228
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39670
86.4%
Common 6202
 
13.5%
Latin 33
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
추 1570
 
4.0%
고 1241
 
3.1%
양 1013
 
2.6%
파 880
 
2.2%
기 870
 
2.2%
수 829
 
2.1%
마 822
 
2.1%
일 820
 
2.1%
감 810
 
2.0%
리 801
 
2.0%
Other values (259) 30014
75.7%
Common
ValueCountFrequency (%)
3746
60.4%
) 1228
 
19.8%
( 1228
 
19.8%
Latin
ValueCountFrequency (%)
M 11
33.3%
B 11
33.3%
A 11
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39670
86.4%
ASCII 6235
 
13.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3746
60.1%
) 1228
 
19.7%
( 1228
 
19.7%
M 11
 
0.2%
B 11
 
0.2%
A 11
 
0.2%
Hangul
ValueCountFrequency (%)
추 1570
 
4.0%
고 1241
 
3.1%
양 1013
 
2.6%
파 880
 
2.2%
기 870
 
2.2%
수 829
 
2.1%
마 822
 
2.1%
일 820
 
2.1%
감 810
 
2.0%
리 801
 
2.0%
Other values (259) 30014
75.7%

단위(등급)
Text

Distinct225
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:42:11.454902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length8.0791
Min length5

Characters and Unicode

Total characters80791
Distinct characters37
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)0.2%

Sample

1st row8키로상자(상)
2nd row4키로상자(상)
3rd row10키로상자(중)
4th row2키로상자(하)
5th row20키로상자(하)
ValueCountFrequency (%)
10키로상자(상 564
 
5.6%
10키로상자(중 558
 
5.6%
10키로상자(하 538
 
5.4%
10키로상자(특 439
 
4.4%
4키로상자(상 410
 
4.1%
4키로상자(중 366
 
3.7%
4키로상자(하 346
 
3.5%
2키로상자(상 300
 
3.0%
2키로상자(중 291
 
2.9%
5키로상자(상 277
 
2.8%
Other values (211) 5911
59.1%
2024-05-11T15:42:12.108497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
상 10263
12.7%
( 10048
12.4%
) 10048
12.4%
키 9476
11.7%
로 9476
11.7%
자 7333
9.1%
1 4534
5.6%
0 3726
 
4.6%
중 2801
 
3.5%
하 2553
 
3.2%
Other values (27) 10533
13.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45673
56.5%
Decimal Number 14599
 
18.1%
Open Punctuation 10048
 
12.4%
Close Punctuation 10048
 
12.4%
Other Punctuation 423
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 10263
22.5%
키 9476
20.7%
로 9476
20.7%
자 7333
16.1%
중 2801
 
6.1%
하 2553
 
5.6%
특 1527
 
3.3%
대 403
 
0.9%
단 343
 
0.8%
개 342
 
0.7%
Other values (14) 1156
 
2.5%
Decimal Number
ValueCountFrequency (%)
1 4534
31.1%
0 3726
25.5%
2 1849
12.7%
5 1683
 
11.5%
4 1394
 
9.5%
8 750
 
5.1%
3 425
 
2.9%
6 145
 
1.0%
9 57
 
0.4%
7 36
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 10048
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10048
100.0%
Other Punctuation
ValueCountFrequency (%)
. 423
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45673
56.5%
Common 35118
43.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 10263
22.5%
키 9476
20.7%
로 9476
20.7%
자 7333
16.1%
중 2801
 
6.1%
하 2553
 
5.6%
특 1527
 
3.3%
대 403
 
0.9%
단 343
 
0.8%
개 342
 
0.7%
Other values (14) 1156
 
2.5%
Common
ValueCountFrequency (%)
( 10048
28.6%
) 10048
28.6%
1 4534
12.9%
0 3726
 
10.6%
2 1849
 
5.3%
5 1683
 
4.8%
4 1394
 
4.0%
8 750
 
2.1%
3 425
 
1.2%
. 423
 
1.2%
Other values (3) 238
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45673
56.5%
ASCII 35118
43.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
상 10263
22.5%
키 9476
20.7%
로 9476
20.7%
자 7333
16.1%
중 2801
 
6.1%
하 2553
 
5.6%
특 1527
 
3.3%
대 403
 
0.9%
단 343
 
0.8%
개 342
 
0.7%
Other values (14) 1156
 
2.5%
ASCII
ValueCountFrequency (%)
( 10048
28.6%
) 10048
28.6%
1 4534
12.9%
0 3726
 
10.6%
2 1849
 
5.3%
5 1683
 
4.8%
4 1394
 
4.0%
8 750
 
2.1%
3 425
 
1.2%
. 423
 
1.2%
Other values (3) 238
 
0.7%

전주평균
Text

Distinct7224
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:42:12.684191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length6
Mean length5.7964
Min length3

Characters and Unicode

Total characters57964
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

Unique5059 ?
Unique (%)50.6%

Sample

1st row28,220
2nd row11,344
3rd row13,280
4th row3,248
5th row19,320
ValueCountFrequency (%)
24,000 7
 
0.1%
10,856 7
 
0.1%
28,220 6
 
0.1%
350 6
 
0.1%
31,000 6
 
0.1%
28,000 6
 
0.1%
11,214 5
 
< 0.1%
22,000 5
 
< 0.1%
43,000 5
 
< 0.1%
4,597 5
 
< 0.1%
Other values (7214) 9942
99.4%
2024-05-11T15:42:13.643259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 9913
17.1%
1 7074
12.2%
2 5862
10.1%
3 5312
9.2%
0 4534
7.8%
4 4468
7.7%
5 4393
7.6%
6 4383
7.6%
7 4202
7.2%
8 4113
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48051
82.9%
Other Punctuation 9913
 
17.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7074
14.7%
2 5862
12.2%
3 5312
11.1%
0 4534
9.4%
4 4468
9.3%
5 4393
9.1%
6 4383
9.1%
7 4202
8.7%
8 4113
8.6%
9 3710
7.7%
Other Punctuation
ValueCountFrequency (%)
, 9913
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57964
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 9913
17.1%
1 7074
12.2%
2 5862
10.1%
3 5312
9.2%
0 4534
7.8%
4 4468
7.7%
5 4393
7.6%
6 4383
7.6%
7 4202
7.2%
8 4113
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57964
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 9913
17.1%
1 7074
12.2%
2 5862
10.1%
3 5312
9.2%
0 4534
7.8%
4 4468
7.7%
5 4393
7.6%
6 4383
7.6%
7 4202
7.2%
8 4113
7.1%

금주평균
Text

Distinct8567
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:42:14.230861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length5.7219
Min length3

Characters and Unicode

Total characters57219
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

Unique7484 ?
Unique (%)74.8%

Sample

1st row25,011
2nd row10,382
3rd row12,534
4th row2,073
5th row18,471
ValueCountFrequency (%)
45,000 15
 
0.1%
15,000 15
 
0.1%
16,500 13
 
0.1%
16,000 11
 
0.1%
32,000 11
 
0.1%
12,000 10
 
0.1%
25,000 9
 
0.1%
22,000 9
 
0.1%
26,000 8
 
0.1%
20,000 7
 
0.1%
Other values (8557) 9892
98.9%
2024-05-11T15:42:15.057445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 9877
17.3%
1 6945
12.1%
2 5521
9.6%
0 5053
8.8%
3 4970
8.7%
4 4472
7.8%
5 4412
7.7%
6 4199
7.3%
8 4022
7.0%
7 4021
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 47342
82.7%
Other Punctuation 9877
 
17.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6945
14.7%
2 5521
11.7%
0 5053
10.7%
3 4970
10.5%
4 4472
9.4%
5 4412
9.3%
6 4199
8.9%
8 4022
8.5%
7 4021
8.5%
9 3727
7.9%
Other Punctuation
ValueCountFrequency (%)
, 9877
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57219
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 9877
17.3%
1 6945
12.1%
2 5521
9.6%
0 5053
8.8%
3 4970
8.7%
4 4472
7.8%
5 4412
7.7%
6 4199
7.3%
8 4022
7.0%
7 4021
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57219
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 9877
17.3%
1 6945
12.1%
2 5521
9.6%
0 5053
8.8%
3 4970
8.7%
4 4472
7.8%
5 4412
7.7%
6 4199
7.3%
8 4022
7.0%
7 4021
7.0%

등락율
Real number (ℝ)

Distinct78
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.7338
Minimum8
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:42:15.380221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile60
Q179
median89
Q395
95-th percentile99
Maximum100
Range92
Interquartile range (IQR)16

Descriptive statistics

Standard deviation12.465227
Coefficient of variation (CV)0.14539454
Kurtosis1.9519032
Mean85.7338
Median Absolute Deviation (MAD)7
Skewness-1.3393063
Sum857338
Variance155.38188
MonotonicityNot monotonic
2024-05-11T15:42:15.646758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
98 550
 
5.5%
99 549
 
5.5%
96 515
 
5.1%
97 503
 
5.0%
95 482
 
4.8%
94 437
 
4.4%
92 437
 
4.4%
91 392
 
3.9%
93 376
 
3.8%
90 372
 
3.7%
Other values (68) 5387
53.9%
ValueCountFrequency (%)
8 1
 
< 0.1%
10 1
 
< 0.1%
21 1
 
< 0.1%
22 1
 
< 0.1%
24 2
< 0.1%
26 1
 
< 0.1%
27 2
< 0.1%
30 2
< 0.1%
31 2
< 0.1%
32 3
< 0.1%
ValueCountFrequency (%)
100 300
3.0%
99 549
5.5%
98 550
5.5%
97 503
5.0%
96 515
5.1%
95 482
4.8%
94 437
4.4%
93 376
3.8%
92 437
4.4%
91 392
3.9%

해당일자
Real number (ℝ)

Distinct194
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20237211
Minimum20231024
Maximum20240510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:42:15.910698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20231024
5-th percentile20231102
Q120231211
median20240207
Q320240329
95-th percentile20240501
Maximum20240510
Range9486
Interquartile range (IQR)9118

Descriptive statistics

Standard deviation4330.8763
Coefficient of variation (CV)0.00021400559
Kurtosis-1.5264174
Mean20237211
Median Absolute Deviation (MAD)206
Skewness-0.68638925
Sum2.0237211 × 1011
Variance18756489
MonotonicityNot monotonic
2024-05-11T15:42:16.465643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20240413 87
 
0.9%
20240410 79
 
0.8%
20231129 79
 
0.8%
20240412 79
 
0.8%
20240409 78
 
0.8%
20231031 77
 
0.8%
20240328 77
 
0.8%
20231214 77
 
0.8%
20231212 76
 
0.8%
20240411 76
 
0.8%
Other values (184) 9215
92.2%
ValueCountFrequency (%)
20231024 13
 
0.1%
20231025 52
0.5%
20231026 48
0.5%
20231027 48
0.5%
20231028 57
0.6%
20231029 53
0.5%
20231030 56
0.6%
20231031 77
0.8%
20231101 75
0.8%
20231102 65
0.7%
ValueCountFrequency (%)
20240510 44
0.4%
20240509 59
0.6%
20240508 64
0.6%
20240507 60
0.6%
20240506 49
0.5%
20240505 60
0.6%
20240504 55
0.5%
20240503 46
0.5%
20240502 61
0.6%
20240501 59
0.6%

(구분)
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
33
10000 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row33
2nd row33
3rd row33
4th row33
5th row33

Common Values

ValueCountFrequency (%)
33 10000
100.0%

Length

2024-05-11T15:42:16.683043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:16.833140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
33 10000
100.0%

Interactions

2024-05-11T15:42:09.193083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:08.861767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:09.381236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:09.042069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:42:16.922278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등락율해당일자
등락율1.0000.023
해당일자0.0231.000
2024-05-11T15:42:17.060166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등락율해당일자
등락율1.000-0.017
해당일자-0.0171.000

Missing values

2024-05-11T15:42:09.627678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:42:09.837451image/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

품목단위(등급)전주평균금주평균등락율해당일자(구분)
7325가지8키로상자(상)28,22025,011892024042833
47992청상추4키로상자(상)11,34410,382922024021333
74448비트 국산10키로상자(중)13,28012,534942023121133
9928비타민2키로상자(하)3,2482,073642024042333
76907감자 두백20키로상자(하)19,32018,471962023120533
52959감자 대지마20키로상자(상)45,07042,486942024013033
53492청양고추10키로상자(특)130,382128,788992024012833
94344오이맛고추10키로상자(특)61,67849,421802023110333
30120백다다기오이100개(하)66,68962,689942024032133
20203아보카도 수입5키로상자(중)14,43812,319852024040733
품목단위(등급)전주평균금주평균등락율해당일자(구분)
97324포도 거봉2키로상자(상)14,76013,169892023102933
22768참두릅(자연산)1키로(중)46,18932,981712024040233
77862주꾸미 수입3키로상자(중)20,16318,908942023120333
49073감귤 온주5키로상자(상)28,19525,718912024020733
47840대파(일반)1키로단(상)3,6732,835772024021433
75736홍고추10키로상자(하)39,84437,095932023120833
67522건오징어 근해1키로(상)56,38355,325982023122533
7809상추 포기찹4키로상자(하)6,7356,082902024042733
59822활 돔(자연)1키로(중)23,81616,265682024011333
64253영양부추200그람단(중)7,4467,177962024010533