Terminate each number in Python pandas dataframe by 2 decimal places
This works p_table.apply(pd.Series.round)
but has no decimal places
import pandas as pd
Series.round(decimals=0, out=None)
I tried this p_table.apply(pd.Series.round(2))
, but I get this error:
unbound method round() must be called with Series instance as first argument (got int instance instead)
How do I concatenate all the elements in a dataframe with two decimal places?
[EDIT] Figured it out.
import numpy as np
np.round(p_table, decimals=2)
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From 0.17.0
version 0.17.0
you can do .round(n)
df.round(2)
0 1 2 3
0 0.06 0.67 0.77 0.71
1 0.80 0.56 0.97 0.15
2 0.03 0.59 0.11 0.95
3 0.33 0.19 0.46 0.92
df
0 1 2 3
0 0.057116 0.669422 0.767117 0.708115
1 0.796867 0.557761 0.965837 0.147157
2 0.029647 0.593893 0.114066 0.950810
3 0.325707 0.193619 0.457812 0.920403
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what: data.apply(lambda x: np.round(x, decimals=2))
--- timeit.timer for 100x: 0.00356676544494
- this is the same, but slower: np.round(data,decimals=2)
--- timeit.timer for 100x: 0.000921095
for example both give:
x y z
Input Sequence
1 5.60 0.85 -6.50
2 5.17 0.72 -6.50
3 5.60 0.89 -6.28
4 5.17 0.76 -6.29
for data:
x y z
Input Sequence
1 5.6000 0.8519 -6.5000
2 5.1730 0.7151 -6.5000
3 5.6000 0.8919 -6.2794
4 5.1724 0.7551 -6.2888
5 5.6000 0.9316 -6.0587
Below is an example of a reproducible possible way to do this using the round pandas function .
# importing pandas as pd
import pandas as pd
# generate sample dataframe
df = pd.DataFrame(np.random.random([5, 4]), columns =["A", "B", "C"])
# use pandas dataframe.round()function to round off all the decimal values to 2 decimal
df.round(2)
# If you want to customize the round off by individual columns
df.round({"A":1, "B":2, "C":3})
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