python - 使用 Pandas 读取数据并将其设置为 DataFrame 的索引

Question

我想迭代 DataFrame 的行并将值分配给新的 DataFrame。我已经像这样间接完成了这项任务:

#first I read the data from df1 and assign it to df2 if something happens
counter = 0                         #line1
for index,row in df1.iterrows():    #line2
    value = row['df1_col']          #line3
    value2 = row['df1_col2']          #line4
    #try unzipping a file (pseudo code)                  
        df2.loc[counter,'df2_col'] = value  #line5
        counter += 1                        #line6
    #except
        print("Error, could not unzip {}")  #line7

#then I set the desired index for df2
df2 = df2.set_index(['df2_col'])  #line7

有没有办法直接在第5行将值分配给df2的索引？抱歉，我原来的问题不清楚。我正在根据发生的事情创建一个索引。

Answer 1

有很多方法可以做到这一点。根据您的代码，您所做的只是创建一个空的 df2 数据框，其中包含 df1.df1_col 中的值索引。您可以直接这样做:

df2 = pd.DataFrame([], df1.df1_col)
#                   ^     ^
#                   |     |
# specifies no data, yet  |
#                        defines the index

如果您担心必须过滤df1，那么您可以这样做:

# cond is some boolean mask representing a condition to filter on.
# I'll make one up for you.
cond = df1.df1_col > 10
df2 = pd.DataFrame([], df1.loc[cond, 'df1_col'])