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Dealing with decimals with many digits in Pandas,

pd.set_option('display.max_colwidth', None )
pd.set_option('display.float_format', lambda x: '%.200f' % x)
exData = pd.read_csv('AP11.csv',delimiter=';',float_precision=None)
x = exData.loc[:,['A','B']]
y = exData.loc[:,['C']]
x
my original float on excel is 0.1211101931541032183754113717355410323332315436353654273243543132542237415430173719
what is being displayed is
0.12111019315410319341363987177828676067292690277099609375000000000000000000000000000000000000000000000000000000000...
this is not a display issue. something in pandas rounds my float. i don't want to round any number for it will affect the result of my string. because this is originally a string that is converted to a float. i tried to use int64 but it can't handle big numbers. so instead i decided to use floats with "0.mystring" to not get "inf" displayed in pandas. and i get it rounded. is machine learning limited by these missy variables? or is there another way to deal with big numbers without rounding, displaying inf?

Use decimal instead of float. Just put
from decimal import Decimal
at the top of your code, and write your floats as
x = Decimal(0.121110193154103218375411371735541032333231543635365427324354313254223741543017371)
decimal is a library for floats with a dynamic length, rather than rounded.
Generally you should avoid floats, as they can have strange irregularities and roundings. Often when operations are performed on them, they can have a series of zeros and then some other numbers, when it should just have a few decimal places.

Clean way to convert string to floating point number with specific precision?

I'm trying to convert strings of numbers that come from the output of another program into floating point numbers with two forced decimal places (including trailing zeros).
Right now I'm converting the strings to floats, then separately specifying precision (two decimal places), then converting back to float to do numeral comparisons on later.
# convert to float
float1 = float(output_string[6])
# this doesn't guarantee two decimal places in my output
# eg: -36.55, -36.55, -40.34, -36.55, -35.7 (no trailing zero on the last number)
nice_float = float('{0:.2f}'.format(float1))
# this works but then I later need to convert back into a float
# string->float->string->float is not super clean
nice_string = '{0:.2f}'.format(float1)
Edit for clarity:
I have a problem with the display in that I need that to show exactly two decimal places.
Is there a way to convert a string to a floating point number rounded to two decimal places that's cleaner than my implementation which involves converting a string to a float, then the float back into a formatted string?

Rounding Off function to given decimal without using round function

I am trying to write a function to round a floating point number up to n decimal places. The function can take one or two arguments. If there is only one argument the number should be rounded to two decimal places.
This is where I have gotten so far:
def roundno(num,point=2):
import math
x=1*(math.pow(10,-point))
round=0
while (num>x):
while(num>0):
round+=num/10
num=num/10
round*=10
round+=num/10
num=num/10
round*=0.1
return round
I am getting infinity as the output, every time... Where did I go wrong?

I can't see how your algorithm is supposed to round numbers. I guess a similar strategy could work, but you'd need a subtraction in there somewhere...
One way to do this would be to convert the argument to a string, adjust the number of digits after the decimal point, and then convert the string back to a float, but I suspect that your teacher would not like that solution. :)
Here's a simple way to do rounding arithmetically:
def roundno(num, point=2):
scale = 10.0 ** point
return int(num * scale) / scale
data = [123, 12.34, 1.234, 9.8765, 98.76543]
for n in data:
print n, roundno(n), roundno(n, 3)
output
123 123.0 123.0
12.34 12.34 12.34
1.234 1.23 1.234
9.8765 9.87 9.876
98.76543 98.76 98.765
This simply drops unwanted digits, but it's not hard to modify it to round up or off (your question isn't clear on exactly what type of rounding you want).
Note that this function doesn't check the point argument. It really should check that it's a non-negative integer and raise ValueError with an appropriate error message otherwise.

Problems with decimals and scientific notation in Python 2.6.6

I'm having difficulty with decimal values that I need to use for arithmetic in some cases and as strings in others. Specifically I have a list of rates, ex:
rates=[0.1,0.000001,0.0000001]
And I am using these to specify the compression rates for images. I need to initially have these values as numbers because I need to be able to sort them to make sure they are in a specific order. I also want to be able to convert each of these values to strings so I can 1) embed the rate into the filename and 2) log the rates and other details in a CSV file. The first problem is that any float with more than 6 decimal places is in scientific format when converted to a string:
>>> str(0.0000001)
'1e-07'
So I tried using Python's Decimal module but it is also converting some floats to scientific notation (seemingly contrary to the docs I've read). Ex:
>>> Decimal('1.0000001')
Decimal('1.0000001')
# So far so good, it doesn't convert to scientific notation with 7 decimal places
>>> Decimal('0.0000001')
Decimal('1E-7')
# Scientific notation, back where I started.
I've also looking into string formatting as suggested in multiple posts, but I've not had any luck. Any suggestions and pointers are appreciated by this Python neophyte.

You have to specify the string format then:
["%.8f" % (x) for x in rates]
This yields ['0.10000000', '0.00000100', '0.00000010']. Works with Decimal, too.

'{0:f}'.format(Decimal('0.0000001'))
The above should work for you

See % formatting, especially the floating point conversions:
'e' Floating point exponential format (lowercase). (3)
'E' Floating point exponential format (uppercase). (3)
'f' Floating point decimal format. (3)
'F' Floating point decimal format. (3)
'g' Floating point format. Uses lowercase exponential format if exponent is less than -4 or not less than precision, decimal format otherwise. (4)
'G' Floating point format. Uses uppercase exponential format if exponent is less than -4 or not less than precision, decimal format otherwise. (4)
An example, using f format.
>>> ["%10.7f" %i for i in rates]
[' 0.1000000', ' 0.0000010', ' 0.0000001']
>>>
You can also use the newer (starting 2.6) str.format() method:
>>> ['{0:10.7f}'.format(i) for i in rates]
[' 0.1000000', ' 0.0000010', ' 0.0000001']
>>>

Using f-strings:
>>> rates = [0.1, 0.000001, 0.0000008]
>>> [f'{r:.7f}' for r in rates]
['0.1000000', '0.0000010', '0.0000008']
The string format {r:.7f} indicates the number of digits used after the decimal point, which in this case is 7.

How to store exponential values using python

I am looking for a way to perform a digit divided by larger value(2/5000000) and then store that value in table, but the problem is when i save that value, only 0 is stored , instead of correct value.I tried with float, double precision, but still only 0 is stored, is there any other way .
Thank you

Remember to operate on floating numbers, and not convert it after the operation. E.g. 2/5000000.
Also, use the Decimal library, if you are looking for more accurate decimals.

You need to use floating point division. To be explicit, you can cast ints to float:
>>> a = 2
>>> b = 5000000
>>> c = a/float(b)
>>> c
4e-07
You can cast either a or b to float.