熊猫在聚合后选择要保存的列

Question

I'm reading data and calculate mean for groups, and then save the data to other file. The problem is that I want to select only some of the columns to write to that file, currently it gives me error, so I have to save all to the file, then reopen, choose columns and write again.

This code doesn't work:

df = pd.read_csv("./file.csv")
grouped = df.groupby(['Condition','ID','BeginEnd'])
agg = grouped.mean()
agg = agg[['Condition','ID','BeginEnd3','KnowledgeScore']]
agg.to_csv('file2.csv')

I have to do this:

df = pd.read_csv("./file.csv")
grouped = df.groupby(['Condition','ID','BeginEnd'])
agg = grouped.mean()
agg.to_csv('file2.csv')
df3 = pd.read_csv('file2.csv')
df3 = df3[['Condition','ID','BeginEnd3','KnowledgeScore']]
df3.to_csv('file2.csv')

Answer 1

You didn't post either the code you tried which didn't work or the full traceback of the error message, so we're left having to guess what the issue is. ("currently it gives me error" isn't very useful.) I'm assuming you tried something like

agg = agg[['Condition','ID','BeginEnd3','KnowledgeScore']]

That wouldn't have worked because after grouping, the columns that you grouped on become parts of the index ( print agg.index to see) and not columns ( print agg.columns ). You can promote them to columns again using reset_index :

agg = grouped.mean().reset_index()

---

Example:

>>> df
   A  B  C
0  0  2  6
1  0  2  7
2  1  3  8
3  1  4  9
>>> grouped = df.groupby(["A", "B"])
>>> agg = grouped.mean()
>>> agg
       C
A B     
0 2  6.5
1 3  8.0
  4  9.0
>>> agg = agg.reset_index()
>>> agg
   A  B    C
0  0  2  6.5
1  1  3  8.0
2  1  4  9.0