I want to take input in the form of lists and join them into strings. How I can store the output as a dataframe column?
The input X is a dataframe and the column name is des:
X['des'] =
[5, 13]
[L32MM, 4MM, 2]
[724027, 40]
[58, 60MM, 36MM, 0, 36, 3]
[8.5, 45MM]
[5.0MM, 44MM]
[10]
This is my code:
def clean_text():
for i in range(len(X)):
str1 = " "
print(str1.join(X['des'][i]))
m = clean_text
m()
And here is my output, but how I can make it as a dataframe?
5 13
L32MM 4MM 2
724027 40
58 60MM 36MM 0 36 3
8.5 45MM
5.0MM 44MM
10
CodePudding user response：
Note that iterating in pandas is an antipattern. Whenever possible, use DataFrame and Series methods to operate on entire columns at once.
Series.str.join (recommended)
X['joined'] = X['des'].str.join(' ')
Output:
des joined
0 [5, 13] 5 13
1 [L32MM, 4MM, 2] L32MM 4MM 2
2 [724027, 40] 724027 40
3 [58, 60MM, 36MM, 0, 36, 3] 58 60MM 36MM 0 36 3
4 [8.5, 45MM] 8.5 45MM
5 [5.0MM, 44MM] 5.0MM 44MM
6 [10] 10
Loop (not recommended)
Iterate the numpy values and assign using
DataFrame.loc:for i, des in enumerate(X['des'].to_numpy()): X.loc[i, 'loop'] = ' '.join(des)Or iterate via
DataFrame.itertuples:for row in X.itertuples(): X.loc[row.Index, 'itertuples'] = ' '.join(row.des)Or iterate via
DataFrame.iterrows:for i, row in X.iterrows(): X.loc[i, 'iterrows'] = ' '.join(row.des)
Output:
des loop itertuples iterrows
0 [5, 13] 5 13 5 13 5 13
1 [L32MM, 4MM, 2] L32MM 4MM 2 L32MM 4MM 2 L32MM 4MM 2
2 [724027, 40] 724027 40 724027 40 724027 40
3 [58, 60MM, 36MM, 0, 36, 3] 58 60MM 36MM 0 36 3 58 60MM 36MM 0 36 3 58 60MM 36MM 0 36 3
4 [8.5, 45MM] 8.5 45MM 8.5 45MM 8.5 45MM
5 [5.0MM, 44MM] 5.0MM 44MM 5.0MM 44MM 5.0MM 44MM
6 [10] 10 10 10