Dealing with python library pandas and matplotlib | How became a data analyst?

Pandas is the most popular python library that is used for data analysis. It provides highly optimized performance with back-end source code is purely written in C or Python.


Way to analyse pandas in python:

  • Dataframe

  • Series

Pandas dataframes: Pandas DataFrame is two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). A Data frame is a two-dimensional data structure, i.e., data is aligned in a tabular fashion in rows and columns. Pandas DataFrame consists of three principal components, the data, rows, and columns.

Here we understand it easily by below some examples:

Select Columns


Importing csv file:

We import Contrib_data.csv by using read_csv().

Select column from csv file

Selecting row from csv file:


Selecting a single row from the csv file:


Data framing using loc and iloc:

Dataframe using iloc:


data.iloc[0] # first row of data frame (Aleshia Tomkiewicz)

- Note a Series data type output.

data.iloc[1] # second row of data frame (Evan Zigomalas)

data.iloc[-1] # last row of data frame (Mi Richan)# Columns:

data.iloc[:,0] # first column of data frame (first_name)

data.iloc[:,1] # second column of data frame (last_name)

data.iloc[:,-1] # last column of data frame (id)


Multiple row and column selections using iloc and DataFrame

data.iloc[0:5] # first five rows of dataframe

data.iloc[:, 0:2] # first two columns of data frame with all rows

data.iloc[[0,3,6,24], [0,5,6]] # 1st, 4th, 7th, 25th row + 1st 6th 7th columns.

data.iloc[0:5, 5:8] # first 5 rows and 5th, 6th, 7th columns of data frame

(county -> phone1).


Dataframe using loc:

The Pandas loc indexer can be used with DataFrames for two different use cases:

  • Selecting row by boolean

  • Selecting row by label

Select row by label:

Find all CAND_NAME whose name is WARREN,ELIZABETH




In next tutorial we discuss some complex example which is very useful for any Data Analyst.

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