DataFrame.update(other, join='left', overwrite=True, filter_func=None, errors='ignore')[source]#

Modify a DataFrame in place using non-NA values from another DataFrame.

Aligns on indices. There is no return value.

otherDataFrame, or object coercible into a DataFrame

Should have at least one matching index/column label with the original DataFrame. If a Series is passed, its name attribute must be set, and that will be used as the column name to align with the original DataFrame.

join{‘left’}, default ‘left’

Only left join is implemented, keeping the index and columns of the original object.

overwrite{True, False}, default True

How to handle non-NA values for overlapping keys: True: overwrite original DataFrame’s values with values from other. False: only update values that are NA in the original DataFrame.


filter_func is not supported yet Return True for values that should be updated.S

errors{‘raise’, ‘ignore’}, default ‘ignore’

If ‘raise’, will raise a ValueError if the DataFrame and other both contain non-NA data in the same place.

Nonemethod directly changes calling object
  • When errors = ‘raise’ and there’s overlapping non-NA data.

  • When errors is not either ‘ignore’ or ‘raise’

  • If join != ‘left’