some simple python codes for biology
Summary Day 1 - Why Python Introduction to Google Colab Data types - numeric - int, float, complex and string datatype Basic mathematical operations The syntax for input throuh the terminal Any input taken through the trminal is by default a string command - print(), type(), input(), int(), float(), str()
Summary Day 2 - String data type and 0 indexing subsetting a string, number of characters in a string string methods - upper, lower, swap, title, count Sequence composition
Summary Day 3 Iteration Genratinga series of numbers, table of a given number etc. Iteration through a string Composition of DNA or protein by iteration - giving the count statement only once
Summary Day 4 - Data structures List and list modifications - append, delete, remove, insert, pop Tuples Dictionaries Converting dictionaries to dataframes
Summary Day 5 - Python libraries -Pandas for data wrangling Dataframes filter, sort, select, groupby, group summary, creating and adding new columns with Pandas
Summary Day 6 andDat 7 - Data Visualization Matplotlib - base library in Python for data visualization - scatter plot, line plot and stem plot, brief reference to numpy for log conversions Plotnine (ggplot in R) - bar plot, boxplot, violin plot, scatter plot
Summary Day 7 - Handling a text file - read, write and append mode, Parsing a fasta file for sequence composition glob for automation - reading multiple files in series
#Summary Day 8 - Introduction to Biopython Seq object - complement, reversecomplement, transcribe, translate methods, codon table DNA composition with gc_frac Parsing a multifasta file using the parse module Alignment using Biopython