Reputation: 1354
When I try to convert the following dictionary to dataframe, python repeats each row twice.
a = [[[[130.578125, 96, 130.59375, 541],
[130.5625, 635, 130.609375, 1055],
[130.546875, 657, 130.625, 1917],
[130.53125, 707, 130.640625, 1331],
[130.515625, 1530, 130.65625, 2104]],
[[130.578125, 96, 130.59375, 541],
[130.5625, 635, 130.609375, 1055],
[130.546875, 657, 130.625, 1917],
[130.53125, 707, 130.640625, 1331],
[130.515625, 1530, 130.65625, 2104]]],
[[[143.34375, 5, 143.359375, 79],
[143.328125, 142, 143.375, 129],
[143.3125, 132, 143.390625, 137],
[143.296875, 126, 143.40625, 118],
[143.28125, 113, 143.421875, 125]],
[[143.34375, 5, 143.359375, 79],
[143.328125, 142, 143.375, 129],
[143.3125, 132, 143.390625, 137],
[143.296875, 126, 143.40625, 118],
[143.28125, 113, 143.421875, 125]]]]
b = ['Mini','on']
c = dict(zip(b,a))
d = pd.DataFrame.from_dict(c)
print d
Python prints the following output:
Mini \
0 [[130.578125, 96, 130.59375, 541], [130.5625, ...
1 [[130.578125, 96, 130.59375, 541], [130.5625, ...
on
0 [[143.34375, 5, 143.359375, 79], [143.328125, ...
1 [[143.34375, 5, 143.359375, 79], [143.328125, ...
The desired output is:
Mini \
0 [[130.578125, 96, 130.59375, 541], [130.5625, ...
on
0 [[143.34375, 5, 143.359375, 79], [143.328125, ...
Can someone please suggest how I can fix this?
Upvotes: 2
Views: 253
Reputation: 294506
Let's start with an example
You're getting
pd.DataFrame({'Mini': [1, 1], 'on': [2, 2]})
When you want
pd.DataFrame({'Mini': [1], 'on': [2]})
You're definition of a
is a 2x2x5x4 array in list form. The first dimension is getting zipped away into the values of the dict
. The second dimension is a list of length 2 and I've just demonstrated what happens when you pass such a dictionary to pd.DataFrame
To fix it, swap the following line with your previous definition of d
d = pd.Series(c).to_frame().T
Response to comment
To print entire cell content
with pd.option_context('display.max_colwidth', -1):
print d
Upvotes: 1