将 pandas 上的列从非空值 object 转换为浮点数

Question

I'm having some difficulties to convert the values from object to float!!!

I saw some examples but I couldn't be able to get it.

I would like to have a for loop to convert the values in all columns.

I didn't have yet a script cause I saw different ways to do it

Terawatt-hours  Total Asia Pacific  Total CIS   Total Europe
2000             0.428429            0             0.134473
2001             0.608465            0             0.170166
2002             0.829254            0             0.276783
2003             1.11654             0             0.468726
2004             1.46406             0             0.751126
2005             1.85281             0             1.48641
2006             2.29128             0             2.52412
2007             2.74858             0             3.81573
2008             3.3306              0             7.5011
2009             4.3835              7.375e-06     14.1928
2010             6.73875             0.000240125   23.2634
2011             12.1544             0.00182275    46.7135

I tried this:

df = pd.read_excel(r'bp-stats-review-2019-all-data.xls')
columns = list(df.head(0))
for i in range(len(columns)):
    df[columns[i]].astype(float)

Answer 1

Your question is not clear as to which column you are trying to convert, So I am sharing the example for the 1st column in your screenshot.

df['Terawatt-hours'] = df.Terawatt-hours.astype(float)

or same for any other column.

EDIT

for creating a loop on the dataframe and change it for all the columns, you can do the following:

Generating a dummy dataframe

df = pd.DataFrame(np.random.randint(0, 100, size=(20, 4)), columns=list('abcd'))

Check the type of column in dataframe:

for column in df.columns:
    print(df[column].dtype)

Change the type of all the columns to float

for column in df.columns:
    df[column] = df[column].astype(float)

Answer 2

your question is not clear? which columns are you trying to convert to float and also post what you have done.

EDIT:

what you tried is right until the last line of your code where you failed to reassign the columns. df[columns[i]] = df[columns[i]].astype(float)

also try using df.columns to get column names instead of list(df.head(0))

the link here to pandas docs on how to cast a pandas object to a specified dtype