如何通过数据框中的名称将功能应用于特定列

Question

I have a dataframe with a columns that contain GPS coordinates. I want to convert the columns that are in degree seconds to degree decimals. For example, I have a 2 columns named "lat_sec" and "long_sec" that are formatted with values like 186780.8954N. I tried to write a function that saves the last character in the string as the direction, divide the number part of it to get the degree decimal, and then concatenate the two together to have the new format. I then tried to find the column by its name in the data frame and apply the function to it.

New to python and can't find other resources on this. I don't think I created my function properly. I have the word 'coordinate' in it because I did not know what to call the value that I am breaking down. My data looks like this:

long_sec
635912.9277W
555057.2000W
581375.9850W
581166.2780W


df = pd.DataFrame(my_array)

def convertDec(coordinate):
    decimal = float(coordinate[:-1]/3600)
    direction = coordinate[-1:]
    return str(decimal) + str(direction)

df['lat_sec'] = df['lat_sec'].apply(lambda x: x.convertDec())

My error looks like this:
Traceback (most recent call last):
  File "code.py", line 44, in <module>
    df['lat_sec'] = df['lat_sec'].apply(lambda x: x.convertDec())
  File "C:\Python\Python37\lib\site-packages\pandas\core\frame.py", line 2917, in __getitem__
    indexer = self.columns.get_loc(key)
  File "C:\Python\Python37\lib\site-packages\pandas\core\indexes\base.py", line 2604, in get_loc
    return self._engine.get_loc(self._maybe_cast_indexer(key))
  File "pandas\_libs\index.pyx", line 108, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\index.pyx", line 129, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\index_class_helper.pxi", line 91, in pandas._libs.index.Int64Engine._check_type
KeyError: 'lat_sec'

Answer 1

By doing float(coordinate[:-1]/3600) you are dividing str by int which is not possible, what you can do is convert the str into float than divide it by integer 3600 which gives you float output.

Second you are not using apply properly and there is no lat_sec column to which you are applying your function

import pandas as pd

df = pd.DataFrame(['635912.9277W','555057.2000W','581375.9850W','581166.2780W'],columns=['long_sec'])

#function creation
def convertDec(coordinate):
    decimal = float(coordinate[:-1])/3600
    direction = coordinate[-1:]
    return str(decimal) + str(direction)

#if you just want to update the existing column 
df['long_sec'] = df.apply(lambda row: convertDec(row['long_sec']), axis=1)

#if you want to create a new column, just change to the name that you want
df['lat_sec'] = df.apply(lambda row: convertDec(row['long_sec']), axis=1) 

#OUTPUT
    long_sec
0   176.64247991666667W
1   154.18255555555555W
2   161.49332916666665W
3   161.43507722222225W

if you don't want output in float but in integer just change float(coordinate[:-1])/3600 to int(float(coordinate[:-1])/3600)

Answer 2

In your code above, inside convertDec method, there is also an error in :

decimal = float(coordinate[:-1]/3600)

You need to convert the coordinate to float first before divide it with 3600.

So, your code above should look like this :

import pandas as pd

# Your example dataset
dictCoordinates = {
    "long_sec" : ["111111.1111W", "222222.2222W", "333333.3333W", "444444.4444W"],
    "lat_sec"  : ["555555.5555N", "666666.6666N", "777777.7777N", "888888.8888N"]
}

# Insert your dataset into Pandas DataFrame
df = pd.DataFrame(data = dictCoordinates)

# Your conversion method here
def convertDec(coordinate):
    decimal = float(coordinate[:-1]) / 3600 # Eliminate last character, then convert to float, then divide it with 3600
    decimal = format(decimal, ".4f") # To make sure the output has 4 digits after decimal point
    direction = coordinate[-1] # Extract direction (N or W) from content
    return str(decimal) + direction # Return your desired output

# Do the conversion for your "long_sec"
df["long_sec"] = df.apply(lambda x : convertDec(x["long_sec"]), axis = 1)

# Do the conversion for your "lat_sec"
df["lat_sec"] = df.apply(lambda x : convertDec(x["lat_sec"]), axis = 1)

print(df)

That's it. Hope this helps.