String Concatenation of Two Pandas Columns

Concat two columns values of dataframe

Since Age is an int column, you need to cast it to str using astype

In [2511]: df['Name'] = df["Age"].astype(str) + " " + df["Name"]

In [2511]: df['Name']
Out[2511]: 
0      10 Alex
1       12 Bob
2    13 Clarke

How to do column string concatenation including space separator in Pandas dataframe?

You can also add separator between columns:

df['alltext'] = df['txt1']  + ' ' + df['txt2'] + ' ' + df['txt3']

Or filter by DataFrame.filter only columns with txt in column name and use join per rows with apply:

df['alltext'] = df.filter(like='txt').apply(' '.join, axis=1)

Or filter only object columns by DataFrame.select_dtypes - most times a Series with a dtype of object is going to be a string - but it could be any Python object:

df['alltext'] = df.select_dtypes('object').apply(' '.join, axis=1)

Or select columns by positions - all columns without first by DataFrame.iloc:

df['alltext'] = df.iloc[:, 1:].apply(' '.join, axis=1)

Thank you, @Jon Clements for solution for better matching columns names with txt and numeric:

df['alltext'] = df.filter(regex=r'^txt\d+$').apply(' '.join, axis=1)

How to string-concatenate multiple string columns in pandas?

Use agg with append:

df = df.append(df.agg(' '.join), ignore_index=True)
df

              string1                  string2
0               Hello              This is Sam
1        how are you?              from Canada
2  Hello how are you?  This is Sam from Canada

Concatenate string and Pandas field in an apply lambda

I guess you want to check if values in one column end with another. You can achieve that by calling apply on multiple columns.
Provided that df is:

   Field B Field A
0  1/a.pdf       a
1  2/b.pdf       b
2  3/b.pdf       c
3  4/c.pdf       d

You can apply some lambda along the axis 1

df[['Field A', 'Field B']].apply(lambda item: item['Field A'].endswith(item['Field B'] + '.pdf'), axis=1)

Output:

0     True
1     True
2    False
3    False
dtype: bool

Edit: To have result in the form of dataframe, you can cast it like below

result = df[['Field A', 'Field B']].apply(lambda item: item['Field A'].endswith(item['Field B'] + '.pdf'), axis=1)
result = pd.DataFrame(result) # You can add your optional params, column names for example

Concatenate two columns excepting strings from a list_pandas

Given:

      words             sentence
0   unknown  This is a new paint
1     brown   This is a new item
2  for sale   The product is new

Doing:

restricted = ['not present', 'for sale', 'unknown']
mask = df.words.str.contains('|'.join(restricted))
df['output'] = df.sentence.where(mask, df.sentence + ' ' + df.words)
print(df)

Output:

      words             sentence                    output
0   unknown  This is a new paint       This is a new paint
1     brown   This is a new item  This is a new item brown
2  for sale   The product is new        The product is new

How to concatenate two columns consisting of text values i.e, string in Jupyter Lab?

Try this:

import pandas as pd

#create dataframe
df = pd.DataFrame()
df['col1'] = ['a','b','c']
df['col2'] = ['d','e','f']

#new column
df['new_col'] = df['col1'] + df['col2']

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