CODEWITHSUNDEEP
pythonpandasdataframe
user11638578
user11638578

Reputation: 35

Concatenating string with each row in data frame and applying function to them?

I have a dataframe that contains all sort of data -- string,int and date object too.

I already have apiece of code (deal_value(val)) that identifies the type of val and makes it a string. I need to be able to apply that to all the cells in the dataframe I have right now.

After that, I need to concatenate the row value with the row name in the dataframe.

I looked at apply function for both of these but was unable to figure out how to use it in either case

Dataframe Examples:

     name    age    dob
0    A        10    20-Jun-1969

And I want the dataframe to be:

    name         age         dob
0    A name     10 age      20-Jun-1969 dob

My function deal_value would take each cell element and make them good to concatenate into a string, so ultimately I want it to be something like:

"A name, 10 age,20-Jun-1969 AND (row-2) AND (row-3)......."

Upvotes: 1

Views: 1234

Answers (2)

Kaies LAMIRI
Kaies LAMIRI

Reputation: 199

import pandas

df = pandas.DataFrame({'name': 'A', 'age': 10, 'date_of_birth': '20-Jun-1969'}, index=[0])

for col in list(df.columns): 
    df[col] = df[col].apply(lambda x: ' '.join([str(col), str(x)]))


df.head()

Output

    name     age        date_of_birth
0   name A   age 10     date_of_birth 20-Jun-1969

String Output : 


df_to_string = df.to_string(header=False,
                            index=False,
                            index_names=False).split('\n')
vals = [ ', '.join(element.lstrip().rstrip().split('  ')) for element in df_to_string]
vals_str = ' And '.join(vals)

print(vals_str)

Output: 

'name A, age 10, date_of_birth 20-Jun-1969 And name B,  age 5, date_of_birth 21-Jun-1969'

Upvotes: 1

anky
anky

Reputation: 75080

Seems like you just need:

df.astype(str).add(' '+df.columns)

     name     age              dob
0  A name  10 age  20-Jun-1969 dob

Upvotes: 1

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