correlation

问题 It seems that corrcoef from numpy throw a RuntimeWarning when a constant list passed to the corrcoef() function, for example the below code throw a warning : import numpy as np X = [1.0, 2.0, 3.0, 4.0] Y = [2, 2, 2, 2] print(np.corrcoef(X, Y)[0, 1]) Warning : /usr/local/lib/python3.6/site-packages/numpy/lib/function_base.py:3003: RuntimeWarning: invalid value encountered in true_divide c /= stddev[:, None] Can anyone explain why it's throw this error when one of the lists is constant, and how

问题 It seems that corrcoef from numpy throw a RuntimeWarning when a constant list passed to the corrcoef() function, for example the below code throw a warning : import numpy as np X = [1.0, 2.0, 3.0, 4.0] Y = [2, 2, 2, 2] print(np.corrcoef(X, Y)[0, 1]) Warning : /usr/local/lib/python3.6/site-packages/numpy/lib/function_base.py:3003: RuntimeWarning: invalid value encountered in true_divide c /= stddev[:, None] Can anyone explain why it's throw this error when one of the lists is constant, and how

问题 How do I correlate two pandas dataframes, find a single r value for all values? I don't want to correlate columns or rows, but all scalar values. One dataframe is the x axis, and the other dataframe is the y axis. I downloaded identically structured csv files here: https://www.gapminder.org/data/ The tables have years for columns, countries for rows, with numerical values for the indicator that each table reports. For instance, I want to see how the Political Participation Indicator

问题 How do I calculate correlations between one column and all other columns in a data frame in R without using column names? I tried to use ddply and it works if I use just two column names i.e. library(plyr) ddply(iris, ~Species, summarize, cormat=cor(Sepal.Length,Petal.Width)) But how to get correlations of column 1 with all other columns, broken down by Species, without using the column names? 回答1: Maybe like this? It produces a correlation matrix for each species. by(iris[,1:4], iris$Species

问题 How do I calculate correlations between one column and all other columns in a data frame in R without using column names? I tried to use ddply and it works if I use just two column names i.e. library(plyr) ddply(iris, ~Species, summarize, cormat=cor(Sepal.Length,Petal.Width)) But how to get correlations of column 1 with all other columns, broken down by Species, without using the column names? 回答1: Maybe like this? It produces a correlation matrix for each species. by(iris[,1:4], iris$Species

来源： https://stackoverflow.com/questions/53771844/reformatting-results-of-cor-test-to-dataframe

来源： https://stackoverflow.com/questions/53771844/reformatting-results-of-cor-test-to-dataframe

来源： https://stackoverflow.com/questions/14266333/extract-confidence-interval-values-from-acf-correlogram

来源： https://stackoverflow.com/questions/14266333/extract-confidence-interval-values-from-acf-correlogram

来源： https://stackoverflow.com/questions/18275639/remove-highly-correlated-variables