Python

Coming Soon...

Comments

Post a Comment

Popular posts from this blog

DVB Q&A

Image
- Headend workflow including transmission MUX - A2B, Harmonic,Tandburg Encoder - Harmonic, Tandburg EN8030 IRD - Tandburg RX-1290 STB - Kaon Middleware - Any SMS intergrated with VCAS OMI - EMM and ECM persists in which PSI table? EMM in CAT ECM in PMT - How DVB works? - Why simulcrypt is used because of multiple conditional access systems can be used at the same time which saves bandwidth. - Architecture of STB? Transmission Parameters given to tune the channels: Downlink Frequency Polarization Symbol rate - What is the use of STB middleware Parsing and version monitoring of SI/PSI tables Support for full & manual scan and detection of new channels Three lists maintained: one each for TV, radio and data services Middleware with caching methods (e.g., EPG buffer manager) helping to minimize memory consumption Maintaining of system time by parsing TDT/TOT tables - MPEG functional diagram - TS Packet Size of pack...
Read more

Comprehensive guide to Matplotlib

Image
=> Simple plot with 2 axis from matplotlib import pyplot as plt age_x = [25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35] dev_y = [38496, 42000, 46752, 49320, 53200,          56000, 62316, 64928, 67317, 68748, 73752] plt.plot(age_x, dev_y) plt.show() => Simple plot with 2 axis with xlabel, ylabel and title from matplotlib import pyplot as plt age_x = [25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35] dev_y = [38496, 42000, 46752, 49320, 53200,          56000, 62316, 64928, 67317, 68748, 73752] plt.plot(age_x, dev_y) plt.xlabel("Age") plt.ylabel("Median Salary (USD)") plt.title("Median Dev Salary (USD) by Age") plt.show() => Plot multi-dimentional data from matplotlib import pyplot as plt age_x = [25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35] dev_y = [38496, 42000, 46752, 49320, 53200,          56000, 62316, 64928, 67317, 68748, 73752] plt.plot(age_x, dev_y) py_dev_y = [45372, 48...
Read more