Converting Exponential to Float

Converting exponential to float

The easy way is replace! One simple example:

value=str('6,0865000000e-01')
value2=value.replace(',', '.')
float(value2)
0.60865000000000002

Converting a number in exponential form to decimal form in python

You need to convert to a float and use str.format specifying the precision:

 In [41]: print "{:f}".format(float("1.70000043572e-05"))
 0.000017

# 16 digits 
In [38]: print "{:.16f}".format(float("1.70000043572e-05"))
0.0000170000043572

Just calling float would give 1.70000043572e-05.

Using older style formatting:

In [45]: print( "%.16f" % float("1.70000043572e-05"))
0.0000170000043572

Query to convert exponential number to float in SQL Server

Provide correct output for this so that we test and throw few more sample data.

Try this,

SELECT CONVERT(decimal(18,8), CAST('5E-05' AS FLOAT))

Converting exponential notation numbers to strings - explanation

When you use pd.read_csv to import data and do not define datatypes,
pandas makes an educated guess and in this case decides, that column
values like "2.04256e+14" are best represented by a float value.

This, converted back to string adds a ".0". As you corrently write,
converting to int64 fixes this.

If you know that the column has int64 values only before input (and
no empty values, which np.int64 cannot handle), you can force this type on import to avoid the unneeded conversions.

import numpy as np

temp=u"""Total,Price,test_num
0,71.7,2.04256e+14
1,39.5,2.04254e+14
2,82.2,2.04188e+14
3,42.9,2.04171e+14"""

df = pd.read_csv(pd.compat.StringIO(temp), dtype={2: np.int64})

print(df)

returns

   Total  Price         test_num
0      0   71.7  204256000000000
1      1   39.5  204254000000000
2      2   82.2  204188000000000
3      3   42.9  204171000000000

Convert Scientific Notation to Float

You are looking at the default str() formatting of floating point numbers, where scientific notation is used for sufficiently small or large numbers.

You don't need to convert this, the value itself is a proper float. If you need to display this in a different format, format it explicitly:

>>> print(0.00001357)
1.357e-05
>>> print(format(0.00001357, 'f'))
0.000014
>>> print(format(0.00001357, '.8f'))
0.00001357

Here the f format always uses fixed point notation for the value. The default precision is 6 digits; the .8 instructs the f formatter to show 8 digits instead.

In Python 3, the default string format is essentially the same as format(fpvalue, '.16g'); the g format uses either a scientific or fixed point presentation depending on the exponent of the number. Python 2 used '.12g'.

pandas converting a float remove exponents

You are trying to avoid using scientific notation:So here is what you can do:

import pandas as pd
pd.set_option('display.float_format', lambda x: '%.3f' % x)

this line of code set the pandas display format so it will not use scientific notaion

reference:http://pandas.pydata.org/pandas-docs/stable/options.html?highlight=display%20float_format

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