如何根据条件计算所有数据框列值并将列转置为 Python 中的行
How to count all data frame column values based on condition and transpose the columns into rows in Python
请在 Python 数据框中找到示例数据,如下所示。我有大约 30 列。
Column1 Column2 Column3
Male Male Female
Male Female Female
Female Male Female
Female Male Male
我想要以下格式的输出
Male Female
Column1 2 2
Column2 3 1
Column3 1 3
如果有人能帮助我在 Python 中实现这一目标,我将不胜感激。
谢谢,
斯里
尝试:
df.melt().value_counts().unstack()
value Female Male
variable
Column1 2 2
Column2 1 3
Column3 3 1
去掉轴名称
df.melt().value_counts().rename_axis([None, None]).unstack()
Female Male
Column1 2 2
Column2 1 3
Column3 3 1
value_counts
在 apply
和 transpose
df.apply(lambda c : c.value_counts()).transpose()
输出
Female Male
Column1 2 2
Column2 1 3
Column3 3 1
请在 Python 数据框中找到示例数据,如下所示。我有大约 30 列。
Column1 Column2 Column3
Male Male Female
Male Female Female
Female Male Female
Female Male Male
我想要以下格式的输出
Male Female
Column1 2 2
Column2 3 1
Column3 1 3
如果有人能帮助我在 Python 中实现这一目标,我将不胜感激。
谢谢, 斯里
尝试:
df.melt().value_counts().unstack()
value Female Male
variable
Column1 2 2
Column2 1 3
Column3 3 1
去掉轴名称
df.melt().value_counts().rename_axis([None, None]).unstack()
Female Male
Column1 2 2
Column2 1 3
Column3 3 1
value_counts
在 apply
和 transpose
df.apply(lambda c : c.value_counts()).transpose()
输出
Female Male
Column1 2 2
Column2 1 3
Column3 3 1