lookup

问题 I have two DataFrames . . . df1 is a table I need to pull values from using index, column pairs retrieved from multiple columns in df2. I see there is a function get_value which works perfectly when given an index and column value, but when trying to vectorize this function to create a new column I am failing... df1 = pd.DataFrame(np.arange(20).reshape((4, 5))) df1.columns = list(\'abcde\') df1.index = [\'cat\', \'dog\', \'fish\', \'bird\'] a b c d e cat 0 1 2 3 4 dog 5 6 7 8 9 fish 10 11 12

问题 Does anyone know of a simple way to retrieve the country for a given IP Address? Preferably in ISO_3166-1 format? 回答1: A lot of people (including my company) seem to use MaxMind GeoIP. They have a free version GeoLite which is not as accurate as the paid version, but if you're just after something simple, it may be good enough. 回答2: There are two approaches: using an Internet service and using some kind of local list (perhaps wrapped in a library). What you want will depend on what you are

问题 I would like to lookup an enum from its string value (or possibly any other value). I\'ve tried the following code but it doesn\'t allow static in initialisers. Is there a simple way? public enum Verbosity { BRIEF, NORMAL, FULL; private static Map<String, Verbosity> stringMap = new HashMap<String, Verbosity>(); private Verbosity() { stringMap.put(this.toString(), this); } public static Verbosity getVerbosity(String key) { return stringMap.get(key); } }; 回答1: Use the valueOf method which is

问题 Recently began branching out from my safe place (R) into Python and and am a bit confused by the cell localization/selection in Pandas . I\'ve read the documentation but I\'m struggling to understand the practical implications of the various localization/selection options. Is there a reason why I should ever use .loc or .iloc over the most general option .ix ? I understand that .loc , iloc , at , and iat may provide some guaranteed correctness that .ix can\'t offer, but I\'ve also read where

问题 I\'d like to do the following: Lookup a Vec for a certain key, and store it for later use. If it doesn\'t exist, create an empty Vec for the key, but still keep it in the variable. How to do this efficiently? Naturally I thought I could use match : use std::collections::HashMap; // This code doesn\'t compile. let mut map = HashMap::new(); let key = \"foo\"; let values: &Vec<isize> = match map.get(key) { Some(v) => v, None => { let default: Vec<isize> = Vec::new(); map.insert(key, default);

问题 I have a dataset about 105000 rows and 30 columns. I have a categorical variable that I would like to assign it to a number. In Excel, I would probably do something with VLOOKUP and fill. How would I go about doing the same thing in R ? Essentially, what I have is a HouseType variable, and I need to calculate the HouseTypeNo . Here are some sample data: HouseType HouseTypeNo Semi 1 Single 2 Row 3 Single 2 Apartment 4 Apartment 4 Row 3 回答1: If I understand your question correctly, here are

问题 I am having some trouble replacing values in a dataframe. I would like to replace values based on a separate table. Below is an example of what I am trying to do. I have a table where every row is a customer and every column is an animal they purchased. Lets call this dataframe table . > table # P1 P2 P3 # 1 cat lizard parrot # 2 lizard parrot cat # 3 parrot cat lizard I also have a table that I will reference called lookUp . > lookUp # pet class # 1 cat mammal # 2 lizard reptile # 3 parrot

问题 I have a function with the same name, but with different signature in a base and derived classes. When I am trying to use the base class\'s function in another class that inherits from the derived, I receive an error. See the following code: class A { public: void foo(string s){}; }; class B : public A { public: int foo(int i){}; }; class C : public B { public: void bar() { string s; foo(s); } }; I receive the following error from the gcc compiler: In member function `void C::bar()\': no

问题 Is it possible to add a key to a Python dictionary after it has been created? It doesn\'t seem to have an .add() method. 回答1: d = {'key':'value'} print(d) # {'key': 'value'} d['mynewkey'] = 'mynewvalue' print(d) # {'mynewkey': 'mynewvalue', 'key': 'value'} 回答2: To add multiple keys simultaneously: >>> x = {1:2} >>> print x {1: 2} >>> d = {3:4, 5:6, 7:8} >>> x.update(d) >>> print x {1: 2, 3: 4, 5: 6, 7: 8} For adding a single key, the accepted answer has less computational overhead. 回答3: I