Writing output of a for loop to pandas data-frame

Question

How can I write an output of a for loop to pandas data-frame?

Input data is a list of data-frames (df_elements).

[                          seq  score    status
1652  TGGCTTCGATTTTGTTATCGATG  -0.22  negative
1277  GTACTGTGGAATCTCGGCAGGCT   4.87  negative
302   CCAAAGTCTCACTTGTTGAGAAC  -4.66  negative
1756  TGGCGGTGGTGGCGGCGCAGAGC   1.55  negative
5043  TGACGAAACATCTTATAAAGGAA   1.96  negative
3859  CAGAGCTCTTCAAACTTAAGAAC  -0.39  negative
1937  GTATGCTTGTGCTTCTCCAAAAA  -0.91  negative
2805  GGCCGGCCTGTGGTCGACGGGGA  -3.26  negative
3353                CCGATGGGC  -1.97  negative
5352  ACTTACTATTTACTGATCAGCAC   3.53  negative
5901  TTGAGGCTCTCCTTATCCAGATT   6.37  negative
5790  AAGGAAACGTGTAATGATAGGCG  -2.69  negative,                           seq  score    status
2197  CTTCCATTGAGCTGCTCCAGCAC  -0.97  negative
1336  CCAAATGCAACAATTCAAAGCCC  -0.44  negative
4825                CAATTTTGT  -6.44  negative
4991  ATACTGTTTGCTCACAAAAGGAG   2.15  negative
1652  TGGCTTCGATTTTGTTATCGATG  -0.22  negative
1964  ACCACTTTGTGGACGAATACGAC  -4.51  negative
4443  TTCCTCGTCTAGCCTTTCAGTGC   3.05  negative
4208  TGGCTGTGAACCCCTATCAGCTG   2.70  negative
212   CTGTCGTTTCAATGTTTAAGATA   6.43  negative
775                 GCTTTAAGT   0.06  negative
3899                GAGCAAAGC  -6.61  negative

I am trying to write the output of the below for loop to a data-frame. I tried by creating an empty list (data) and append row-wise output using data.append. I am getting an error like cannot concatenate object of type "";

The code is given below which print the output in the console:


cut_off = [0,1,2]

for co in cut_off:
    for df in df_elements:
        print co, "\t", str((df['score'] > co).sum())

The code should compare the cut_off value to the column score and print the total for each data-frame element, where the score is > than cut_off.

The output should look like this:

cutoff number
0   5  #for first dataframe element
0   5  #for second dataframe element

This is working to me. Are the elements of the list pandas Dataframes? Are you sure? — Billy Bonaros
– Billy Bonaros, Commented Dec 4, 2019 at 11:10
Also, if you are using python 3. don't forget to add parenthesis to print — Billy Bonaros
– Billy Bonaros, Commented Dec 4, 2019 at 11:13

Neo · Accepted Answer · 2019-12-04 11:09:28Z

5

# create empty lists for cutoff and number
cutoff_list = []
number_list = []

# loop through cutoff values and dataframes, to populate your lists
for co in cut_off:
    for df in df_elements:
        cutoff_list.append(co)
        number_list.append((df['score'] > co).sum())

# create dataframe from your lists
df = pd.DataFrame(list(zip(cutoff_list , number_list)), 
           columns =['cutoff', 'number']) 

# get your desired output
print(df)

answered Dec 4, 2019 at 11:09

Neo

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3 Comments

Neo Over a year ago

If this solution is the desired, please consider accepting it. In other case let me know how to improve it, cheers.

rshar Over a year ago

It worked perfectly!! Could you please explain this part to me? pd.DataFrame(list(zip(cutoff_list , number_list)), columns =['cutoff', 'number']). What does list and zip function do?

Neo Over a year ago

@ranusharma Zip is a generator that binds together items. I believe that to understand this you can run a toy example like this: a = [1,2] b = [3,4] c = [5,6] for item in zip(a, b, c): print(item) list(zip(a, b, c))

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