.loc indexing in Pandas-Python

Question

I am having and issue with indexing of some columns. when i try indexing like that on python:

list(df1.loc[:,1980:1987])

I get the following error: TypeError: cannot do slice indexing on with these indexers [1980] of

If i try it like that:

list(df1.loc[:,'1980':'1987'])

I get the following error:

KeyError: '1980'

The dtype is float64. I want to be able to call the column label which ia year for columns 1980-1987 and drop those but without calling the index column number but the label.

Thank you

Answer 1

Slicing works on columns whatever their type. See the examples below. Maybe, you have to check your data and / or provide us an example.

# Test data
df = pd.DataFrame({'1980': ['A', 'B'], 
                   '1981': ['A', 'B'], 
                   '1982': ['A', 'B']})

# With string
print(df.columns.dtype)
print(df.loc[:,'1980':'1981'])

# object
#   1980 1981
# 0    A    A
# 1    B    B

# With integer
df.columns = df.columns.astype('int')
print(df.columns.dtype)
print(df.loc[:,1980:1981])

# int64
#   1980 1981
# 0    A    A
# 1    B    B

# With float
df.columns = df.columns.astype('float')
print(df.columns.dtype)
print(df.loc[:,1980:1981])

# float64
#   1980.0 1981.0
# 0      A      A
# 1      B      B