如何迭代字符串的DataFrame并在结果上应用条件

Question

我正在尝试使用 if 条件迭代数据帧，以在字符串等于数据帧中第 i 个位置的字符串时返回一个值。

运行示例代码时出现以下错误

(`ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().`):

 df = {'step_ID':[1,1,2,2,3,3,4,4], 'step_name':['CC_Dchg', 'CC_Dchg', 'Rest', 'Rest', 'CC_Chg', 
    'CC_Chg', 'Rest', 'Rest']}
    df = pd.DataFrame(df)

    chg_step = []
    a = []

    for i in df:
        if df['step_name'] == 'CC_Chg':
            a = SiO_1['step_ID']
            chg_step = chg_step + a
        else:
            continue

检查df['step_name'] == 'CC_Chg' 是否为真的正确语法是什么？

Answer 1

如果我理解正确，您需要step_name 等于给定值的行的step_ID。在 pandas 中，您不必编写自己的循环（或仅在极端情况下）。相反，这里有一个替代方案：

# step by step

# do the comparison step_name == X for each row.
# The result is a boolean pandas Series
mask = df['step_name'] == 'CC_Chg' 
# The boolean pandas series can be used to select only some rows.
# Then, we can retrieve the step_ID column for those rows only.
# The result is again a pandas Series
chg_step_series = df[mask].step_ID # this is a series
# A pandas series can be converted to a numpy array using values,
# and then a list by calling tolist()
chg_step_series.values.tolist() # this is a list: [3,3]

或者，在一行中：

chg_step = df[df.step_name == 'CC_Chg'].step_ID.values.tolist()