pandas 用熊猫计算矩阵的逆
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Calculating the inverse of a matrix with pandas
提问by Polo.B
I have a large pandas DataFrame - which is a square matrix with header and index, and I am trying to use pandas' capabilities to calculate the inverse of that matrix, without going directly through numpy.
我有一个大 Pandas DataFrame——它是一个带有标题和索引的方阵，我正在尝试使用 Pandas 的功能来计算该矩阵的逆，而不是直接通过 numpy。
I want to stay within a pandas framework to keep the headings of my dataframe. I could use the pd.as_matrix function, but that turns it into an ndarray and I loose all the information provided by the headings.
我想留在Pandas框架内以保留数据框的标题。我可以使用 pd.as_matrix 函数，但这会将它变成一个 ndarray 并且我丢失了标题提供的所有信息。
Any suggestions?
有什么建议？
回答by piRSquared
consider the dataframe df
考虑数据框 df
np.random.seed([3,1415])
df = pd.DataFrame(np.random.rand(3, 3), list('abc'), list('xyz'))
df
calculate the inverse (with numpy, let's not be crazy)
计算逆（用 numpy，让我们不要发疯）
df_inv = pd.DataFrame(np.linalg.pinv(df.values), df.columns, df.index)
df_inv
notice I use pinvfor the pseudo inverse
注意我pinv用于伪逆
then check
然后检查
df_inv.dot(df)
