Concatenating Strings and Items from a Pandas Data Frame-CodePudding

I have the following dframe and attempted code below.

import pandas as pd
dframe = pd.DataFrame({
        
            'A' : [1,2,3],
            'B' : ['Guitar', 'Piccolo', 'Sax']
        })
    
dframe

for item in dframe:
    print(f"{"Mary's favorite number is"}{dframe[0]}{"and her favorite instrument is"}{dframe[1]}")

The expected output is a formatted string for each line of the code indicating "Mary's favorite letter is 1 and her favorite instrument is Guitar", "Mary's favorite letter is 2 and her favorite instrument is Piccolo", etc.

However, the code does not seem to produce these results.

CodePudding user response：

You can use string concatenation. You have to convert column 'A' to string before:

out = "Mary's favorite number is "   dframe['A'].astype(str)   " and her favorite instrument is "   dframe['B']
print(*out, sep='\n')

# Output
Mary's favorite number is 1 and her favorite instrument is Guitar
Mary's favorite number is 2 and her favorite instrument is Piccolo
Mary's favorite number is 3 and her favorite instrument is Sax

Update: to convert out series to a dataframe, use to_frame:

out = out.to_frame('colname')
print(out)

# Output
                                             colname
0  Mary's favorite number is 1 and her favorite i...
1  Mary's favorite number is 2 and her favorite i...
2  Mary's favorite number is 3 and her favorite i...

CodePudding user response：

import pandas as pd
df = pd.DataFrame({
        
            'A' : [1,2,3],
            'B' : ['Guitar', 'Piccolo', 'Sax']
        })
    
for index, row in df.iterrows():
    print(f"Mary's favorite number is {df.A.iloc[index]} and her favorite instrument is {df.B.iloc[index]}")

output

CodePudding user response：

Here's something that works:

df["Sentence"] = df.apply(lambda row: f"Mary's favorite number is {row.A} and her favorite instrument is {row.B}", axis=1)

for sentence in df["Sentence"]:
    print(sentence)

Output:

Mary's favorite number is 1 and her favorite instrument is Guitar
Mary's favorite number is 2 and her favorite instrument is Piccolo
Mary's favorite number is 3 and her favorite instrument is Sax

You could get fancier:

def sentence_maker(name, possessive_pronoun, number, instrument):
    return f"{name}'s favorite number is {number} and {possessive_pronoun} favorite instrument is {instrument}"


for sentence in df.apply(lambda row: sentence_maker("Leela", "their", row.A, row.B), axis=1):
    print(sentence)

Output:

Leela's favorite number is 1 and their favorite instrument is Guitar
Leela's favorite number is 2 and their favorite instrument is Piccolo
Leela's favorite number is 3 and their favorite instrument is Sax