CODEWITHSUNDEEP
pythonpandasdataframetruncate
geistmate
geistmate

Reputation: 555

Pandas Dataframe How to cut off float decimal points without rounding?

I have longitude and latitude in two dataframes that are close together. If I run an exact similarity check such as

test_similar = test1_latlon.loc[~test1_latlon['cr'].isin(test2_latlon['cr'])]

I get a lot of failures because a lot of the numbers are off at the 5th decimal place. I want to truncate at after the 3rd decimal. I've seen people format so it shows up truncated, but I want to change the actual value. Using round() rounds off the data and I get even more errors, so is there a way to just drop after 3 decimal points?

Upvotes: 6

Views: 18251

Answers (3)

mikey
mikey

Reputation: 2644

You may want to use numpy.trunc:

import numpy as np
import pandas as pd

df = pd.DataFrame([[1.2366, 1.2310], [1, 1]])
df1 = np.trunc(1000 * df) / 1000
print(df1, type(df1))
#        0      1
# 0  1.236  1.231
# 1  1.000  1.000 <class 'pandas.core.frame.DataFrame'>

Note that df1 is still a DataFrame not a numpy.array

Upvotes: 10

jonboy
jonboy

Reputation: 368

import math

value1 = 1.1236
value2 = 1.1266

value1 = math.trunc(1000 * value1) / 1000;
value2 = math.trunc(1000 * value2) / 1000;

#value1 output
1.123

#value2 output
1.126

Upvotes: 4

Norman
Norman

Reputation: 485

As suggested here you can do:

x = 1.123456
float( '%.3f'%(x) )

if you want more decimal places, just change the 3 with any number you need.

Upvotes: 3

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