Pandas 根据同一数据框中另一列的条件替换列值

Question

I have a data frame as below:

I want to copy the selected values of easting and northing to the column longitude and latitude if northing is < 90 and then set the original values to None.

Here is my python code:

for i, j in waypoint_df.iterrows():
    easting = j['easting']
    northing = j['northing']
    if northing and northing < 90:
        waypoint_df.at[i,'latitude'] = northing
        waypoint_df.at[i,'longitude'] = easting
        waypoint_df.at[i,'northing'] = None
        waypoint_df.at[i,'easting']= None

Is there a simpler way to run the operation above instead of iterating all rows?

Answer 1

Use pandas.DataFrame.assign to swap the values of eas/nor and lon/lat with a boolean mask.

mask = waypoint_df['northing'].lt(90)

waypoint_df.loc[mask] = waypoint_df.assign(latitude= waypoint_df['easting'], easting= waypoint_df'[latitude'],
                         longitude= waypoint_df['northing'], northing= waypoint_df['longitude'])

# Output:

print(waypoint_df)

   locality_id locality   waypoint   easting   northing                                     description   grid      date collected_by  latitude  longitude  waypoint_pk
0          761     None  BATurnoff  368255.0  6614695.0   Turnoff from Yarri Rd (also access to Harpers  AMG51  12-12-07          SJB       NaN        NaN            1
1          761     None       BKAW  367700.0  6616800.0                End of access track at breakaway  AMG51  12-12-07          SJB       NaN        NaN            2
2          761     None      BKAWT  367071.0  6615492.0   Access track turnoff from Harpers Lagoon road  AMG51  12-12-07          SJB       NaN        NaN            3
3         3581     None    DM14-01       NaN        NaN   King of the Hills dyke -- Hugely contaminated   None  10-11-15       D Mole     121.2     -28.62            4
4         3581     None    DM14-02       NaN        NaN  Intrusion into KOTH dyke? -- Graphic granite -   None  10-11-15       D Mole     121.2     -28.62            5