Indexing and Selecting Data with Pandas
Indexing in Pandas :
Indexing in pandas means simply selecting particular rows and columns of data from a DataFrame. Indexing could mean selecting all the rows and some of the columns, some of the rows and all of the columns, or some of each of the rows and columns. Indexing can also be known as Subset Selection.
Let’s see some example of indexing in Pandas. In this article, we are using “ nba.csv ” file to download the CSV, click here.
Selecting some rows and some columns
Let’s take a DataFrame with some fake data, now we perform indexing on this DataFrame. In this, we are selecting some rows and some columns from a DataFrame. Dataframe with dataset.
Suppose we want to select columns Age , College and Salary for only rows with a labels Amir Johnson and Terry Rozier 
Our final DataFrame would look like this:
Selecting some rows and all columns
Let’s say we want to select row Amir Jhonson , Terry Rozier and John Holland with all columns in a dataframe.
Our final DataFrame would look like this:
Selecting some columns and all rows
Let’s say we want to select columns Age, Height and Salary with all rows in a dataframe.
Our final DataFrame would look like this:
Pandas Indexing using [ ] , .loc[] , .iloc[ ] , .ix[ ]
There are a lot of ways to pull the elements, rows, and columns from a DataFrame. There are some indexing method in Pandas which help in getting an element from a DataFrame. These indexing methods appear very similar but behave very differently. Pandas support four types of Multi-axes indexing they are:
- Dataframe.[ ] ; This function also known as indexing operator
- Dataframe.loc[ ] : This function is used for labels.
- Dataframe.iloc[ ] : This function is used for positions or integer based
- Dataframe.ix[] : This function is used for both label and integer based
Collectively, they are called the indexers. These are by far the most common ways to index data. These are four function which help in getting the elements, rows, and columns from a DataFrame.
Indexing a Dataframe using indexing operator [] :
Indexing operator is used to refer to the square brackets following an object. The .loc and .iloc indexers also use the indexing operator to make selections. In this indexing operator to refer to df[].
Selecting a single columns
In order to select a single column, we simply put the name of the column in-between the brackets