[FIXED] Make event N rows of a Dataframe into a column Aggregated by date in pandas?

Issue

I have a dataframe like this

title	timestamp
String one	2016-12-02
String two	2016-12-02
...	...
String twenty-five	2016-12-02
String twenty-six	2016-12-03
String twenty-seven	2016-12-03
...	...
String fifty	2016-12-03

And I want to change it into a dataframe like this

timestamp	top 1	top 2	...	top 25
2016-12-02	String one	String two	...	String twenty-five
2016-12-03	String twenty-six	String twenty-seven	...	String fifty

Basically i'm trying to make every 25 rows to become columns consecutively and i'm not sure how big the dataset will be but it's going to have atleast a few years as date.

I know i'm suppose to use reshape or melt but I've been unsuccessful till now. Any help in how to tackle this?

Solution

Here is an idea, where column A is your dates and column D is your strings

df = pd.DataFrame({"A": ["foo", "foo", "foo", "foo", "foo",
                         "bar", "bar", "bar", "bar"],
                   "D": ["1", "this text", "text other", "What", "migrate", "Data", "5", "6 saucisses", "Okayy"]
                   })
# Join with a character very specific, that you won't find in your rows
# Something like '#######'
df = df.pivot_table(values='D', index=['A'], aggfunc=lambda x: '#'.join(x))

df_test = df.D.str.split(pat='#',expand=True,)

Answered By - Benoit Drogou