Input-Output, Read, write data and Data Visualization in Python

1. BSP Lab 3
Input-Output, Read write data and
Data Visualization

2. Contents
• Pandas Library
• What is a Dataframe?
• Data Visualization
• Matplotlib
• Seaborn
– Line plot
– Histogram
– Scatter plot
– Bar plot
– Boxplot

3. Pandas Library
• Pandas is an open source library in Python. It
provides ready to use high-performance data
structures and data analysis tools.
• Pandas module runs on top of NumPy and it is
popularly used for data science and data
analytics.

4. DataFrame
• DataFrame is two-dimensional size-mutable,
potentially heterogeneous tabular data
structure with labeled axes (rows and columns)
Fig.1. Example of a DataFrame

5. Fig.2. Example code of a DataFrame Fig.3. Output of the
corresponding code

6. Data Visualization
• Data visualization is a field in data analysis
that deals with visual representation of data.
• It graphically plots data and is an effective way
to communicate inferences from data.
• Using data visualization, we can get a visual
summary of our data.
• Python offers several plotting libraries,
namely Matplotlib and Seaborn

7. Matplotlib
• Matplotlib is a python library used to create
2D graphs and plots by using python scripts.
• It has a module named pyplot which makes
things easy for plotting by providing feature to
control line styles, font properties, formatting
axes etc.
• It is used along with NumPy to provide an
environment that is an effective open source
alternative for MatLab.

8. Seaborn
• Seaborn is a Python data visualization library
based on matplotlib. It provides a high-level
interface for drawing attractive and
informative statistical graphics.

9. Plots to be done in the lab
• Line Plot
• Histogram
• Scatter Plot
• Boxplot
• Barplot
• ECG signal plot

10. Assignment Questions
Q1) Write a short note on: with code
Line plot
Histogram plot
Scatter plot
Boxplot
Q2) Explain the different methods to read and
write a .CSV file in python
Q3) Load “S1.csv file” & plot the ECG data
of each patient individually and in a single plot.