df.append() not adding rows to dataframe in pandas

Question

I'm using a very simple piece of code and initializing a pandas dataframe with a single row and then adding other rows from a list named itemsets_dct and then appending them to the dataframe, using the following code:

finalResults = pd.DataFrame({'Concept1': itemsets_dct[0][0][0], 'Concept2': itemsets_dct[0][0][1], 'Concept3': itemsets_dct[0][0][2], 'Concept4': itemsets_dct[0][0][3], 'Count': itemsets_dct[0][1]}, index=[0])
for i in range(1,len(itemsets_dct)):
    tempResult = pd.DataFrame({'Concept1': itemsets_dct[i][0][0], 'Concept2': itemsets_dct[i][0][1], 'Concept3': itemsets_dct[i][0][2], 'Concept4': itemsets_dct[i][0][3], 'Count': itemsets_dct[i][1]}, index=[i])
    finalResults.append(tempResult)

when I run this code, it executes without any errors, but the finalResults variable only has 1 row, the row that I initialized.

Why is the code not appending rows to the dataframe?

append is not an inplace operation, so you need to reassign. i.e. finalResults = finalResults.append(tempResult). — root
– root, Commented Nov 1, 2016 at 18:15
Can't imagine the sdolution would be so simple. Thanks a lot. — Patthebug
– Patthebug, Commented Nov 1, 2016 at 18:16
Also show the contents of itemsets_dct as there may be a preferred way to do this in one call instead of iteratively in loop. — Parfait
– Parfait, Commented Nov 1, 2016 at 21:05

Parfait · Accepted Answer · 2016-11-01 21:34:15Z

1

Consider not using an iterative for loop append but building a list of dictionaries that you then cast into a dataframe all in one call. Below hopefully recreates the outer structure of your nested list:

itemsets_dct = [[['check1', 'check2', 'check3', 'check4'], 3],
                [['check11', 'check22', 'check33', 'check44'], 3],
                [['check111', 'check222', 'check333', 'check444'], 3]]

dfDict = [{'Concept1': i[0][0],
           'Concept2': i[0][1],
           'Concept3': i[0][2],
           'Concept4': i[0][3],
           'Count': i[1]} for i in itemsets_dct]

finalresults = pd.DataFrame(dfDict)
print(finalresults)

#    Concept1  Concept2  Concept3  Concept4  Count
# 0    check1    check2    check3    check4      3
# 1   check11   check22   check33   check44      3
# 2  check111  check222  check333  check444      3

answered Nov 1, 2016 at 21:34

Parfait

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