Convert Each Element Of Pandas Dataframe Into Dict

I am trying to add feature index to each element of pandas dataframe such that each element will be like column_number:feature_value. For example, if input is like this: co

Solution 1:

I used the following code to get my desired output format:

f_out = open('check_features.csv','w')
X = feature_matrix1.drop(['Disease'], axis=1)
Y = feature_matrix1['Disease'].tolist()
for i in tqdm(range(X.shape[0])):
    line = ''
    line += str(Y[i]) + '\t'for j inrange(X.shape[1]):
        line +=  str(j+1) + ':' + str(X.iloc[i,j]) + '\t'
    line += '\n'
    f_out.write(line)

f_out.close()

Solution 2:

First convert to string and use radd to get expect output:

>>>df.astype(str).radd([f'{i+1}:'for i inrange(len(df.columns))])

        col1    col2
row1  1:1.23  2:2.24
row2  1:0.42  2:5.52

Solution 3:

You can use df.columns.get_loc() to get the column integer location number (0-based) and then string concatenate with the column values for each column, as follows:

for col in df.columns:
    df[col] = str(df.columns.get_loc(col) + 1) + ':' + df[col].astype(str)

Result:

print(df)

        col1    col2
row1  1:1.23  2:2.24
row2  1:0.42  2:5.52

Solution 4:

It works

for c in df.columns:
    df[c] = df[c].apply(lambda x:f"{c[-1]}:{x}")

result

        col1    col2
row1  1:1.23  2:2.24
row2  1:0.42  2:5.52

Solution 5:

Short version In

[f"{i+1}:"for i inrange(df.shape[1])] + df.astype(str)

Out

        col1    col2
row1  1:1.23  2:2.24
row2  1:0.42  2:5.52