熊猫：遍历一行并将值添加到空列

Question

您好，我想遍历CPB％行并将计算结果添加到名为“ Proba”的相关列中。我的数据框如下所示：

到目前为止我尝试过的内容如下：

bins = np.linspace(0, 1, num=100)
dCPB = df['CPB%']
df['binnedB'] = pd.cut(dCPB, bins)
dfnew = pd.DataFrame(pd.cut(df['CPB%'], bins=bins).value_counts()).sort_index(ascending = True)
dfnew['binned'] = dfnew.index

total = dfnew['CPB%'].sum()
idx = total

for index,row in dfnew.iterrows():
  idx = idx - row['CPB%']
  row['Proba'] = float(idx) / float(total)

但是我的迭代不会更新我的空列Proba，为什么？谢谢！

Answer 1

我认为问题是，您正在将结果分配回row，而该proba = [] for index, row in dfnew.iterrows(): idx = idx - row['CPB%'] proba.append(float(idx) / float(total)) dfnew['Proba'] = proba 不会存储在任何地方。相反，您可以这样做：

.apply

但是，这不是最好的方法，可以将axis=1与Sub test() Dim vDB, vR() Dim i As Long, j As Integer, n As Long Dim r As Long vDB = Range("a1").CurrentRegion r = UBound(vDB, 1) For i = 1 To r For j = 1 To 6 n = n + 1 ReDim Preserve vR(1 To 2, 1 To n) vR(1, n) = vDB(i, j) vR(2, n) = vDB(i, j + 6) Next j Next i Sheets.Add Range("a1").Resize(n, 2) = WorksheetFunction.Transpose(vR) End Sub 一起使用来对数据帧进行逐行计算。

Answer 2

您可以使用pd.Series.cumsum来进行迭代推论：

total = dfnew['CPB%'].sum()
dfnew['Proba'] = 1 - df['CPB%'].cumsum() / total

对于熊猫，您应该着眼于向量化算法，该算法通常涉及列式操作，而不是行式for循环。这是一个完整的演示：

df = pd.DataFrame({'A': list(range(1, 7))})

def jpp(df):
    total = df['A'].sum()
    df['Proba'] = 1 - df['A'].cumsum() / total
    return df

def yolo(df):
    total = df['A'].sum()
    idx = total

    proba = []
    for index, row in df.iterrows():
        idx = idx - row['A']
        proba.append(float(idx) / float(total))

    df['Proba'] = proba
    return df

# check results are the same
assert df.pipe(jpp).equals(df.pipe(yolo))

%timeit df.pipe(jpp)   # 691 µs
%timeit df.pipe(yolo)  # 840 µs