how to convert normal dataframe to time series dataframe

Question

I have normal dataframe.

id  name    age city        date
1   Jane    43  London      2020-01-12
2   Jose    34  London      2020-01-12
3   Poul    53  Leed        2020-01-12
4   Mark    29  Manchester  2020-02-12
5   Zak     36  London      2020-02-12
6   Lin     75  Birmingham  2020-03-12
7   Word    55  York        2020-04-12
8   Gene    33  Leed        2020-04-12

I would like convert to time series dataframe, could you teach me how to do?

In real dataset, there are a lot of cities. I want it automatically generating table.

My expect time series is:

date        London  Leed    Manchester  Birmingham  York    
2020-01-12  2       1       0           0            0
2020-02-12  1       0       1           0            0
2020-03-12  0       0       0           1            0
2020-04-12  0       1       0           0            1

Answer 1

You can use pivot_table :

df.pivot_table(index='date', columns='city', aggfunc='size', fill_value=0)

city        Birmingham  Leed  London  Manchester  York
date
2020-01-12           0     1       2           0     0
2020-02-12           0     0       1           1     0
2020-03-12           1     0       0           0     0
2020-04-12           0     1       0           0     1

You can also use pd.crosstab(df.date, df.city)