Use center in pandas rolling when using a time-series
来源： https://stackoverflow.com/questions/47014765/use-center-in-pandas-rolling-when-using-a-time-series
rolling-sum
Use center in pandas rolling when using a time-series
来源： https://stackoverflow.com/questions/47014765/use-center-in-pandas-rolling-when-using-a-time-series
how to do forward rolling sum in pandas?
问题 I have this dataframe: dates = pd.date_range(start='2016-01-01', periods=20, freq='d') df = pd.DataFrame({'A': [1] * 20 + [2] * 12 + [3] * 8, 'B': np.concatenate((dates, dates)), 'C': np.arange(40)}) I sorted the data frame by Date: df.sort_values('B',inplace=True) I am looking to do a forward rolling sum on date. However, I can only do backward rolling sum using: df.groupby('A').rolling(7, on='B',min_periods=0).C.sum() A B 1 2016-01-01 0.0 2016-01-02 1.0 2016-01-03 3.0 2016-01-04 6.0 2016-01
Conditional rolling sum of events with 'ragged' dates
问题 Introduction I am using R to analyze the 'momentum' of protest movements in Africa. To do so, I am analyzing individual protest events. I want to create a rolling measure of the rolling number (sum) of protests within a time period . Most of the answers here on Stack Overflow deal with datasets where observations are at fixed intervals (one obs. per day or per month, etc.). But my data are 'ragged' in the sense that they occur in different intervals. Sometimes there is one day between
Calculating sum of array elements and reiterate for entire array in MATLAB
问题 I have a vector A of size 7812x1 and would like to calculate the sum of fixed windows of length 21 (so 372 blocks). This should be reiterated, so that the output should return a vector of size 372x1. I have t=7812 , p=372 , w=21 ; for t=1:p out = sum(A((t*w-w+1):(t*w))); end This code, however, does not work. My idea is that the part ((t*w-w+1):(t*w)) allows for something like a rolling window. The window is of length 21, so there is not really a need to express is with variables, yet I think
Rolling sum in dplyr
问题 set.seed(123) df <- data.frame(x = sample(1:10, 20, replace = T), id = rep(1:2, each = 10)) For each id , I want to create a column which has the sum of previous 5 x values. df %>% group_by(id) %>% mutate(roll.sum = c(x[1:4], zoo::rollapply(x, 5, sum))) # Groups: id [2] x id roll.sum <int> <int> <int> 3 1 3 8 1 8 5 1 5 9 1 9 10 1 10 1 1 36 6 1 39 9 1 40 6 1 41 5 1 37 10 2 10 5 2 5 7 2 7 6 2 6 2 2 2 9 2 39 3 2 32 1 2 28 4 2 25 10 2 29 The 6th row should be 35 (3 + 8 + 5 + 9 + 10) , the 7th row
Rolling sum in dplyr
set.seed(123) df <- data.frame(x = sample(1:10, 20, replace = T), id = rep(1:2, each = 10)) For each id , I want to create a column which has the sum of previous 5 x values. df %>% group_by(id) %>% mutate(roll.sum = c(x[1:4], zoo::rollapply(x, 5, sum))) # Groups: id [2] x id roll.sum <int> <int> <int> 3 1 3 8 1 8 5 1 5 9 1 9 10 1 10 1 1 36 6 1 39 9 1 40 6 1 41 5 1 37 10 2 10 5 2 5 7 2 7 6 2 6 2 2 2 9 2 39 3 2 32 1 2 28 4 2 25 10 2 29 The 6th row should be 35 (3 + 8 + 5 + 9 + 10) , the 7th row should be 33 (8 + 5 + 9 + 10 + 1) and so on. However, the above function is also including the row
how to do forward rolling sum in pandas?
I have this dataframe: dates = pd.date_range(start='2016-01-01', periods=20, freq='d') df = pd.DataFrame({'A': [1] * 20 + [2] * 12 + [3] * 8, 'B': np.concatenate((dates, dates)), 'C': np.arange(40)}) I sorted the data frame by Date: df.sort_values('B',inplace=True) I am looking to do a forward rolling sum on date. However, I can only do backward rolling sum using: df.groupby('A').rolling(7, on='B',min_periods=0).C.sum() A B 1 2016-01-01 0.0 2016-01-02 1.0 2016-01-03 3.0 2016-01-04 6.0 2016-01-05 10.0 2016-01-06 15.0 I want to do forward rolling sum. I believe need change ordering by iloc[::-1]
Pandas rolling sum on string column
问题 I'm using Python3 with pandas version '0.19.2'. I have a pandas df as follows: chat_id line 1 'Hi.' 1 'Hi, how are you?.' 1 'I'm well, thanks.' 2 'Is it going to rain?.' 2 'No, I don't think so.' I want to group by 'chat_id', then do something like a rolling sum on 'line' to get the following: chat_id line conversation 1 'Hi.' 'Hi.' 1 'Hi, how are you?.' 'Hi. Hi, how are you?.' 1 'I'm well, thanks.' 'Hi. Hi, how are you?. I'm well, thanks.' 2 'Is it going to rain?.' 'Is it going to rain?.' 2
Pandas rolling sum on string column
I'm using Python3 with pandas version '0.19.2'. I have a pandas df as follows: chat_id line 1 'Hi.' 1 'Hi, how are you?.' 1 'I'm well, thanks.' 2 'Is it going to rain?.' 2 'No, I don't think so.' I want to group by 'chat_id', then do something like a rolling sum on 'line' to get the following: chat_id line conversation 1 'Hi.' 'Hi.' 1 'Hi, how are you?.' 'Hi. Hi, how are you?.' 1 'I'm well, thanks.' 'Hi. Hi, how are you?. I'm well, thanks.' 2 'Is it going to rain?.' 'Is it going to rain?.' 2 'No, I don't think so.' 'Is it going to rain?. No, I don't think so.' I believe df.groupby('chat_id')[