根據 DataFrame2 中的值在 DataFrame1 中創建列

Question

我有兩個數據框，想在 DataFrame 1 中基於 DataFrame 2 值創建一個新列。

但我不想按說加入兩個數據幀並制作一個大的 dataframe，而是將第二個 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

一種方法是使用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

鑒於df2有點像基於大小的查找，如果您的大小列是它的索引，那將是有意義的：

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，您可以將df1中的尺寸 map 計算為其平均值，並將每個尺寸與售出數量進行比較：

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

最后 map 使用np.where將 boolean 值賦給相應的字符串

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!