• footguns
  • type inference when constructing
  • .copy() or else transforms are just slices/views that share underlying storage
• creation
  • read_csv
  • flags: parse_dates
• slicing and dicing
  • iloc: by indexes
  • loc: supports labels
  • query
  • sample
  • drop
  • dropna: drop columns with na’s, can specify thresholds
• summaries
  • head
  • describe
  • quantile
  • nlargest
  • nsmallest
• df transforms
  • rename
  • filter(regex=): project columns
  • apply: rows
  • get_dummies: replace missing values
  • concat
  • sort_values(by=…)
  • drop_duplicates
  • groupby
    • agg, aggregate: can specify dict of new columns and their agg function(s)
    • filter: return same rows but filtered (like SQL OVER + WHERE)
    • transform: passed in entire group, e.g. x - x.mean() (like SQL OVER)
    • apply: passed in rows (like SQL OVER)
  • pivot_table: groupby + unstack (groupby results in multi-index along rows)
• series transforms
  • cut: bin continuous values into discrete
  • fillna
  • isin: for categoricals
• time series
  • rolling: sliding window: s.rolling(window=2).agg(…)
  • resample: aggregate over windows of 5min, 1ms, 1h, ME=month end, BME=business ME, QE, BQE, W, etc.
• indexes
  • set_index
  • reset_index: moves indexes into normal columns, indexes now just ints
  • unstack: move index to column
  • stack: move column to index, potentially collapsing into a Series if no more columns remain
• joins
  • merge: how you join - inner, outer, left, right, cross
    • appends _x and _y for same-name columns
    • supports validation
    • supports arbitrary grouping: pass in a group key per row
  • merge_asof: time-based merge
• plot
  • plot(kind=’scatter’)
• misc: supports styling
• export
  • to_numpy