英文:
How can I duplicate the same row but with different information in a column in pandas?
问题
这是您的代码部分的翻译：
我的pandas数据框如下所示：```pythonimport pandas as pdtable = pd.DataFrame({'Range': ["A", "B", "C", "A"], 'First Name': ["W","X","Y", "Z"], 'ID': [1,2,3,4]})
我想要复制相同的行，如果在"Level"列中有文本"A"，则在"Activity"列中添加文本"Monitoring"和"Informant"，类似于这样：
我尝试使用以下代码进行复制：
columns_new = pd.DataFrame(columns=["NO ID","Level", "Name", "Activity"])row_modified = []for index, row in table.iterrows():rang = row['Range']f_name= row['First Name']n_id = row['ID']columns_new.loc[index, "NO ID"] = n_idcolumns_new.loc[index, "Level"] = rangcolumns_new.loc[index, "Name"] = f_nameif rang == "A":row_modified.append(row)row_modified.append(row)else:row_modified.append(row)column_new2 = pd.DataFrame(row_modified)column_new2
但我不知道如何添加我想要的文本 😅
如果您需要进一步的帮助或有其他问题，请随时告诉我。<details><summary>英文:</summary>My pandas dataframe looks like this:
import pandas as pd
table = pd.DataFrame({'Range': ["A", "B", "C", "A"],'First Name': ["W","X","Y", "Z"], 'ID': [1,2,3,4]})
I want to replicate the same row if in the "Level" column I have the text "A", but in the "Activity" column add the text "Monitoring" and "Informant", something like this:I tried to make the duplicate with this code
columns_new = pd.DataFrame(columns=["NO ID","Level", "Name", "Activity"])
row_modified = []
for index, row in table.iterrows():
rang = row['Range']
f_name= row['First Name']
n_id = row['ID']
columns_new.loc[index, "NO ID"] = n_id
columns_new.loc[index, "Level"] = rang
columns_new.loc[index, "Name"] = f_name
if rang == "A":row_modified.append(row)row_modified.append(row)else:row_modified.append(row)
column_new2 = pd.DataFrame(row_modified)
column_new2
But I don't know how to add the texts I want 😅</details># 答案1**得分**: 2你可以使用 [`merge`](https://pandas.pydata.org/docs/reference/api/pandas.merge.html) 函数：```pythons = pd.Series(['Monitoring', 'Informant'], index=['A', 'A'], name='Activity')(table.merge(s, left_on='Range', right_index=True, how='left').fillna({'Activity': 'Assistant'}))
输出结果：
Range First Name ID Activity0 A W 1 Monitoring0 A W 1 Informant1 B X 2 Assistant2 C Y 3 Assistant3 A Z 4 Monitoring3 A Z 4 Informant
英文:
You can use a merge:
s = pd.Series(['Monitoring', 'Informant'], index=['A', 'A'], name='Activity')(table.merge(s, left_on='Range', right_index=True, how='left').fillna({'Activity': 'Assistant'}))
Output:
Range First Name ID Activity0 A W 1 Monitoring0 A W 1 Informant1 B X 2 Assistant2 C Y 3 Assistant3 A Z 4 Monitoring3 A Z 4 Informant
答案2
得分: 1
你可以使用一个映射字典：
d = {'A': ['监控', '通知者']}out = (table.assign(活动=table['范围'].map(d).fillna('助手')).explode('活动'))print(out)# 输出结果范围 姓 ID 活动0 A W 1 监控0 A W 1 通知者1 B X 2 助手2 C Y 3 助手3 A Z 4 监控3 A Z 4 通知者
英文:
You can use a mapping dict:
d = {'A': ['Monitoring', 'Informant']}out = (table.assign(Activity=table['Range'].map(d).fillna('Assistant')).explode('Activity'))print(out)# OutputRange First Name ID Activity0 A W 1 Monitoring0 A W 1 Informant1 B X 2 Assistant2 C Y 3 Assistant3 A Z 4 Monitoring3 A Z 4 Informant
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