General functions

Data manipulations

melt(frame[, id_vars, value_vars, var_name, ...]) “Unpivots” a DataFrame from wide format to long format, optionally leaving
pivot(index, columns, values) Produce ‘pivot’ table based on 3 columns of this DataFrame.
pivot_table(data[, values, index, columns, ...]) Create a spreadsheet-style pivot table as a DataFrame.
crosstab(index, columns[, values, rownames, ...]) Compute a simple cross-tabulation of two (or more) factors.
cut(x, bins[, right, labels, retbins, ...]) Return indices of half-open bins to which each value of x belongs.
qcut(x, q[, labels, retbins, precision]) Quantile-based discretization function.
merge(left, right[, how, on, left_on, ...]) Merge DataFrame objects by performing a database-style join operation by columns or indexes.
merge_ordered(left, right[, on, left_on, ...]) Perform merge with optional filling/interpolation designed for ordered data like time series data.
merge_asof(left, right[, on, left_on, ...]) Perform an asof merge.
concat(objs[, axis, join, join_axes, ...]) Concatenate pandas objects along a particular axis with optional set logic along the other axes.
get_dummies(data[, prefix, prefix_sep, ...]) Convert categorical variable into dummy/indicator variables
factorize(values[, sort, order, ...]) Encode input values as an enumerated type or categorical variable

Top-level missing data

isnull(obj) Detect missing values (NaN in numeric arrays, None/NaN in object arrays)
notnull(obj) Replacement for numpy.isfinite / -numpy.isnan which is suitable for use on object arrays.

Top-level conversions

to_numeric(arg[, errors, downcast]) Convert argument to a numeric type.

Top-level dealing with datetimelike

to_datetime(*args, **kwargs) Convert argument to datetime.
to_timedelta(*args, **kwargs) Convert argument to timedelta
date_range([start, end, periods, freq, tz, ...]) Return a fixed frequency datetime index, with day (calendar) as the default
bdate_range([start, end, periods, freq, tz, ...]) Return a fixed frequency datetime index, with business day as the default
period_range([start, end, periods, freq, name]) Return a fixed frequency datetime index, with day (calendar) as the default
timedelta_range([start, end, periods, freq, ...]) Return a fixed frequency timedelta index, with day as the default
infer_freq(index[, warn]) Infer the most likely frequency given the input index.

Top-level evaluation

eval(expr[, parser, engine, truediv, ...]) Evaluate a Python expression as a string using various backends.

Testing

test Run tests for module using nose.