CODEWITHSUNDEEP
pandasdataframerounding
Smith Dwayne
Smith Dwayne

Reputation: 2797

Pandas handling rounding with very small number

I have a data frame like as below. I am trying to round the number to 1 decimal. But in some cases, if a number is 0.9 or below, I need to show the number with rounding exactly with the least precision

import pandas as pd
df_input = pd.read_csv('test.csv')
print(df_input)

The result of the data frame,

     Cateogry  Consumption
0  Category 1    31.248175
1  Category 1     0.401825
2  Category 2     0.178149
3  Category 2     6.538878
4  Category 3     0.011308
5  Category 3     0.023273
6  Category 4     0.000533
7  Category 5     0.126154

I am rounding up the above data frame as like below,

print(df_input.round(1))

     Cateogry  Consumption
0  Category 1         31.2
1  Category 1          0.4
2  Category 2          0.2
3  Category 2          6.5
4  Category 3          0.0   // It should show 0.01
5  Category 3          0.0   // It should show 0.02
6  Category 4          0.0   // It should show 0.0005
7  Category 5          0.1

Like I commented in rows 4, 5, 6, It should show the value as the way I show.

Is there anyway can I do that?

Upvotes: 0

Views: 569

Answers (1)

Daniel Wlazło
Daniel Wlazło

Reputation: 1155

If you just want to round the numbers, this should work fine:

from math import floor, log10
df_input["Consumption"] = df_input["Consumption"].apply(lambda x: round(x, max(1, - int(floor(log10(abs(x)))))))
df_input["Consumption"]
#0    31.2000
#1     0.4000
#2     0.2000
#3     6.5000
#4     0.0100
#5     0.0200
#6     0.0005
#7     0.1000

You can deal with trailing zeros via formatting, fe:

format_mapping = {"Consumption": "{:,g}"}
df_input.style.format(format_mapping)
#   Cateogry    Consumption
#0  Category 1  31.2
#1  Category 1  0.4
#2  Category 2  0.2
#3  Category 2  6.5
#4  Category 3  0.01
#5  Category 3  0.02
#6  Category 4  0.0005
#7  Category 5  0.1

Upvotes: 1

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