I desire either something like this:
Column A Column B Column C
100 200 No Value
400 No value 500
When CSV files lookes like this:
CSV File 1
Column A Column B
100 200
CSV File 2
Column A Column C
400 500
I have started importing with something similar to this:
file_list = [CSV File 1, CSV File 2]
#Empty list
list = []
for n in range(len(file_list)):
g = pd.read_csv(file_list[n], delimiter = "\;")
list.append(g)
#Data frame for all the values
real_list = pd.concat(list, axis = 1)
This gives the result of something similar to this.
Column A Column B Column A Column B
100 200 400 500
Which is wrong.
Any ideas are much appreciated =)
Just perform an outer merge
:
In [8]:
df.merge(df1, how='outer')
Out[8]:
Column A Column B Column C
0 100 200 NaN
1 400 NaN 500
The reason you get that result when using concat
is that you are concatenating column-wise and it's aligning on the common index values
The technical post webpages of this site follow the CC BY-SA 4.0 protocol. If you need to reprint, please indicate the site URL or the original address.Any question please contact:yoyou2525@163.com.