将熊猫系列更改为 int

Question

我有以下代码：x1 = df[(df['event_name'] == 'Listen') & (df['cell'] == 'CONTROL')].yes_user_county1 = df[(df['event_name'] == 'Listen') & (df['cell'] != 'CONTROL')].yes_user_countx_n = df[(df['event_name'] == 'Listen') & (df['cell'] == 'CONTROL')].total_user_county_n = df[(df['event_name'] == 'Listen') & (df['cell'] != 'CONTROL')].total_user_countzscore, pval = proportions_ztest([x1, y1], [x_n, y_n])但是，ztest 函数不起作用。原因看起来是x1、y1、x_n和y_n是熊猫系列。我尝试使用 x1.astype(int) 但它似乎没有解决问题。有人可以建议什么是最好的解决方案吗？

Answer 1

你想要.tolist()：

x1 = df[(df['event_name'] == 'Listen') & (df['cell'] == 'CONTROL')].yes_user_count.tolist()

y1 = df[(df['event_name'] == 'Listen') & (df['cell'] != 'CONTROL')].yes_user_count.tolist()

x_n = df[(df['event_name'] == 'Listen') & (df['cell'] == 'CONTROL')].total_user_count.tolist()

y_n = df[(df['event_name'] == 'Listen') & (df['cell'] != 'CONTROL')].total_user_count.tolist()

zscore, pval = proportions_ztest([x1, y1], [x_n, y_n])

但我也建议使用loc列名作为第二个值：

x1 = df.loc[(df['event_name'] == 'Listen') & (df['cell'] == 'CONTROL'), 'yes_user_count'].tolist()

y1 = df.loc[(df['event_name'] == 'Listen') & (df['cell'] != 'CONTROL'), 'yes_user_count'].tolist()

x_n = df.loc[(df['event_name'] == 'Listen') & (df['cell'] == 'CONTROL'), 'total_user_count'].tolist()

y_n = df.loc[(df['event_name'] == 'Listen') & (df['cell'] != 'CONTROL'), 'total_user_count'].tolist()

zscore, pval = proportions_ztest([x1, y1], [x_n, y_n])

或者甚至更好：

mask1 = (df['event_name'] == 'Listen') & (df['cell'] == 'CONTROL')

mask2 = (df['event_name'] == 'Listen') & (df['cell'] != 'CONTROL')

x1 = df.loc[mask1, 'yes_user_count'].tolist()

y1 = df.loc[mask2, 'yes_user_count'].tolist()

x_n = df.loc[mask1, 'total_user_count'].tolist()

y_n = df.loc[mask2, 'total_user_count'].tolist()

zscore, pval = proportions_ztest([x1, y1], [x_n, y_n])