count

问题 I have read much in textbooks and browsed a lot of pages on the internet but I can't understand how functions/operators like min, max, count, ... that aggregate over a relation/table or groups of tuples/rows in a relation/table are built with basic operations such as ∪ (union), ∩ (intersection), x (join), - (minus), π (projection), .... Can anyone show me how to express these functions/operators with relational algebra? 回答1: Computing functions in relation algebra are not fully included yet.

问题 I have a pandas dataframe that looks as follows: ID round player1 player2 1 1 A B 1 2 A C 1 3 B D 2 1 B C 2 2 C D 2 3 C E 3 1 B C 3 2 C D 3 3 C A The dataframe contains sport match results, where the ID column denotes one tournament, the round column denotes the round for each tournament, and player1 and player2 columns contain the names of players that played against eachother in the respective round . I now want to cumulatively count the tournament participations for, say, player A . In

问题 I want to do what they've done in the answer here: Calculating the number of specific consecutive equal values in a vectorized way in pandas , but using a grouped dataframe instead of a series. So given a dataframe with several columns A B C ------------ x x 0 x x 5 x x 2 x x 0 x x 0 x x 3 x x 0 y x 1 y x 10 y x 0 y x 5 y x 0 y x 0 I want to groupby columns A and B, then count the number of consecutive zeros in C. After that I'd like to return counts of the number of times each length of

问题 Sample data frame data uid bas_id dist2mouth type 2020 2019 W3A9101601 2.413629 1 2021 2020 W3A9101601 2.413629 1 2022 2021 W3A9101602 2.413629 1 2023 2022 W3A9101602 3.313893 1 2032 2031 W3A9101602 3.313893 1 2033 2032 W3A9101602 3.313893 1 2034 2033 W3A9101602 3.313893 1 15023 15022 W3A9101601 1.349000 2 15025 15024 W3A9101601 3.880000 2 15026 15025 W3A9101602 3.880000 2 15027 15026 W3A9101602 0.541101 2 16106 17097 W3A9101602 1.349000 2 For each row I'd like to calculate how many rows of

问题 Sample data frame data uid bas_id dist2mouth type 2020 2019 W3A9101601 2.413629 1 2021 2020 W3A9101601 2.413629 1 2022 2021 W3A9101602 2.413629 1 2023 2022 W3A9101602 3.313893 1 2032 2031 W3A9101602 3.313893 1 2033 2032 W3A9101602 3.313893 1 2034 2033 W3A9101602 3.313893 1 15023 15022 W3A9101601 1.349000 2 15025 15024 W3A9101601 3.880000 2 15026 15025 W3A9101602 3.880000 2 15027 15026 W3A9101602 0.541101 2 16106 17097 W3A9101602 1.349000 2 For each row I'd like to calculate how many rows of

问题 Sample data frame data uid bas_id dist2mouth type 2020 2019 W3A9101601 2.413629 1 2021 2020 W3A9101601 2.413629 1 2022 2021 W3A9101602 2.413629 1 2023 2022 W3A9101602 3.313893 1 2032 2031 W3A9101602 3.313893 1 2033 2032 W3A9101602 3.313893 1 2034 2033 W3A9101602 3.313893 1 15023 15022 W3A9101601 1.349000 2 15025 15024 W3A9101601 3.880000 2 15026 15025 W3A9101602 3.880000 2 15027 15026 W3A9101602 0.541101 2 16106 17097 W3A9101602 1.349000 2 For each row I'd like to calculate how many rows of

问题 I have two tables. Table 1: +------------+-------------+------+-----+---------+-------+ | Field | Type | Null | Key | Default | Extra | +------------+-------------+------+-----+---------+-------+ | ID | varchar(255)| NO | PRI | NULL | | | Sex | int(20) | YES | | NULL | | | Age | varchar(255)| YES | | NULL | | +------------+-------------+------+-----+---------+-------+ Table 2: +-----------+--------------+------+-----+---------+-------+ | Field | Type | Null | Key | Default | Extra | +--------

问题 New to R and would like to do the following operation: I have a set of numbers e.g. (1,1,0,1,1,1,0,0,1) and need to count adjacent duplicates as they occur. The result I am looking for is: 2,1,3,2,1 as in 2 ones, 1 zero, 3 ones, etc. Thanks. 回答1: We can use rle rle(v1)$lengths #[1] 2 1 3 2 1 data v1 <- c(1,1,0,1,1,1,0,0,1) 来源： https://stackoverflow.com/questions/33528106/r-counting-adjacent-duplicate-items

问题 The data: index = [('A', 'aa', 'aaa'), ('A', 'aa', 'aab'), ('B', 'bb', 'bbb'), ('B', 'bb', 'bbc'), ('C', 'cc', 'ccc') ] values = [0.07, 0.04, 0.04, 0.06, 0.07] s = pd.Series(data=values, index=pd.MultiIndex.from_tuples(index)) s A aa aaa 0.07 aab 0.04 B bb bbb 0.04 bbc 0.06 C cc ccc 0.07 To get a mean of first two levels is easy: s.mean(level=[0,1]) Result: A aa 0.055 B bb 0.050 C cc 0.070 But to get a count on first two levels does not work the same: #s.count(level=[0,1]) # does not work I

问题 This question already has answers here : How to use dplyr as alternative to aggregate (2 answers) Count number of rows within each group (15 answers) Closed 1 year ago . I would like to generate a table with groups per range, the mean and the count of variables in each group. I have a data.frame like below: Variable Shap 1 0.10 6 0.50 7 0.30 5 0.40 9 0.10 9 0.25 2 0.24 9 0.23 5 0.22 5 0.21 1 0.20 4 0.19 5 0.18 8 0.17 6 0.16 And would like to get a dataframe like this Range Shap_Avg Counts 0-5