In this jupyter notebook, I have built some visualizations from Stocks dataset.
I have used Matplotlib package for creating visualizations - line plots, and histograms.
Stocks dataset is available in this repository. (Here)
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Importing the required libraries
- pandas : pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with structured (tabular, multidimensional, potentially heterogeneous) and time series data both easy and intuitive.
- Matplotlib : Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. It is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.
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Importing and Loading the dataset
- Stocks data (of 2 Companies: Company-1 and Company-2)
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Exploratory Data Analysis
df.shape-- Return a tuple representing the dimensionality of the DataFrame.df.head()-- Return the first n rows. This function returns the first n rows for the object based on position. (default n=5)df.info()-- Print a concise summary of a DataFrame. This method prints information about a DataFrame including the index dtype and columns, non-null values and memory usagedf.describe()-- Generate descriptive statistics. It is used to view some basic statistical details like percentile, mean, std etc. of a data frame or a series of numeric values.df.isna().sum()-- Count missing values for each column of the dataframe.
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Data Visualizations
df.plot()-- Make plots of Series or DataFrame. default - Line plot/ graph.- Plotting Stock Prices of Company-1 vs Days (Line plot)
- Plotting Stock Prices of Company-2 vs Days (Line plot)
- Plotting both companies Stock Prices on same plot (Adding 2 lines on the same plot)
- Adding Labels (legend function)
- Different Linestyles and Colors
- Adding axis labels (x-label, y-label) and title
- Additional Line on the plot (showing mean)
- Layering histograms on the same plot
- Changing transpareny of histograms (alpha)