Format Suppress Scientific Notation from Python Pandas Aggregation Results

Question

How can one modify the format for the output from a groupby operation in pandas that produces scientific notation for very large numbers    I know how to do string formatting in python but I m at a loss when it comes to applying it here    df1 groupby  dept    data1   sum    dept value1       1 192433e 08 value2       1 293066e 08 value3       1 077142e 08   This suppresses the scientific notation if I convert to string but now I m just wondering how to string format and add decimals    sum sales dept astype str

User · Answer

I had multiple dataframes with different floating point, so thx to Allans idea made dynamic length.

pd.set_option('display.float_format', lambda x: f'%.{len(str(x%1))-2}f' % x)

The minus of this is that if You have last 0 in float, it will cut it. So it will be not 0.000070, but 0.00007.

User · Answer

Here is another way of doing it  similar to Dan Allan s answer but without the lambda function    gt  gt  gt  pd options display float format       2f   format  gt  gt  gt  Series np random randn 3   0    0 41 1    0 99 2    0 10   or    gt  gt  gt  pd set option  display float format       2f   format

User · Answer

Setting a fixed number of decimal places globally is often a bad idea since it is unlikely that it will be an appropriate number of decimal places for all of your various data that you will display regardless of magnitude   Instead  try this which will give you scientific notation only for large and very small values  and adds a thousands separator unless you omit the  quot   quot    pd set option  display float format   lambda x     g    x   Or to almost completely suppress scientific notation without losing precision  try this  pd set option  display float format   str

User · Answer

Granted  the answer I linked in the comments is not very helpful  You can specify your own string converter like so   In  25   pd set option  display float format   lambda x     3f    x   In  28   Series np random randn 3   1000000000 Out 28    0    -757322420 605 1   -1436160588 997 2   -1235116117 064 dtype  float64   I m not sure if that s the preferred way to do this  but it works   Converting numbers to strings purely for aesthetic purposes seems like a bad idea  but if you have a good reason  this is one way   In  6   Series np random randn 3   apply lambda x     3f    x  Out 6    0     0 026 1    -0 482 2    -0 694 dtype  object

User · Answer

If you would like to use the values  say as part of csvfile csv writer  the numbers can be formatted before creating a list   df  label   apply lambda x     17f    x  values tolist

User · Answer

You can use round function just to suppress scientific notation for specific dataframe   df1 round 4    or you can suppress is globally by   pd options display float format       4f   format

User · Answer

If you want to style the output of a data frame in a jupyter notebook cell  you can set the display style on a per-dataframe basis   df   pd DataFrame   A   np random randn 4  1e7   df style format     1f        See the documentation here

[python] Format / Suppress Scientific Notation from Python Pandas Aggregation Results

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