Python Pandas 用顶行替换标题
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Python Pandas Replacing Header with Top Row
提问by Jeremy G
I currently have a dataframe that looks like this:
我目前有一个如下所示的数据框：
Unnamed: 1 Unnamed: 2 Unnamed: 3 Unnamed: 4
0 Sample Number Group Number Sample Name Group Name
1 1.0 1.0 s_1 g_1
2 2.0 1.0 s_2 g_1
3 3.0 1.0 s_3 g_1
4 4.0 2.0 s_4 g_2
I'm looking for a way to delete the header row and make the first row the new header row, so the new dataframe would look like this:
我正在寻找一种删除标题行并使第一行成为新标题行的方法，因此新数据框将如下所示：
Sample Number Group Number Sample Name Group Name
0 1.0 1.0 s_1 g_1
1 2.0 1.0 s_2 g_1
2 3.0 1.0 s_3 g_1
3 4.0 2.0 s_4 g_2
I've tried stuff along the lines of if 'Unnamed' in df.columns:then make the dataframe without the header df.to_csv(newformat,header=False,index=False)but I don't seem to be getting anywhere.
我已经尝试了一些方法，if 'Unnamed' in df.columns:然后在没有标题的情况下制作数据框，df.to_csv(newformat,header=False,index=False)但我似乎没有任何进展。
采纳答案by rgalbo
new_header = df.iloc[0] #grab the first row for the header
df = df[1:] #take the data less the header row
df.columns = new_header #set the header row as the df header
回答by JoeCondron
The dataframe can be changed by just doing
只需执行以下操作即可更改数据框
df.columns = df.iloc[0]
df = df[1:]
Then
然后
df.to_csv(path, index=False)
Should do the trick.
应该做的伎俩。
回答by ostrokach
If you want a one-liner, you can do:
如果你想要一个单线，你可以这样做：
df.rename(columns=df.iloc[0]).drop(df.index[0])
回答by GoPackGo
@ostrokach answer is best. Most likely you would want to keep that throughout any references to the dataframe, thus would benefit from inplace = True.df.rename(columns=df.iloc[0], inplace = True)
df.drop([0], inplace = True)
@ostrokach 答案是最好的。您很可能希望在对数据框的任何引用中都保留它，因此将从 inplace = True 中受益。df.rename(columns=df.iloc[0], inplace = True)
df.drop([0], inplace = True)
回答by rra
--another way to do this
--另一种方式来做到这一点
df.columns = df.iloc[0]
df = df.reindex(df.index.drop(0)).reset_index(drop=True)
df.columns.name = None
Sample Number Group Number Sample Name Group Name
0 1.0 1.0 s_1 g_1
1 2.0 1.0 s_2 g_1
2 3.0 1.0 s_3 g_1
3 4.0 2.0 s_4 g_2
If you like it hit up arrow. Thanks
如果你喜欢它击中箭头。谢谢
回答by Alex P. Miller
Here's a simple trick that defines column indices "in place". Because set_indexsets rowindices in place, we can do the same thing for columns by transposing the data frame, setting the index, and transposing it back:
这是一个简单的技巧，可以“就地”定义列索引。因为set_index设置了行索引，我们可以通过转置数据框、设置索引并将其转回来对列执行相同的操作：
df = df.T.set_index(0).T
Note you may have to change the 0in set_index(0)if your rows have a different index already.
请注意0，set_index(0)如果您的行已经有不同的索引，您可能需要更改in 。
回答by Fazley Rafy
header = table_df.iloc[0]
table_df.drop([0], axis =0, inplace=True)
table_df.reset_index(drop=True)
table_df.columns = header
table_df
