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Let's load data for more options Using a Pandas DataFrame You can see that the pd.read_csv() method returns a Pandas dataframe object. If you want to use a particular column, you could use the as_matrix() method Each row in the matrix is an object in the pandas dataframe. You can access the object by indexing it. In this case, you use the column you want as your index and access it via the column name. You can also use indexing for the data in each row You can get the names of the columns using the columns() method, which returns an iterable of the column names in the dataframe. Getting at the data You can access the data using the loc[] method If you need to access only one item, you can use iloc[] If you need to access an item from an index, you can use get_loc[] I would also like to add that Pandas is a very powerful library and definitely worth checking out. It is not just useful for analyzing data, but also for parsing CSV files and reading in data from web sources. If you are at all interested in learning more about how to use it, check out Pandas Cheat Sheet. A: As I understood, you want to know how to get at the data in each cell in a Pandas dataframe. So, I will assume that you know how to get at each cell in the dataframe with 'indexing'. Anyway, you can get at the data in a dataframe cell like this (this is obviously not best practice and there are good reasons for not doing this, but it works): df.get_value(index=indexname, column=columnname, default=defaultvalue) So, for example, to get at the first data in each cell in the first row of your dataframe, you would do: df.get_value(index='0', column='col1') But the best way to get at the data in a dataframe cell is to just access the data in the first row of the dataframe like this: df.iloc[0,0] Or to access the first data in the first column of the first row of the dataframe: df.iloc[0,0].col1 I

 

 

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