mars.dataframe.DataFrame.corr¶
- DataFrame.corr(method='pearson', min_periods=1)¶
Compute pairwise correlation of columns, excluding NA/null values.
- 参数
method ({'pearson', 'kendall', 'spearman'} or callable) –
Method of correlation:
pearson : standard correlation coefficient
kendall : Kendall Tau correlation coefficient
spearman : Spearman rank correlation
- callable: callable with input two 1d ndarrays
and returning a float. Note that the returned matrix from corr will have 1 along the diagonals and will be symmetric regardless of the callable’s behavior.
注解
kendall, spearman and callables not supported on multiple chunks yet.
min_periods (int, optional) – Minimum number of observations required per pair of columns to have a valid result. Currently only available for Pearson and Spearman correlation.
- 返回
Correlation matrix.
- 返回类型
参见
DataFrame.corrwith
Compute pairwise correlation with another DataFrame or Series.
Series.corr
Compute the correlation between two Series.
实际案例
>>> import mars.dataframe as md >>> df = md.DataFrame([(.2, .3), (.0, .6), (.6, .0), (.2, .1)], ... columns=['dogs', 'cats']) >>> df.corr(method='pearson').execute() dogs cats dogs 1.000000 -0.851064 cats -0.851064 1.000000