I have a csv file which i have converted in dataframe and input file looks like this:

```
    Date     Area    Input
4/5/2019    Forest  apple
4/5/2019    Forest  banana
4/5/2019    Forest  Lion
4/5/2019    Town    banana
4/6/2019    Town    dog
4/6/2019    Town    grapes
4/6/2019    Town    cat

```

I need an output like this which displays count of fruits and animals in seperate Fruits and Animals Columns based on Date and Area:

```
    Date    Area    Fruits  Animals
4/5/2019    Forest  2       1
4/5/2019    Town    1       0
4/6/2019    Forest  0       0
4/6/2019    Town    1       2

```

The code I have written:

```
1.Conversion of date format

date_final='2019-04-05'
data_to_analyse1['date'] = pd.to_datetime(data_to_analyse1['date'],format= 
'%Y-%m-%d')
data_to_analyse2= 
data_to_analyse1.loc[(data_to_analyse1['date']==date_final)]

2.To read Input column based on date and area:

for a in Area:
    intent_name=data_to_analyse2.loc[data_to_analyse2['Area'] ==  a]
    intent_list=list(intent_name['Input'])

3.Then to count entries in 'Input' column I am using count for each unique 
entry like this:

Intent_IsNull=intent_list.count('Intent_IsNull')
apple=intent_list.count('apple')
banana=intent_list.count('banana')
lion=intent_list.count('lion')
dog=intent_list.count('dog')
grapes=intent_list.count('grapes')
cat=intent_list.count('cat')

```

Requirement(what my code does not do):

```
I am able to make each columns seperately But I have not find 
a way here to put (apples,banana,grapes) in one column called 'Fruits' and 
(elephant,lion,cat,dog) in one column called 'Animals' as shown in output 
above

```

How it could be done in context of my code, any help is much appreciated