在将数据帧拆分为两个组时，是否有多个变量影响因素？Pandas

Question

我正在研究各州的新冠病毒-19死亡病例数量，并研究高州人口是否会导致感染新冠病毒-19的人死亡的可能性更高

目前正在将我的数据框分为两组，但按照我的设置方式，这一组将取决于两个因素，而不仅仅是一个-例如：高人口\高死亡率（这意味着州人口大于中值，死亡率大于中值），另一组将是高人口\低死亡率（州人口大于中位数，死亡率小于中位数）。当前代码如下，但我一直收到一个无效语法错误。所以我想知道是否不能基于两个变量将数据帧分成两组

将死亡病例数据集分为两组

highpop_highdeath = df.iloc[(df'StatePopulation' > 4342705.0), (df'deaths_to_cases' > 0.012143070253953211).values]
highpop_highdeath.name = 'States with a high population and high death rate'
highpop_lowdeath = df.iloc[(df'StatePopulation'> 4342705.0), (df'deaths_to_cases' <= 0.012143070253953211).values]
highpop_lowdeath.name = 'States with a high population and low death rate'

Answer 1

要在过滤器上组合多个因子，需要对每个条件使用布尔运算符&：

highpop_highdeath = df.loc[(df'StatePopulation' > 4342705.0) & (df'deaths_to_cases' > 0.012143070253953211), :]

Answer 2

是的，你可以有两个变量。顺便问一下，你能分享一下错误信息吗？ 此外，请尝试以下方法：

highpop_highdeath = df.loc[(df['StatePopulation'] > 4342705.0) &  (df['deaths_to_cases'] > 0.012143070253953211)]
highpop_highdeath.name = 'States with a high population and high death rate'
highpop_lowdeath = df.loc[(df['StatePopulation']> 4342705.0) & (df['deaths_to_cases'] <= 0.012143070253953211)]
highpop_lowdeath.name = 'States with a high population and low death rate'

Answer 3

您希望合并这两个布尔向量。通过这种方式，对于数据帧中的每个位置，pandas将计算这两个语句，并且只有当这两个语句都为真时，才保留数据

highpop_highdeath = df.loc[(df'StatePopulation' > 4342705.0) & (df'deaths_to_cases' > 0.012143070253953211)]

ighpop_lowdeath = df.loc[(df'StatePopulation'> 4342705.0) & (df'deaths_to_cases' <= 0.012143070253953211)]

更简洁的是：

highpop_highdeath_names = df.loc[(df'StatePopulation' > 4342705.0) & (df'deaths_to_cases' > 0.012143070253953211),'name']