Pandas variable rounding of column
>>> print(df)
item value1
0 a 1.121
1 a 1.510
2 a 0.110
3 b 3.322
4 b 4.811
5 c 5.841
This is my dummy pandas df.
Below is how I truncate/round my column value1.
decimals = 2
df['value1'] = df['value1'].apply(lambda x: round(x, decimals))
>>> print(df)
item value1
0 a 1.12
1 a 1.51
2 a 0.11
3 b 3.32
4 b 4.81
5 c 5.84
This truncate all the two column to two decimal point after decimal. Is it possible to have variable rounding w dictionary. So in below we see 'a' = two places post decimal, 'b': 3 post decimal....default(value not convered....default to 2). My expected df below. Not sure if this is possible. (More of thought experimentation)
dec_dict = {'a' : 2, 'b': 3, 'l':3, 'default': 2}
>>> print(df)
item value1
0 a 1.12
1 a 1.51
2 a 0.11
3 b 3.322
4 b 4.811
5 c 5.84
Solution 1:
Given the fact that trailing zeros are not significant, the best approach should be:
dec_dict = {'a' : 2, 'b': 3, 'l':3, 'default': 2}
df['value1'] = (df.groupby('item')['value1']
.apply(lambda g: g.round(dec_dict.get(g.name, dec_dict['default']))
)
output:
item value1
0 a 1.120
1 a 1.510
2 a 0.110
3 b 3.322
4 b 4.811
5 c 5.840