Pandas to Pathway Cheat Sheet

Operation	Pandas	Pathway
Selecting columns	`df[['colA', 'colB', ...]]`	`t.select(t.colA, t['colB'], pw.this.colC)`
Filtering on a given value	`df[df['name'] == value]`	`t.filter(t.name == value)`
Filtering on a condition	`df[condition]`	`t.filter(condition)`
Group-by and Aggregation	`df.groupby('name').sum()`	`t.groupby(pw.this.name).reduce(sum=pw.reducers.sum(pw.this.value))`
Applying a function	`df['c'] = func(df['a'], df['b'], ..)`	`t.select(c=pw.apply(func, t.a, t.b))`
Join Operations	`df1.join(df2, on='name')`	`t1.join(t2, pw.left.name == pw.right.name).select(...)`
Reading CSV files	`df = pd.read_csv('file_name')`	`t = pw.io.csv.read('./data/', schema=InputSchema)`
Writing to CSV files	`pd.to_csv('file_name')`	`pw.io.csv.write(table, './output/')`
Accessing a row by label	`df.loc[[label]]`	Using joins or `ix_ref`
Accessing a row by index	`df.iloc[0]`	No equivalence as location-based indexes don't make sense with changing table data.

Pandas Cheat Sheet