Rename unnamed column pandas dataframe
PythonPandasCsvPython Problem Overview
My csv file has no column name for the first column, and I want to rename it. Usually, I would do data.rename(columns={'oldname':'newname'}, inplace=True), but there is no name in the csv file, just ''.
Python Solutions
Solution 1 - Python
You can view the current dataframe using
data.head()
if that returns 'Unnamed: 0' as the column title, you can rename it in the following way:
data.rename( columns={'Unnamed: 0':'new column name'}, inplace=True )
Solution 2 - Python
When you load the csv, use the option 'index_col' like
pd.read_csv('test.csv', index_col=0)
> index_col : int or sequence or False, default None Column to use as > the row labels of the DataFrame. If a sequence is given, a MultiIndex > is used. If you have a malformed file with delimiters at the end of > each line, you might consider index_col=False to force pandas to not > use the first column as the index (row names)
http://pandas.pydata.org/pandas-docs/dev/generated/pandas.io.parsers.read_csv.html
Solution 3 - Python
The solution can be improved as data.rename( columns={0 :'new column name'}, inplace=True ). There is no need to use 'Unnamed: 0', simply use the column number, which is 0 in this case and then supply the 'new column name'.
Solution 4 - Python
This should work:
data.rename( columns={0 :'Articles'}, inplace=True )
Solution 5 - Python
Try the below code,
df.columns = [‘A’, ‘B’, ‘C’, ‘D’]
Solution 6 - Python
It can be that the first column/row could not have a name, because it's an index and not a column/row. That's why you need to rename the index like this:
df.index.name = 'new_name'
Solution 7 - Python
usually the blank column names are named based on their index
so for example lets say the 4 column is unnamed.
df.rename({'unnamed:3':'new_name'},inplace=True)
usually it is named like this since the indexing of columns start with zero.
Solution 8 - Python
It has a name, the name is just '' (the empty string).
In [2]: df = pd.DataFrame({'': [1, 2]})
In [3]: df
Out[3]:
0 1
1 2
In [4]: df.rename(columns={'': 'A'})
Out[4]:
A
0 1
1 2
Solution 9 - Python
Another solution is to invoke the columns of the dataframe and use replace:
df.columns = df.columns.str.replace('Unnamed: 0','new_name')