put two columns from two different datasets together into one column
Question:
I have two dataframes
df1
name
Elias
David
Simon
Manuel
and a second df2
name
Gabriel
Brian
Simona
Danielle
Dilara
Martin
David
Simon
I one to put them into one column
I expecting an output like these:
name
Elias
David
Simon
Manuel
Gabriel
Brian
Simona
Danielle
Dilara
Martin
where every name occur once, so remove also duplicates.
i tried these
frames = [df1,df2]
but these gave me something different
Answers:
**here we are creating two data frame by using pd.Series **
df1 = pd.Series(['a', 'b'])
df2 = pd.Series(['c', 'd'])
and using pd.concat we concatenate df1 dataframe firstly with df2 dataframe
pd.concat([df1, df2])
as you can see the output df1 show firstly and lastely the df2 :
0 a
1 b
0 c
1 d
note:
you can concatenate multiple dataframe [df1, df2,….,dfn]
Assuming the columns names are ‘A’ and ‘B’:
df3 = pd.concat([df1['A'], df2['B']], axis = 0).drop_duplicates().reset_index(drop=True)
You can use the pandas.concat() function to merge two columns from two different datasets into one column. Here’s an example of how you can do this:
# Select the columns you want to merge
col1 = df1['name']
col2 = df2['name']
merged_column = pd.concat([col1, col2])
merged_df = pd.DataFrame({'name': merged_column}).reset_index(drop=True)
I have two dataframes
df1
| name |
|---|
| Elias |
| David |
| Simon |
| Manuel |
and a second df2
| name |
|---|
| Gabriel |
| Brian |
| Simona |
| Danielle |
| Dilara |
| Martin |
| David |
| Simon |
I one to put them into one column
I expecting an output like these:
| name |
|---|
| Elias |
| David |
| Simon |
| Manuel |
| Gabriel |
| Brian |
| Simona |
| Danielle |
| Dilara |
| Martin |
where every name occur once, so remove also duplicates.
i tried these
frames = [df1,df2]
but these gave me something different
**here we are creating two data frame by using pd.Series **
df1 = pd.Series(['a', 'b'])
df2 = pd.Series(['c', 'd'])
and using pd.concat we concatenate df1 dataframe firstly with df2 dataframe
pd.concat([df1, df2])
as you can see the output df1 show firstly and lastely the df2 :
0 a
1 b
0 c
1 d
note:
you can concatenate multiple dataframe [df1, df2,….,dfn]
Assuming the columns names are ‘A’ and ‘B’:
df3 = pd.concat([df1['A'], df2['B']], axis = 0).drop_duplicates().reset_index(drop=True)
You can use the pandas.concat() function to merge two columns from two different datasets into one column. Here’s an example of how you can do this:
# Select the columns you want to merge
col1 = df1['name']
col2 = df2['name']
merged_column = pd.concat([col1, col2])
merged_df = pd.DataFrame({'name': merged_column}).reset_index(drop=True)