Python 大熊猫的平均计算不包括零
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mean calculation in pandas excluding zeros
提问by Gabriel
Is there a direct way to calculate the mean of a dataframe column in pandas but not taking into account data that has zero as a value? Like a parameter inside the .mean() function? Was currently doing it like this:
有没有一种直接的方法来计算 Pandas 中数据框列的平均值，但不考虑值为零的数据？就像 .mean() 函数中的参数一样？目前是这样做的：
x = df[df[A]!=0]
x.mean()
采纳答案by tibi3000
It also depends on the meaning of 0 in your data.
它还取决于数据中 0 的含义。
- If these are indeed '0' values, then your approach is good
If '0' is a placeholder for a value that was not measured (i.e. 'NaN'), then it might make more sense to replace all '0' occurrences with 'NaN' first. Calculation of the mean then by default exclude NaN values.
df = pd.DataFrame([1, 0, 2, 3, 0], columns=['a']) df = df.replace(0, np.NaN) df.mean()
- 如果这些确实是“0”值，那么您的方法很好
如果“0”是未测量的值（即“NaN”）的占位符，那么首先用“NaN”替换所有出现的“0”可能更有意义。计算平均值然后默认排除 NaN 值。
df = pd.DataFrame([1, 0, 2, 3, 0], columns=['a']) df = df.replace(0, np.NaN) df.mean()
