I read some weather data from a csv file as a dataframe named \"weather\". The problem is that one of the columns\' data type is an object. this is weird beacuse it indicates te
pandas.Series.astype
You can do something like this :
weather["Temp"] = weather.Temp.astype(float)
You can also use pd.to_numeric
that will convert the column from object to float
Example :
s = pd.Series(['apple', '1.0', '2', -3])
print(pd.to_numeric(s, errors='ignore'))
print("=========================")
print(pd.to_numeric(s, errors='coerce'))
Output:
0 apple
1 1.0
2 2
3 -3
=========================
dtype: object
0 NaN
1 1.0
2 2.0
3 -3.0
dtype: float64
In your case you can do something like this:
weather["Temp"] = pd.to_numeric(weather.Temp, errors='coerce')
convert_objects
Example is as follows
>> pd.Series([1,2,3,4,'.']).convert_objects(convert_numeric=True)
0 1
1 2
2 3
3 4
4 NaN
dtype: float64
You can use this as follows:
weather["Temp"] = weather.Temp.convert_objects(convert_numeric=True)
NaN
... so be careful while using it.