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

DataFrame

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

mars.dataframe.DataFrame.any

mars.dataframe.DataFrame.corrwith