chunks

问题 Is there any option to load a pickle file in chunks? I know we can save the data in CSV and load it in chunks. But other than CSV, is there any option to load a pickle file or any python native file in chunks? 来源： https://stackoverflow.com/questions/59983073/how-to-load-pickle-file-in-chunks

问题 I have array of strings const arr = ['some', 'word', 'anotherverylongword', 'word', 'yyy', 'u'] const joined = arr.join(';') I want to get array of chunks where joined string length is not greater than 10 for example output would be: [ ['some;word'], // joined string length not greater than 10 ['anotherverylongword'], // string length greater than 10, so is separated ['word;yyy;u'] // joined string length is 10 ] 回答1: You can use reduce (with some spread syntax and slice) to generate such

问题 I have array of strings const arr = ['some', 'word', 'anotherverylongword', 'word', 'yyy', 'u'] const joined = arr.join(';') I want to get array of chunks where joined string length is not greater than 10 for example output would be: [ ['some;word'], // joined string length not greater than 10 ['anotherverylongword'], // string length greater than 10, so is separated ['word;yyy;u'] // joined string length is 10 ] 回答1: You can use reduce (with some spread syntax and slice) to generate such

问题 I want to read the file f (file size:85GB) in chunks to a dataframe. Following code is suggested. chunksize = 5 TextFileReader = pd.read_csv(f, chunksize=chunksize) However, this code gives me TextFileReader, not dataframe. Also, I don't want to concatenate these chunks to convert TextFileReader to dataframe because of the memory limit. Please advise. 回答1: As you are trying to process 85GB CSV file, if you will try to read all the data by breaking it into chunks and converting it into

问题 I want to read the file f (file size:85GB) in chunks to a dataframe. Following code is suggested. chunksize = 5 TextFileReader = pd.read_csv(f, chunksize=chunksize) However, this code gives me TextFileReader, not dataframe. Also, I don't want to concatenate these chunks to convert TextFileReader to dataframe because of the memory limit. Please advise. 回答1: As you are trying to process 85GB CSV file, if you will try to read all the data by breaking it into chunks and converting it into

问题 I want to read the file f (file size:85GB) in chunks to a dataframe. Following code is suggested. chunksize = 5 TextFileReader = pd.read_csv(f, chunksize=chunksize) However, this code gives me TextFileReader, not dataframe. Also, I don't want to concatenate these chunks to convert TextFileReader to dataframe because of the memory limit. Please advise. 回答1: As you are trying to process 85GB CSV file, if you will try to read all the data by breaking it into chunks and converting it into

问题 I am trying to download data using a Webclient object in chunks of 5% each. The reason is that I need to report progress for each downloaded chunk. Here is the code I wrote to do this task: private void ManageDownloadingByExtractingContentDisposition(WebClient client, Uri uri) { //Initialize the downloading stream Stream str = client.OpenRead(uri.PathAndQuery); WebHeaderCollection whc = client.ResponseHeaders; string contentDisposition = whc["Content-Disposition"]; string contentLength = whc[

问题 If I have a csv file that's too large to load into memory with pandas (in this case 35gb), I know it's possible to process the file in chunks, with chunksize. However I want to know if it's possible to change chunksize based on values in a column. I have an ID column, and then several rows for each ID with information, like this: ID, Time, x, y sasd, 10:12, 1, 3 sasd, 10:14, 1, 4 sasd, 10:32, 1, 2 cgfb, 10:02, 1, 6 cgfb, 10:13, 1, 3 aenr, 11:54, 2, 5 tory, 10:27, 1, 3 tory, 10:48, 3, 5 ect...

问题 If I have a csv file that's too large to load into memory with pandas (in this case 35gb), I know it's possible to process the file in chunks, with chunksize. However I want to know if it's possible to change chunksize based on values in a column. I have an ID column, and then several rows for each ID with information, like this: ID, Time, x, y sasd, 10:12, 1, 3 sasd, 10:14, 1, 4 sasd, 10:32, 1, 2 cgfb, 10:02, 1, 6 cgfb, 10:13, 1, 3 aenr, 11:54, 2, 5 tory, 10:27, 1, 3 tory, 10:48, 3, 5 ect...

问题 I recently updated my RStudio and while writing an R Markdown document in the Source Window, whenever I run a code in a chunk of the RMD, the output is shown in the source window itself in the following manner. It gets too messy when there are huge plots. Would like to disable this feature if possible and revert back to good old style of displaying output in the Console/Plot viewer window only. Output executed and visible below the Chunk in the Source Window Thanks 回答1: Try this in Rstudio.