How to add values to a Pandas Dataframe using a nested for loop?

Question

I have two data frames containing float values.

The first one is a 1 column data frame that contains positions.
The second one is a matrix of ncol equal to the number of IDs and nrows equal to the nrow of the first data frame.

The idea is to create a new data frame of the same size as the second one. It needs to contain an equation between each value of the 1st data frame and each value for each column of the second one. The idea is that it will iterate over each row for one column before passing to the next one.

The ecuation would be something like df1 * df2 / len(df1)+1 Example data:

df1 = pd.DataFrame([10,20,30,40,50,60], columns=['POS'])
df2 = pd.DataFrame({"ID1" : [0,2,4,6,8,10] , "ID2" :[1,3,5,7,9,11]})
final = pd.DataFrame({"ID1" : [0, 5.714285714, 17.14285714, 34.28571429, 57.14285714, 85.71428571] , "ID2" :[1.428571429, 8.571428571, 21.42857143, 40, 64.28571429, 94.28571429]})

I think the the nested loop would be something like this, but I still can't get theanswer right. What I'm missing?

final = pd.DataFrame([])
for i in list(range(0,len(df1))):
          for j in list(range(0,len(df2))):
                        final.append(df2.iloc[i,j] * df1[0][i] / len(df1)+1)

In R the answer is this:

for (i in 1:nrow(df1)){
  for (j in 1:ncol(df2)){
    final[i,j] <- (df2[i,j] * df1[i,1]) / nrow(df1)+1
  }
}

Please post some sample data. There is better ways of doing this. — mcsoini
– mcsoini, Commented Jan 14, 2023 at 22:00

Timeless · Accepted Answer · 2023-01-15 09:52:42Z

2

In a Pandorable way, you can do it with pandas.DataFrame.squeeze and pandas.DataFrame.mul :

result = df2.mul(df1.squeeze(), axis=0).div(len(df1)+1)

Output :

print(result)

         ID1        ID2
0   0.000000   1.428571
1   5.714286   8.571429
2  17.142857  21.428571
3  34.285714  40.000000
4  57.142857  64.285714
5  85.714286  94.285714

edited Jan 15, 2023 at 9:52

answered Jan 14, 2023 at 22:15

Timeless

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2 Comments

Paulo Cecco Over a year ago

It gave me the result, but I was wondering if there is a way to iterate over each value, because this answer works well when it's a simple multiplication, but what about if you have to do an extra calculation? Let's say df1 * df2 / (len(df1) * df2)

Timeless Over a year ago

This is not what says the result dataframe you shared. Can you update it accordingly ?

RomanPerekhrest · Accepted Answer · 2023-01-14 22:44:11Z

0

Explicitly for df1 * df2 / (len(df1) * df2) calculation:

pd.DataFrame((df1.values * df2.values) / (len(df1) * df2.values), columns=df2.columns)

         ID1        ID2
0        NaN   1.666667
1   3.333333   3.333333
2   5.000000   5.000000
3   6.666667   6.666667
4   8.333333   8.333333
5  10.000000  10.000000

answered Jan 14, 2023 at 22:44

RomanPerekhrest

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