Suppressing scientific notation in pandas?

numpy, pandas, python

Solution

Your data is probably `object` dtype. This is a direct copy/paste of your data. `read_csv` interprets it as the correct dtype. You should normally only have `object` dtype on string-like fields.

In [5]: df = read_csv(StringIO(data),sep='\s+')

In [6]: df
Out[6]: 
           id     value
id       1.00 -0.422000
value   -0.42  1.000000
percent -0.72  0.100000
played   0.03 -0.043500
money   -0.22  0.337000
other     NaN       NaN
sy      -0.03  0.000219
sz      -0.33  0.383000

check if your dtypes are `object`

In [7]: df.dtypes
Out[7]: 
id       float64
value    float64
dtype: object

This converts this frame to `object` dtype (notice the printing is funny now)

In [8]: df.astype(object)
Out[8]: 
           id     value
id          1    -0.422
value   -0.42         1
percent -0.72       0.1
played   0.03   -0.0435
money   -0.22     0.337
other     NaN       NaN
sy      -0.03  0.000219
sz      -0.33     0.383

This is how to convert it back (`astype(float)`) also works here

In [9]: df.astype(object).convert_objects()
Out[9]: 
           id     value
id       1.00 -0.422000
value   -0.42  1.000000
percent -0.72  0.100000
played   0.03 -0.043500
money   -0.22  0.337000
other     NaN       NaN
sy      -0.03  0.000219
sz      -0.33  0.383000

This is what an `object` dtype frame would look like

In [10]: df.astype(object).dtypes
Out[10]: 
id       object
value    object
dtype: object

Problem

I have a DataFrame in pandas where some of the numbers are expressed in scientific notation (or exponent notation) like this: ``` id value id 1.00 -4.22e-01 value -0.42 1.00e+00 percent -0.72 1.00e-01 played 0.03 -4.35e-02 money -0.22 3.37e-01 other NaN NaN sy -0.03 2.19e-04 sz -0.33 3.83e-01 ``` And the scientific notation makes what should be an easy comparison, needlessly difficult. I assume it's the 21900 value that's screwing it up for the others. I mean 1.0 is encoded. ONE! This doesn't work: ``` np.set_printoptions(supress=True) ``` And `pandas.set_printoptions` doesn't implement suppress either, and I've looked all at `pd.describe_options()` in despair, and `pd.core.format.set_eng_float_format()` only seems to turn it on for all the other float values, with no ability to turn it off.

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