根据 DataFrame2 中的值在 DataFrame1 中创建列

Question

我有两个数据框，想在 DataFrame 1 中基于 DataFrame 2 值创建一个新列。

但我不想按说加入两个数据帧并制作一个大的 dataframe，而是将第二个 Dataframe 用作查找。

#Main Dataframe:
df1 = pd.DataFrame({'Size':["Big", "Medium", "Small"], 'Sold_Quantity':[10, 6, 40]})

#Lookup Dataframe
df2 = pd.DataFrame({'Size':["Big", "Medium", "Small"], 'Sold_Quantiy_Score_Mean':[10, 20, 30]})

#Create column in Dataframe 1 based on lookup dataframe values:
df1['New_Column'] = when df1['Size'] = df2['Size'] and df1['Sold_Quantity'] < df2['Sold_Quantiy_Score_Mean'] then 'Below Average Sales' else 'Above Average Sales!' end

Answer 1

一种方法是使用np.where ：

import pandas as pd
import numpy as np

df1 = pd.DataFrame({'Size': ["Big", "Medium", "Small"], 'Sold_Quantity': [10, 6, 40]})
df2 = pd.DataFrame({'Size': ["Big", "Medium", "Small"], 'Sold_Quantiy_Score_Mean': [10, 20, 30]})

condition = (df1['Size'] == df2['Size']) & (df1['Sold_Quantity'] < df2['Sold_Quantiy_Score_Mean'])

df1['New_Column'] = np.where(condition, 'Below Average Sales', 'Above Average Sales!')

print(df1)

Output

     Size  Sold_Quantity            New_Column
0     Big             10  Above Average Sales!
1  Medium              6   Below Average Sales
2   Small             40  Above Average Sales!

Answer 2

鉴于df2有点像基于大小的查找，如果您的大小列是它的索引，那将是有意义的：

import pandas as pd
import numpy as np

df1 = pd.DataFrame({'Size': ["Big", "Medium", "Small"], 'Sold_Quantity': [10, 6, 40]})
df2 = pd.DataFrame({'Size': ["Big", "Medium", "Small"], 'Sold_Quantiy_Score_Mean': [10, 20, 30]})

lookup = df2.set_index("Size")

然后，您可以将df1中的尺寸 map 计算为其平均值，并将每个尺寸与售出数量进行比较：

is_below_mean = df1["Sold_Quantity"] < df1["Size"].map(lookup["Sold_Quantiy_Score_Mean"])

最后 map 使用np.where将 boolean 值赋给相应的字符串

df1["New_Column"] = np.where(is_below_mean, 'Below Average Sales', 'Above Average Sales!')

df1:

     Size  Sold_Quantity            New_Column
0     Big             10  Above Average Sales!
1  Medium              6   Below Average Sales
2   Small             40  Above Average Sales!