根据 if/elif/and 函数在 pandas 数据框中创建新列

Question

我已经搜索了我的确切问题，但没有找到。这两个线程 Creating a new column based on if-elif-else condition 和尽管我的代码无法执行，但它指导了我的代码。

问题：我有一个数据框，我在下面复制了示例。区域属性只有两个值 - a 或 b（或可能有更多），年份相同，尽管区域 a 可能有两个年份等。我想做的是创建一个新列 "dollars"，然后查找区域的值，如果它是区域 "a" 并且年份是例如 2006，则在该行中获取销售额，然后乘以该年份的比率并在新列中追加值- 美元。我是初学者，下面是我到目前为止所拥有的 - 通过函数 - 显然执行 .apply 函数 returns a ValueError: ('The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().', 'occurred at index 0').我对更有效的实现特别感兴趣，因为数据帧相当大并且希望优化计算效率。

import pandas as np

rate_2006, rate_2007 = 100, 200


c = {
'region': ["a", "a", "a", "a", "a", "b", "b", "b", "b", "a", "b"],
'year': [2006, 2007, 2007, 2006, 2006, 2006, 2007, 2007, 2007, 2006, 2007],
'sales': [500, 100, 2990, 15, 5000, 2000, 150, 300, 250, 1005, 600]
}

df1 = pd.DataFrame(c)
df1

def new_col(row): 
    if df1["region"] == "a" and df1["year"] == 2006:
        nc = row["sales"] * rate_2006
    elif df1["region"] == "a" and df1["year"] == 2007:
        nc = row["sales"] * rate_2007
    elif df1["region"] == "b" and df1["year"] == 2006:
        nc = row["sales"] * rate_2006
    else:
        nc = row["sales"] * rate_2007
    return nc

df1["Dollars"] = df1.apply(new_col, axis=1)
df1

Answer 1

问题可能与您的使用方式有关。不知道对你有没有帮助。但我已经根据我的知识重新编写了有效的代码。

import pandas as pd

rate_2006, rate_2007 = 100, 200


c = {
'region': ["a", "a", "a", "a", "a", "b", "b", "b", "b", "a", "b"],
'year': [2006, 2007, 2007, 2006, 2006, 2006, 2007, 2007, 2007, 2006, 2007],
'sales': [500, 100, 2990, 15, 5000, 2000, 150, 300, 250, 1005, 600]
}

df1 = pd.DataFrame(c)
print(df1)

def new_col(value): 
    if df1.loc[value,"region"] == "a" and df1.loc[value,"year"] == 2006:
        df1.loc[value,"Dollars"] = df1.loc[value,"sales"] * rate_2006
    elif df1.loc[value,"region"] == "a" and df1.loc[value,"year"] == 2007:
        df1.loc[value,"Dollars"] = df1.loc[value,"sales"] * rate_2007
    elif df1.loc[value,"region"] == "b" and df1.loc[value,"year"] == 2006:
        df1.loc[value,"Dollars"] = df1.loc[value,"sales"] * rate_2006
    else:
        df1.loc[value,"Dollars"] = df1.loc[value,"sales"] * rate_2007

for value in range(len(df1)):
    new_col(value)

根据 if/elif/and 函数在 pandas 数据框中创建新列

Create new column in pandas dataframe based on if/elif/and functions

python-3.x

sklearn-pandas