Manipulation of Pandas in Foundation of Data Science

 Define Pandas

        Pandas is an powerful library in  Python Programming library. It used to create multi dimensional structured data like 2D structured data its represent rows and columns like table format.

Operation in Pandas

1. Create one dimensional array
2. Loading Data
3. Exploring Data
4. Data cleaning and preprocessing
5. Data Transformation
6. Merging and Joining Data
7. Visualization

1.Create the One dimensional array

One dimensional array

        One dimensional array is used to hold the data in any data type like [ string, integers, float, etc]

Example

Two dimensional array

       Two dimensional array is used to hold the data in any data type like a row and column in table format

Example

 

2.Loading Data

        A pandas can used to read the any file format like CSV, Excel, JSON etc

3.Exploring Data

        Once the data can be load into the data frame , You may be inscept the content and structure.

df.describe ()

        It provide the max, min, mean operation

df.head()

        It return first five elements

df.tail()

        It return last five elements

4.Data cleaning and Preprocessing

df.isnull()

      This function can return the boolean dataframe

dropna()

        It used to remove the row and columns missing value

fillna()

        This function is used to missing value they can be assign random value to the null position

5.Data Transformation

1. df.sort_values()

        It used to sorting the elements in ascending or descending order.

6.Merging and Joining Data

concat()

        This function is used to concatination to vertical and horizontal in table row =0, columns=1

merge()

        This function can be used to merge the row and column in tables

7.Visualization 

        Pandas integrates well with matplotlib and other plotting libraries for simple data visualization.

Example

        Line graph, Bar plot, Histogram