where

问题 I'm trying to create a new column in a dataframe that labels animals that are domesticated with a 1. I'm using a for loop, but for some reason, the loop only picks up the last item in the pets list. dog , cat , and gerbil should all be assigned a 1 under the domesticated column. Anyone have a fix for this or a better approach? df = pd.DataFrame( {'creature': ['dog', 'cat', 'gerbil', 'mouse', 'donkey'] }) pets = ['dog', 'cat', 'gerbil'] for pet in pets: df['domesticated'] = np.where(df[

问题 I have a database which holds different locations, each of which has its own longitude and latitude variable. I want to be able to use a distance function I made that returns the distance between two longitudes and latitudes in my WHERE statement. So I am looking for the distance between two points and it pass the WHERE statement if it is less than the radius I am searching. distance function: function distance($lat1, $lon1, $lat2, $lon2) { $theta = $lon1 - $lon2; $dist = sin(deg2rad($lat1))

问题 I am trying to get return the correct "Where" extension method using reflection, in order to build a custom Expression. I have tried several ways but the closest I get, throws an exception: "An unhandled exception of type 'System.Reflection.AmbiguousMatchException' occurred in mscorlib.dll" I know this is because there are two Where methods defined in the Enumrable class - but how can I return the Where method which using only just a predicate of Func<T, bool>. What I have at the moment is:

问题 How can I "concat" a specific column from many Python Pandas dataframes, WHERE another column in each of the many dataframes meets a certain condition (colloquially termed condition "X" here). In SQL this would be simple using JOIN clause with WHERE df2.Col2 = "X" and df3.Col2 = "X" and df4.col2 = "X"... etc (which can be run dynamically). In my case, I want to create a big dataframe with all the "Col1"s from each of the many dataframes, but only include the Col1 row values WHERE the

问题 I am having some trouble filtering a pandas dataframe on a column (let's call it column_1) whose data type is a list. Specifically, I want to return only rows such that column_1 and the intersection of another predetermined list are not empty. However, when I try to put the logic inside the arguments of the .where, function, I always get errors. Below are my attempts, with the errors returned. Attemping to test whether or not a single element is inside the list: table[element in table['column

问题 I tried to find entries in an Array containing a substring with np.where and an in condition: import numpy as np foo = "aa" bar = np.array(["aaa", "aab", "aca"]) np.where(foo in bar) this only returns an empty Array. Why is that so? And is there a good alternative solution? 回答1: We can use np.core.defchararray.find to find the position of foo string in each element of bar , which would return -1 if not found. Thus, it could be used to detect whether foo is present in each element or not by

来源： https://stackoverflow.com/questions/9503510/how-to-invert-numpy-where-np-where-function

来源： https://stackoverflow.com/questions/9503510/how-to-invert-numpy-where-np-where-function

来源： https://stackoverflow.com/questions/47513408/pandas-dataframe-check-if-column-value-is-in-column-list

来源： https://stackoverflow.com/questions/47513408/pandas-dataframe-check-if-column-value-is-in-column-list