watex.utils.twinning#

watex.utils.twinning(*d, on=None, parse_on=False, mode='strict', coerce=False, force=False, decimals=7, raise_warn=True)[source]#

Find indentical object in all data and concatenate them using merge: intersection (cross) strategy.

Parameters:

d (List of DataFrames) – List of pandas DataFrames
on (str, label or list) –
Column or index level names to join on. These must be found in all DataFrames. If on is None and not merging on indexes then a concatenation along columns axis is performed in all DataFrames. Note that on works with parse_on if its argument is a list of columns names passed into single litteral string. For instance:
```
on ='longitude latitude' --[parse_on=True]-> ['longitude' , 'latitude']
```
parse_on (bool, default=False) – Parse on arguments if given as string and return_iterable objects.
mode (str, default='strict') – Mode to the data. Can be [‘soft’|’strict’]. In strict mode, all the data passed must be a DataFrame, otherwise an error raises. in soft mode, ignore the non-DataFrame. Note that any other values should be in strict mode.
coerce (bool, default=False) – Truncate all DataFrame size to much the shorter one before performing the merge.
force (bool, default=False,) – Force on items to be in the all DataFrames, This could be possible at least, on items should be in one DataFrame. If missing in all data, an error occurs.
decimals (int, default=5) –

Decimal is used for comparison between numeric labels in on columns
items. If set, it rounds values of on items in all data before performing the merge.

raise_warn: bool, default=False
Warn user to concatenate data along column axis if on is None.

Returns:

data – A DataFrame of the merged objects.

Return type:

DataFrames

Examples

>>> import watex as wx
>>> from watex.utils.funcutils import twinning
>>> data = wx.make_erp (seed =42 , n_stations =12, as_frame =True )
>>> table1 = wx.methods.DCProfiling ().fit(data).summary()
>>> table1
       dipole   longitude  latitude  ...  shape  type       sfi
line1      10  110.486111  26.05174  ...      C    EC  1.141844
>>> data_no_xy = wx.make_ves ( seed=0 , as_frame =True)
>>> data_no_xy.head(2)
    AB   MN  resistivity
0  1.0  0.4   448.860148
1  2.0  0.4   449.060335
>>> data_xy = wx.make_ves ( seed =0 , as_frame =True , add_xy =True )
>>> data_xy.head(2)
    AB   MN  resistivity   longitude  latitude
0  1.0  0.4   448.860148  109.332931  28.41193
1  2.0  0.4   449.060335  109.332931  28.41193
>>> table = wx.methods.VerticalSounding (
    xycoords = (110.486111,   26.05174)).fit(data_no_xy).summary()
>>> table.table_
         AB    MN   arrangememt  ... nareas   longitude  latitude
area                             ...
None  200.0  20.0  schlumberger  ...      1  110.486111  26.05174
>>> twinning (table1, table.table_,  )
       dipole   longitude  latitude  ...  nareas   longitude  latitude
line1    10.0  110.486111  26.05174  ...     NaN         NaN       NaN
None      NaN         NaN       NaN  ...     1.0  110.486111  26.05174
>>> twinning (table1, table.table_, on =['longitude', 'latitude'] )
Empty DataFrame
>>> # comments: Empty dataframe appears because, decimal is too large
>>> # then it considers values longitude and latitude differents
>>> twinning (table1, table.table_, on =['longitude', 'latitude'], decimals =5 )
    dipole  longitude  latitude  ...  max_depth  ohmic_area  nareas
0      10  110.48611  26.05174  ...      109.0  690.063003       1
>>> # Now is able to find existing dataframe with identical closer coordinates.