I have some function that takes a DataFrame and an integer as arguments:
func(df, int)
The function returns a new DataFrame, e.g.:
df2 = func(df,2)
I'd like to write a loop for integers 2-10, resulting in 9 DataFrames. If I do this manually it would look like this:
df2 = func(df,2)
df3 = func(df2,3)
df4 = func(df3,4)
df5 = func(df4,5)
df6 = func(df5,6)
df7 = func(df6,7)
df8 = func(df7,8)
df9 = func(df8,9)
df10 = func(df9,10)
Is there a way to write a loop that does this?
This type of thing is what lists are for.
data_frames = [df]
for i in range(2, 11):
data_frames.append(func(data_frames[-1], i))
It's a sign of brittle code when you see variable names like df1, df2, df3, etc. Use lists when you have a sequence of related objects to build.
To clarify, this data_frames is a list of DataFrames that can be concatenated with data_frames = pd.concat(data_frames, sort=False), resulting in one DataFrame that combines the original df with everything that results from the loop, correct?
Yup, that's right. If your goal is one final data frame, you can concatenate the entire list at the end to combine the information into a single frame.
Do you mind explaining why data_frames[-1], which takes the last item of the list, returns a DataFrame? Not clear on this.
Because as you're building the list, at all times each entry is a data frame. data_frames[-1] evaluates to the last element in the list, which in this case, is the data frame you most recently appended.
data_frames is a list of DataFrames that can be concatenated with data_frames = pd.concat(data_frames, sort=False), resulting in one DataFrame that combines the original df with everything that results from the loop, correct?data_frames[-1], which takes the last item of the list, returns a DataFrame? Not clear on this.
You may try using itertools.accumulate as follows:
sample data
df:
a b c
0 75 18 17
1 48 56 3
import itertools
def func(x, y):
return x + y
dfs = list(itertools.accumulate([df] + list(range(2, 11)), func))
[ a b c
0 75 18 17
1 48 56 3, a b c
0 77 20 19
1 50 58 5, a b c
0 80 23 22
1 53 61 8, a b c
0 84 27 26
1 57 65 12, a b c
0 89 32 31
1 62 70 17, a b c
0 95 38 37
1 68 76 23, a b c
0 102 45 44
1 75 83 30, a b c
0 110 53 52
1 83 91 38, a b c
0 119 62 61
1 92 100 47, a b c
0 129 72 71
1 102 110 57]
dfs is the list of result dataframes where each one is the adding of 2 - 10 to the previous result
If you want concat them all into one dataframe, Use pd.concat
pd.concat(dfs)
Out[29]:
a b c
0 75 18 17
1 48 56 3
0 77 20 19
1 50 58 5
0 80 23 22
1 53 61 8
0 84 27 26
1 57 65 12
0 89 32 31
1 62 70 17
0 95 38 37
1 68 76 23
0 102 45 44
1 75 83 30
0 110 53 52
1 83 91 38
0 119 62 61
1 92 100 47
0 129 72 71
1 102 110 57
You can use exec with a formatted string:
for i in range(2, 11):
exec("df{0} = func(df{1}, {0})".format(i, i - 1 if i > 2 else ''))
