Btukfyl

I have a dataset sort of like the following in an excel file named data.xlsx

Building           name    salary

00Apple032           Bob     50000

00Apple032           James   30000

0Bean032            James   30000

0Soda987            Alex    0

0Bean032            Bryon   32000

ive created two data frames from the data.

df = pd.read_excel('data.xlsx', sheet_name='Sheet1, dtype=str)



grouped_df = pd.read_excel('data.xlsx', sheet_name='Sheet1, dtype=str)

grouped = grouped_df.groupby("Building")[["Building", "name", "salary']]

Before I go on here .. the reason why I created the original df as well as grouped_df (which are both data frames) ... I'm not certain that applying the grouping function to the original df and assigning that to a new variable on a single line of code (like the below line) would somehow mess with the original data and cause trouble down the line. That may be inaccurate.

grouped = df.groupby("Builing")[["Building", "name", "salary']]

Anywho. This grouped dataframe is not like a normal dataframe to my knowledge. The type is listed as

pandas.core.groupby.groupby.DataFrameGroupBy

On the normal dataframe that is not grouped I can do something like this:

x = input("search for: ")

df[df['Building'].str.contains(x)]]

however on a grouped dataframe this doesn't work.

My problem that im trying to work around is this - i need to permit the ability to search in this grouped data frame to print the groups, but the user doesn't know the precise or exact group name. Was it Apples im searching for? Or 00Apples .. you can see the problem.

While i can query the data with this:

grouped.get_group('00Apples032')

I don't have a way to offer someone the ability to search for that group via something like a str.contains.

What I have tried

grouped[grouped["Building"].str.contains("Apples")]

ERROR

exception: Columns already selected  

Assuming, you grouped your original dataframe on Building:

grouped = df.groupby("Building")

This creates a groupby object. You can loop over this object like below:

for key, value in grouped:

    print(key, value)

    ## Do your stuff here



00Apple032

     Building   name  salary

0  00Apple032    Bob   50000

1  00Apple032  James   30000

0Bean032

   Building   name  salary

2  0Bean032  James   30000

4  0Bean032  Bryon   32000

0Soda987

   Building  name  salary

3  0Soda987  Alex       0

In this, the key will have unique Buidling names like 00Apple032,0Bean032, etc as shown above. And, value will have the actual rows for each key.

So, you can treat each (key,value) like one dataframe and check if each dataframe has x or not like this:

for key, value in grouped:

    print(value[value['Building'].str.contains(x)])

    ## do more stuff

Let me know if this helps.