Create a pandas dataframe with null columns

Question

I am having a hard time figuring this out. I am working on a program to keep track of some data associated with a bunch of files. I am using pandas to manage the data and load/save it. For the first run, the program identifies the files with the extension, and creates a pandas dataframe with some number of columns for the data associated with each file. The number of columns and the number of rows isn't known until runtime. I want to add all the file paths to a column, but leave all other columns blank for the DataFrame, is there a good way to do this? So if the input is [val1, val2, val3,...] then I want the DataFrame to be

[col1, col2, col,...,coln]
[val1, NaN, NaN,...,  NaN]
[val2, NaN, NaN,...,  NaN]
[val3, NaN, NaN,...,  NaN]

Thanks for any help!

miriamsimone · Accepted Answer · 2016-10-24 03:07:49Z

2

If you create your dataframe from a dict, any extra columns specified in the columns keyword will be initialized as null:

In [3]: pd.DataFrame({'col1':['val1','val2','val3']}, 
                     columns=['col1','col2','col3'])
Out[3]:
   col1 col2 col3
0  val1  NaN  NaN
1  val2  NaN  NaN
2  val3  NaN  NaN

Alternatively if your first column is an index, you can use this syntax:

In [4]: pd.DataFrame([], ['val1','val2','val3'], ['col1','col2','col3'])
Out[4]:
     col1 col2 col3
val1  NaN  NaN  NaN
val2  NaN  NaN  NaN
val3  NaN  NaN  NaN

edited Oct 24, 2016 at 3:07

answered Oct 23, 2016 at 23:53

miriamsimone

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1 Comment

Grimey Over a year ago

Awesome! Thanks for the quick reply!

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