entityMap|blocks|key|1a34i|text|你可以这样做：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2e79g|df_new=df.groupby('ID')['Name'].apply(lambda+x:+','.join(list(x))).reset_index()
df_new.join(df_new.pop('Name').str.split(",",expand=True))

+++ID++0++1+++++2
0+++1++A++B++None
1+++2++X++Y+++++Z|code-block|syntax|javascript|cnael^0|0|0^^$0|$]|1|@$2|3|4|5|6|7|8|I|9|@]|A|@]|B|$]]|$2|C|4|D|6|E|8|J|9|@]|A|@]|B|$F|G]]|$2|H|4|-4|6|7|8|K|9|@]|A|@]|B|$]]]]

you can do something like:

<pre><code>df_new=df.groupby('ID')['Name'].apply(lambda x: ','.join(list(x))).reset_index()
df_new.join(df_new.pop('Name').str.split(",",expand=True))

 ID 0 1 2
0 1 A B None
1 2 X Y Z
</code></pre>

entityMap|blocks|key|elp1b|text|通过+DataFrame.set_index+使用+GroupBy.cumcount+计数器创建+MultiIndex+并通过+Series.unstack+使用+DataFrame.reset_index+重塑索index：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|7f2r5|df1+=+(df.set_index(['ID',df.groupby('ID').cumcount()])['Name']
+++++++++.unstack(fill_value='')
+++++++++.reset_index())
print+(df1)
+++ID++0++1++2
0+++1++A++B+++
1+++2++X++Y++Z|code-block|syntax|javascript|e5mcg|small+DataFrame中的性能|cdrp8|np.random.seed(123)
N+=+1000
L+=+list('abcdefghijklmno')
df+=+pd.DataFrame({'Name':+np.random.choice(L,+N),
+++++++++++++++++++'ID':np.random.randint(100,+size=N)}).sort_values('ID')
#print+(df)

In+[15]:+%25%25timeit
++++...:+df_new=df.groupby('ID')['Name'].apply(lambda+x:+','.join(list(x))).reset_index()
++++...:+df_new.join(df_new.pop('Name').str.split(",",expand=True))
++++...:+
22+ms+±+411+µs+per+loop+(mean+±+std.+dev.+of+7+runs,+10+loops+each)

In+[16]:+%25%25timeit
++++...:+df1+=+(df.set_index(['ID',df.groupby('ID').cumcount()])['Name']
++++...:++++++++++.unstack(fill_value='')
++++...:++++++++++.reset_index())
++++...:+
6.05+ms+±+212+µs+per+loop+(mean+±+std.+dev.+of+7+runs,+100+loops+each)

In+[17]:+%25%25timeit
++++...:+df.set_index('ID').groupby('ID').apply(lambda+x:+x.reset_index(drop=True).T).reset_index(level=1,drop=True)
++++...:+
151+ms+±+1.25+ms+per+loop+(mean+±+std.+dev.+of+7+runs,+10+loops+each)|3kbu^0|2|L|Q|G|1D|B|1R|G|2A|L|2Z|5|0|0|6|9|0|0^^$0|$]|1|@$2|3|4|5|6|7|8|Q|9|@$A|R|B|S|C|D]|$A|T|B|U|C|D]|$A|V|B|W|C|D]|$A|X|B|Y|C|D]|$A|Z|B|10|C|D]|$A|11|B|12|C|D]]|E|@]|F|$]]|$2|G|4|H|6|I|8|13|9|@]|E|@]|F|$J|K]]|$2|L|4|M|6|7|8|14|9|@$A|15|B|16|C|D]]|E|@]|F|$]]|$2|N|4|O|6|I|8|17|9|@]|E|@]|F|$J|K]]|$2|P|4|-4|6|7|8|18|9|@]|E|@]|F|$]]]]

Create <code>MultiIndex</code> by <a href="http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.set_index.html" rel="nofollow noreferrer"><code>DataFrame.set_index</code></a> with counter by <a href="http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.core.groupby.GroupBy.cumcount.html" rel="nofollow noreferrer"><code>GroupBy.cumcount</code></a> and reshape by <a href="http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.unstack.html" rel="nofollow noreferrer"><code>Series.unstack</code></a> with <a href="http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.reset_index.html" rel="nofollow noreferrer"><code>DataFrame.reset_index</code></a> for column from <code>index</code>:

<pre><code>df1 = (df.set_index(['ID',df.groupby('ID').cumcount()])['Name']
 .unstack(fill_value='')
 .reset_index())
print (df1)
 ID 0 1 2
0 1 A B 
1 2 X Y Z
</code></pre>

Performnace in small <code>DataFrame</code>:

<pre><code>np.random.seed(123)
N = 1000
L = list('abcdefghijklmno')
df = pd.DataFrame({'Name': np.random.choice(L, N),
 'ID':np.random.randint(100, size=N)}).sort_values('ID')
#print (df)

In [15]: %%timeit
 ...: df_new=df.groupby('ID')['Name'].apply(lambda x: ','.join(list(x))).reset_index()
 ...: df_new.join(df_new.pop('Name').str.split(",",expand=True))
 ...: 
22 ms ± 411 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)

In [16]: %%timeit
 ...: df1 = (df.set_index(['ID',df.groupby('ID').cumcount()])['Name']
 ...: .unstack(fill_value='')
 ...: .reset_index())
 ...: 
6.05 ms ± 212 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)

In [17]: %%timeit
 ...: df.set_index('ID').groupby('ID').apply(lambda x: x.reset_index(drop=True).T).reset_index(level=1,drop=True)
 ...: 
151 ms ± 1.25 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)
</code></pre>

entityMap|blocks|key|3fmha|text|你想要的东西可以通过下面的代码来创建。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|60mno|++++data+=+[[1,'A']+,+[1+,+'B']+,+[2+,+'X']+,+[2+,+'Y']+,+[2+,+'Z']]++
++++df+=+pd.DataFrame(data+,+columns=['ID'+,+'Name'])

++++id_list+=+df['ID'][~df['ID'].duplicated()]
++++t_rows+=+[]
++++max_val_num+=+0
++++for+id_+in+id_list:
++++++++row+=+df[df['ID']+==+id_]['Name'].tolist()
++++++++t_rows.append(row)
++++++++if+len(row)+>=+max_val_num:
++++++++++++max_val_num+=+len(row)

++++df_transform+=+pd.DataFrame(t_rows+,+columns=['col_'%2Bstr(i)+for+i+in+range(max_val_num)])++
++++print(df_transform)|code-block|syntax|javascript|1s31g^0|0|0^^$0|$]|1|@$2|3|4|5|6|7|8|I|9|@]|A|@]|B|$]]|$2|C|4|D|6|E|8|J|9|@]|A|@]|B|$F|G]]|$2|H|4|-4|6|7|8|K|9|@]|A|@]|B|$]]]]

What you want can be created by following code. 

<pre><code> data = [[1,'A'] , [1 , 'B'] , [2 , 'X'] , [2 , 'Y'] , [2 , 'Z']] 
 df = pd.DataFrame(data , columns=['ID' , 'Name'])

 id_list = df['ID'][~df['ID'].duplicated()]
 t_rows = []
 max_val_num = 0
 for id_ in id_list:
 row = df[df['ID'] == id_]['Name'].tolist()
 t_rows.append(row)
 if len(row) &gt;= max_val_num:
 max_val_num = len(row)

 df_transform = pd.DataFrame(t_rows , columns=['col_'+str(i) for i in range(max_val_num)]) 
 print(df_transform)
</code></pre>

I am sure this has been asked before (since it is a common question), but I am unable to find it.

So my dataframe looks like this:

<pre><code>ID Name
1 A
1 B
2 X
2 Y
2 Z
</code></pre>

I want it in this format (I don't care about the column names)

<pre><code>1 A B
2 X Y Z and so on...
</code></pre>

How to transpose a column based on the condition in another column?

 我肯定以前有人问过这个问题(因为这是一个常见的问题)，但我找不到它。 所以我的数据帧看起来是这样的： ID     Name1      A1      B2      X2      Y2      Z 我希望它采用这种格式(我不关心列名) 1    A    B2    X    Y   Z  and so on...

问如何根据另一列中的条件转置一列？
EN

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问如何根据另一列中的条件转置一列？
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