Pandas：如果A列中的行包含“x”，则在B列中的行中写入“y”

Question

对于pandas，我正在寻找一种方法，根据a列中相应行的子字符串，将条件值写入B列中的每一行

因此，如果A中的单元格包含"BULL"，则将"Long"写入B。或者如果A中的单元格包含"BEAR"，则将"Short"写入B。

期望输出：

A                  B
"BULL APPLE X5"    "Long"
"BEAR APPLE X5"    "Short"
"BULL APPLE X5"    "Long"

B最初为空：df = pd.DataFrame([['BULL APPLE X5',''],['BEAR APPLE X5',''],['BULL APPLE X5','']],columns=['A','B'])

Answer 1

当您错误地创建数据帧时，您的代码将出错，只需创建一个列A，然后基于A添加B：

import pandas as pd
df = pd.DataFrame(["BULL","BEAR","BULL"], columns=['A'])
df["B"] = ["Long" if ele  == "BULL" else "Short" for ele in df["A"]]

print(df)

    A      B
0  BULL   Long
1  BEAR  Short
2  BULL   Long

或者在创建数据帧之前对数据进行逻辑处理：

import pandas as pd
data = ["BULL","BEAR","BULL"]
data2 = ["Long" if ele  == "BULL" else "Short" for ele in data]
df = pd.DataFrame(list(zip(data, data2)), columns=['A','B'])

print(df)
      A      B
 0  BULL   Long
 1  BEAR  Short
 2  BULL   Long

供编辑：

df = pd.DataFrame([['BULL APPLE X5',''],['BEAR APPLE X5',''],['BULL APPLE X5','']], columns=['A','B'])

df["B"] = df["A"].map(lambda x: "Long" if "BULL" in x else "Short" if "BEAR" in x else "")

print(df)

            A      B
0  BULL APPLE X5   Long
1  BEAR APPLE X5  Short
2  BULL APPLE X5   Long

或者只需在以下内容之后添加列：

df = pd.DataFrame(['BULL APPLE X5','BEAR APPLE X5','BLL APPLE X5'], columns=['A'])

df["B"] = df["A"].map(lambda x: "Long" if "BULL" in x else "Short" if "BEAR" in x else "")

print(df)

或使用包含：

df = pd.DataFrame([['BULL APPLE X5',''],['BEAR APPLE X5',''],['BULL APPLE X5','']], columns=['A','B'])


df["B"][df['A'].str.contains("BULL")] = "Long"
df["B"][df['A'].str.contains("BEAR")] = "Short"

print(df)
0  BULL APPLE X5   Long
1  BEAR APPLE X5  Short
2  BULL APPLE X5   Long