apply | 易学教程

Parsing text file of one line JSON objects using RJSONIO

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问题 What I want: I would like to parse a text file of the form {"business_id": "rncjoVoEFUJGCUoC1JgnUA", "full_address": "8466 W Peoria Ave\nSte 6\nPeoria, AZ 85345", "open": true, "categories": ["Accountants", "Professional Services", "Tax Services", "Financial Services"], "city": "Peoria", "review_count": 3, "name": "Peoria Income Tax Service", "neighborhoods": [], "longitude": -112.241596, "state": "AZ", "stars": 5.0, "latitude": 33.581867000000003, "type": "business"} {"business_id":

Optimizing replacement in a data frame

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问题 This is an extension of Update pairs of columns based on pattern in their names . Thus, this is partially motivated by curiosity and partially for entertainment. While developing an answer to that question, it occurred to me that this may be one of those cases where a for loop is more efficient than an *apply function (and I've been looking for a good illustration of the fact that *apply is not necessarily "more efficient" than a well constructed for loop). So I'd like to pose the question

Force pandas to interpret (1,2) in column as string and not as range?

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问题 I have this weird behaviour in a pandas Dataframe. I am using .apply(single_seats_comma) on a column with the following example content: (1,2) . However, it seems to return it as range(1,3) instead of a string (1,2) . Other rows have more than 2 entries as well, e.g. (30,31,32) . I have a function which splits on , and converts each value in brackets into a new row however with (x,x) it breaks. def single_seats_comma(row): strlist = str(row).split(',') strlist = filter(None, strlist) intlist

calculating the frequency of occurrences in every column

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问题 I'm trying to count the frequency of a specific value in every column. Basically, I am looking at how different bacterial isolates (represented by each row) respond to treatment with different antibiotics (represented each column). "1" means the isolate is resistant to the antibiotic, while "0" means the isolate is susceptible to the antibiotic. antibiotic1 <- c(1, 1, 0, 1, 0, 1, NA, 0, 1) antibiotic2 <- c(0, 0, NA, 0, 1, 1, 0, 0, 0) antibiotic3 <- c(0, 1, 1, 0, 0, NA, 1, 0, 0) ab <- data

calculating the frequency of occurrences in every column

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JavaScript function call/apply with string

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问题 I just noticed that, when I want to pass string as "this" , the type cannot be obtained correctly inside a JavaScript function. Here is an example: var str = 'string value'; if (typeof (str) == 'string') { alert('string outside'); } var fn = function(s) { if (typeof (str) == 'string') { alert('string param'); } if (typeof (this) == 'string') { alert('string this'); } else { alert(typeof(this)); } }; fn.call(str, str); I see 3 messages: "string outside" , "string param" , and "object" . My

js函数中的apply()、call()、bind()方法

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1. 什么是类数组ArrayLike 拥有length属性，其它属性（索引）为非负整数(对象中的索引会被当做字符串来处理，这里你可以当做是个非负整数串来理解) 不具有数组所具有的方法 //类数组示例 var a = {'1':'gg','2':'love','4':'meimei',length:5}; Array.prototype.join.call(a,'+');//'+gg+love++meimei' //非类数组示例 var c = {'1':2}; //没有length属性就不是类数组 javascript中常见的类数组有 arguments 对象和DOM方法的返回结果。比如 document.getElementsByTagName() 。 2. 判断一个对象是否属于类数组 function isArrayLike(o) { if (o && // o is not null, undefined, etc. typeof o === 'object' && // o is an object isFinite(o.length) && // o.length is a finite number o.length >= 0 && // o.length is non-negative o.length===Math.floor(o.length) && // o

Apply function that downloads zip files and deletes specific files

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问题 I am trying to write a function and call it using apply to each row in my dataset. The dataset contains URLs of zip files, which will be downloaded, unzipped, and after unzipping TXT and zip files will be deleted from the working directory. head(data) data URL 1 /files/market_valuation/ru/2017/val170502170509.zip http://www.kase.kz/files/market_valuation/ru/2017/val170502170509.zip 2 /files/market_valuation/ru/2017/val170424170430.zip http://www.kase.kz/files/market_valuation/ru/2017

non-numeric argument to binary operator error ONLY within apply

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问题 I am having the "non-numeric argument to binary operator" error. I know that both of the arguments are numeric. Strangely, the calculation works if I just execute that line alone, but when I try and wrap it within 'apply' it gives me the "non-numeric argument to binary operator" error. Here is the error: Error in IPmz * mz_winppm : non-numeric argument to binary operator They are numeric: > mode(IPmz) [1] "numeric" > mode(mz_winppm) [1] "numeric" Here is my code: FindNovelIPFeats<-function(mz

Why there is an extra index when using apply in Pandas

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问题 When I use apply to a user defined function in Pandas, it looks like python is creating an additional array. How could I get rid of it? Here is my code: def fnc(group): x = group.C.values out = x[np.where(x < 0)] return pd.DataFrame(out) data = pd.DataFrame({'A':np.random.randint(1, 3, 10), 'B':3, 'C':np.random.normal(0, 1, 10)}) data.groupby(by=['A', 'B']).apply(fnc).reset_index() There is this weird Level_2 index created. Is there a way to avoid creating it when running my function? A B