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I'm trying to use the 0th column ("Gene.name") as the Index values. Here's the original data below:
I tried to set the index a few different ways. The first was using index_col=0 in the DataFrame creation. I also tried DF_mutations.index = DF_mutations["Gene.name"] but they both led to an empty row underneath the header show below:
How can I get rid of this extra row when I'm reassigning the index values?
537
Use concat() to Add Row at Top of DataFrame concat([new_row,df. loc[:]]). reset_index(drop=True) to add the row to the first position of the Pandas DataFrame as Index starts from zero. reset_index() will reset the Index on the DataFrame to adjust the indexes on other rows.
The most straightforward way to drop a Pandas dataframe index is to use the Pandas . reset_index() method. By default, the method will only reset the index, forcing values from 0 - len(df)-1 as the index. The method will also simply insert the dataframe index into a column in the dataframe.
concat() function to insert a row at any given position in the dataframe.
You can create a DataFrame and append a new row to this DataFrame from dict, first create a Python Dictionary and use append() function, this method is required to pass ignore_index=True in order to append dict as a row to DataFrame, not using this will get you an error.
The empty row in the print you see is because the index has a name - Gene.name (This is not a real row in the DataFrame though) . If you don't want that row , I believe you would need to do away with the name. Example -
df.index.name = None
Demo -
In [6]: df = pd.DataFrame([[1,2,3,4],[1,2,3,4]]).set_index(0)
In [7]: df
Out[7]:
1 2 3
0 <-------------------------- Name of the index for this DataFrame
1 2 3 4
1 2 3 4
In [10]: df.index.name=None
In [11]: df
Out[11]:
1 2 3
1 2 3 4
1 2 3 4
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