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I have a column with consecutive digits in a Pandas DataFrame.
A 1 2 3 4 I would like to change all those values to a simple string, say "foo", resulting in
A foo foo foo foo 
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Pandas DataFrame fillna() MethodThe fillna() method replaces the NULL values with a specified value. The fillna() method returns a new DataFrame object unless the inplace parameter is set to True , in that case the fillna() method does the replacing in the original DataFrame instead.
Press "Ctrl-Enter" on the keyboard. Excel fills the other cells in the column with the same value.
You can set cell value of pandas dataframe using df.at[row_label, column_label] = 'Cell Value'. It is the fastest method to set the value of the cell of the pandas dataframe. Dataframe at property of the dataframe allows you to access the single value of the row/column pair using the row and column labels.
Fill Data in an Empty Pandas DataFrame by Appending Rows First, create an empty DataFrame with column names and then append rows one by one. The append() method can also append rows. When creating an empty DataFrame with column names and row indices, we can fill data in rows using the loc() method.
Just select the column and assign like normal:
In [194]: df['A'] = 'foo' df Out[194]: A 0 foo 1 foo 2 foo 3 foo Assigning a scalar value will set all the rows to the same scalar value
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The good answer above throws a warning. You can also do:
df.insert(0, 'A', 'foo') where 0 is the index where the new column will be inserted.
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