chunks | 易学教程

Splitting vector based on vector of chunk-lengths

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问题 I've got a vector of binary numbers. I know the consecutive length of each group of objects; how can I split based on that information (without for loop)? x = c("1","0","1","0","0","0","0","0","1") .length = c(group1 = 2,group2=4, group3=3) x is the binary number vector that I need to split. .length is the information that I am given. .length essentially tells me that the first group has 2 elements and they are the first two elements 1,0 . The second group has 4 elements and contain the 4

R:Loops to process large dataset(GBs) in chunks?

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问题 I have a large data set in GBs that I'd have to process before I analyse them. I tried creating a connector, which allows me to loop through the large datasets and extract chunks at a time.This allows me to quarantine data that satisfies some conditions. My problem is that I am not able to create an indicator for the connector that stipulates it is null and to execute close(connector) when the end of the dataset is reached. Moreover, for the first chunk of extracted data, I'd have to skip 17

How do you split reading a large csv file into evenly-sized chunks in Python?

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In a basic I had the next process. import csv reader = csv.reader(open('huge_file.csv', 'rb')) for line in reader: process_line(line) See this related question . I want to send the process line every 100 rows, to implement batch sharding. The problem about implementing the related answer is that csv object is unsubscriptable and can not use len. >>> import csv >>> reader = csv.reader(open('dataimport/tests/financial_sample.csv', 'rb')) >>> len(reader) Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: object of type '_csv.reader' has no len() >>> reader[10:]

Process data, much larger than physical memory, in chunks

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问题 I need to process some data that is a few hundred times bigger than RAM. I would like to read in a large chunk, process it, save the result, free the memory and repeat. Is there a way to make this efficient in python? 回答1: The general key is that you want to process the file iteratively. If you're just dealing with a text file, this is trivial: for line in f: only reads in one line at a time. (Actually it buffers things up, but the buffers are small enough that you don't have to worry about

How to change knitr options mid chunk

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问题 Hi I would like to change chunk options, mid chunk, without having to create a new chunk.. running the following code I would expect to get two very different size outputs, but for some reason this does not seem to be the case. Also the second plot doesn't plot at all...(it does when you change it to plot(2:1000)...but either way the second output is the same size as the first. both fig.width=7 . What am I doing wrong? Pls note the importance of 'mid chunk' the reason for this is that I would

Splitting a string into chunks by numeric or alpha char with Javascript

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问题 So I have this: var str = A123B234C456; I need to split it into comma separated chunks to return something like this: A,123,B,234,c,456 I thought regex would be best for this but i keep getting stuck, essentially I tried to do a string replace but you cannot use regex in the second argument I would love to keep it simple and clean and do something like this but it does not work: str = str.replace(/[\d]+/, ","+/[\d]+/); but in the real world that would be too simple. Any thoughts? Thanks in

How do you split reading a large csv file into evenly-sized chunks in Python?

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问题 In a basic I had the next process. import csv reader = csv.reader(open('huge_file.csv', 'rb')) for line in reader: process_line(line) See this related question. I want to send the process line every 100 rows, to implement batch sharding. The problem about implementing the related answer is that csv object is unsubscriptable and can not use len. >>> import csv >>> reader = csv.reader(open('dataimport/tests/financial_sample.csv', 'rb')) >>> len(reader) Traceback (most recent call last): File "

What is the most “pythonic” way to iterate over a list in chunks?

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问题 I have a Python script which takes as input a list of integers, which I need to work with four integers at a time. Unfortunately, I don\'t have control of the input, or I\'d have it passed in as a list of four-element tuples. Currently, I\'m iterating over it this way: for i in xrange(0, len(ints), 4): # dummy op for example code foo += ints[i] * ints[i + 1] + ints[i + 2] * ints[i + 3] It looks a lot like \"C-think\", though, which makes me suspect there\'s a more pythonic way of dealing with

How to read a 6 GB csv file with pandas

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问题 I am trying to read a large csv file (aprox. 6 GB) in pandas and i am getting the following memory error: MemoryError Traceback (most recent call last) <ipython-input-58-67a72687871b> in <module>() ----> 1 data=pd.read_csv(\'aphro.csv\',sep=\';\') C:\\Python27\\lib\\site-packages\\pandas\\io\\parsers.pyc in parser_f(filepath_or_buffer, sep, dialect, compression, doublequote, escapechar, quotechar, quoting, skipinitialspace, lineterminator, header, index_col, names, prefix, skiprows,

How do you split a list into evenly sized chunks?

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问题 I have a list of arbitrary length, and I need to split it up into equal size chunks and operate on it. There are some obvious ways to do this, like keeping a counter and two lists, and when the second list fills up, add it to the first list and empty the second list for the next round of data, but this is potentially extremely expensive. I was wondering if anyone had a good solution to this for lists of any length, e.g. using generators. I was looking for something useful in itertools but I