tessl/pypi-datatable
Python package for manipulating 2-dimensional tabular data structures with emphasis on speed and big data support
—
Pending
row-operations.mddocs/
Row-wise Operations
Element-wise operations across columns within rows for complex transformations and calculations.
Capabilities
Row-wise Aggregation Functions
def rowall(*cols):
"""Row-wise all (logical AND across columns)"""
def rowany(*cols):
"""Row-wise any (logical OR across columns)"""
def rowcount(*cols):
"""Row-wise count of non-missing values"""
def rowsum(*cols):
"""Row-wise sum across columns"""
def rowmean(*cols):
"""Row-wise mean across columns"""
def rowmin(*cols):
"""Row-wise minimum across columns"""
def rowmax(*cols):
"""Row-wise maximum across columns"""
def rowsd(*cols):
"""Row-wise standard deviation across columns"""
def rowfirst(*cols):
"""Row-wise first non-missing value"""
def rowlast(*cols):
"""Row-wise last non-missing value"""
def rowargmin(*cols):
"""Row-wise index of minimum value"""
def rowargmax(*cols):
"""Row-wise index of maximum value"""Examples
import datatable as dt
DT = dt.Frame({
'A': [1, 2, None, 4],
'B': [2, None, 3, 5],
'C': [3, 4, 5, None]
})
# Row-wise operations
result = DT[:, dt.update(
sum_abc=dt.rowsum(f.A, f.B, f.C),
mean_abc=dt.rowmean(f.A, f.B, f.C),
min_abc=dt.rowmin(f.A, f.B, f.C),
max_abc=dt.rowmax(f.A, f.B, f.C),
count_abc=dt.rowcount(f.A, f.B, f.C)
)]Install with Tessl CLI
npx tessl i tessl/pypi-datatable