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Python: Pandas Lesson 6
Learning : Panda Lesson 6
Subject: Pass variable to df
In this post we will cover some commands that we will re-use in a coming post were we will start to develop a small system/app to do full managing of our zoo file. currently i am putting the BluePrint of the app, basically the menu will have these functions:
The Menu: [load, view, add-edit-delete, sort, missing data, save to csv …], so lets start..
If we want to add new row to our dataframe, first we need to know our columns name. In our case data file zoo here is the column we have:
( animal, id, water_need, supervisor, cage_no, years ), at this point we will do this as static variable, but in coming lesson we will use an interactive sample.
So, we will write a dictionary that hold our new_row and append it to the dataframe.
Add new row to the datafram
new_row={‘animal’:’Koala’,’id’:5555,’water_need’:99,’supervisor’:’na’,’cage_no’:55,’years’:10}
df=df.append([new_row])
print(‘\n\n The df after adding one new row.\n’,df)
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You can see that there is a problem here, the id of our new row was entered manually (in this example) but we need this to be automatic and to do so we must first get the max value in the id column, add 1 to it then use it for the new entry. So we need to add this code:
next_id=df[‘id’].max() + 1
new_row={‘animal’:’koala’,’id’:next_id,’water_need’:99,’supervisor’:’na’,’cage_no’:55,’years’:10}
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To delete a row, we simply re-define the df without that row we want to delete. Say we want to delete the row that has id = 1020. The id is a primary key in our data-set and there is no duplicated numbers in id column so we can use it to identify a specific row. I assume that we know that we read the datafram and we want to delete the row id number 1020, here is the code:
Delete the row with id = 1020
df=df[df.id !=1020]
print(‘\n\n df after deleting row id:1020\n’,df)
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At the first paragraph i was talking about writing an app that fully manage the zoo file, so if the user want to read the rows based on a particular selection like : what are the animals in the cages number 2,5 and 8. Here is the code :
Animals in cage no 2,5 and 8
cage_arr=[2,5,8]
print(‘\n\n Animals in cages no.’,cage_arr,’\n’,df.loc[df[‘cage_no’].isin(cage_arr)])
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