在数据框中查找通讯者进行计算

Question

如下两个数据框，我想计算相关系数。当两列都用实际值完成时，它工作正常。但如果不是，则在计算相关系数时取零作为值。例如，Addison 和 Caden 的权重为 0。Jack 和 Noah 没有权重。我想排除它们进行计算。（在尝试中，似乎只考虑相同的长度，即自动排除 Jack 和 Noah – 是吗？）如何只包括非零值的人进行计算？谢谢你。import pandas as pdWeight = {'Name': ["Abigail","Addison","Aiden","Amelia","Aria","Ava","Caden","Charlotte","Chloe","Elijah"], 'Weight': [10, 0, 12, 20, 25, 10, 0, 18, 16, 13]}df_wt = pd.DataFrame(Weight)Score = {'Name': ["Abigail","Addison","Aiden","Amelia","Aria","Ava","Caden","Charlotte","Chloe","Elijah", "Jack", "Noah"], 'Score': [360, 476, 345, 601, 604, 313, 539, 531, 507, 473, 450, 470]}df_sc = pd.DataFrame(Score)print df_wt.Weight.corr(df_sc.Score)

Answer 1

屏蔽和取非零值和公共索引：

df_wt.set_index('Name', inplace=True)

df_sc.set_index('Name', inplace=True)

mask = df_wt['Weight'].ne(0)

common_index = df_wt.loc[mask, :].index

df_wt.loc[common_index, 'Weight'].corr(df_sc.loc[common_index, 'Score'])

0.923425144491911

如果两个数据帧都包含零，则：

mask1 = df_wt['Weight'].ne(0)

mask2 = df_sc['Score'].ne(0)

common_index = df_wt.loc[mask1, :].index.intersection(df_sc.loc[mask2, :].index)

df_wt.loc[common_index, 'Weight'].corr(df_sc.loc[common_index, 'Score'])

Answer 2

屏蔽和取非零值和公共索引：

df_wt.set_index('Name', inplace=True)

df_sc.set_index('Name', inplace=True)

mask = df_wt['Weight'].ne(0)

common_index = df_wt.loc[mask, :].index

df_wt.loc[common_index, 'Weight'].corr(df_sc.loc[common_index, 'Score'])

0.923425144491911

如果两个数据帧都包含零，则：

mask1 = df_wt['Weight'].ne(0)

mask2 = df_sc['Score'].ne(0)

common_index = df_wt.loc[mask1, :].index.intersection(df_sc.loc[mask2, :].index)

df_wt.loc[common_index, 'Weight'].corr(df_sc.loc[common_index, 'Score'])