qwertypy 0.6.0

My personal python utilities library.

qwertypy

Python utilities library for financial utilities, data analysis, visualization and DSA.

Quick links

• Github
• PyPI
• Docs

Installation

pip install qwertypy

Upgrade

pip install --upgrade qwertypy

Usage

• Try on colab: Click here

qwertypy.greetings

import qwertypy.greetings as qpyGreetings

print(qpyGreetings.hello())

qwertypy.tickertape

qwertypy.tickertape.companies

import qwertypy.tickertape.companies as ttCompanies

topCompanies = ttCompanies.getTopCompanies()
print("TOP = ", len(topCompanies))
# print("ALL = ", len(ttCompanies.getAllCompanies()))

ttName = "reliance-industries-RELI"
companyInfo = ttCompanies.getCompanyInfo(ttName)
print(companyInfo)

qwertypy.tickertape.financials

import qwertypy.tickertape.financials as ttFinancials

ttName = "reliance-industries-RELI"
for statementType in ttFinancials.statementTypes:
    statement = ttFinancials.getStatement(ttName, statementType)
    print(statementType, type(statement))

ttName = "reliance-industries-RELI"
statementType = ttFinancials.statementTypes["income"]
statement = ttFinancials.getStatement(ttName, statementType)
yearsAndValues = ttFinancials.getYearsAndValues(statement, "incDps")
print(yearsAndValues)

qwertypy.data_analysis

qwertypy.data_analysis.regression

import qwertypy.data_analysis.regression as qpyRegression

xTrain = [1, 2, 3, 4, 5, 6]
yTrain = [2, 4, 6, 8, 10, 12]
model = qpyRegression.QpyLinearRegression(xTrain, yTrain)
model.train()
yPredict = model.getPrediction()
print("yPredict: ", yPredict)

xPredict2 = [10, 11]
yExpected = [20, 22]
yPredict2 = model.getPrediction(xPredict2)
print("yPredict2: ", yPredict2)

qwertypy.data_plots

qwertypy.data_plots.trend_plot

import random

import qwertypy.data_plots.trend_plot as qpyTrendPlot

xValues = [i for i in range(10)]
yValues = [random.randint(1, 10) for _ in range(10)]
xTicks = ["xTick" + str(i+1) for i in range(10)]
trendValues = list(yValues)
qpyTrendPlot.trendPlot(
    xValues, yValues,
    xTicks = xTicks,
    rotateXTicks = 90,
    xLabel = "xLabel",
    yLabel = "yLabel",
    plotTitle = "plotTitle",
    trendValues = trendValues,
    legends = ["trendLegend", "barLegend"],
    text = "text",
    textBackground = "red",
    watermark = "watermark",
    showValues = True,
    # saveToFile = "testImage.jpg"
)