The question is probaly extremely dumb, but i hurt my brain figuring out what to do
There is a pd.dataframe with N columns. I need to select some columns, referring by index of a column, then convert all values to numeric and rewrite that column in my dataframe
I've done it by column name reference (like df['a'] = pd.to_numeric(df['a']) but stuck with indices (like df[1] = pd.to_numeric(df[1])
What is the right way in this situation to dataframe column referencing? (python 2.7)
You can use iloc for selecting columns and then apply to_numeric:
import pandas as pd
df = pd.DataFrame({1:['1','2','3'],
2:[4,5,6],
3:[7,8,9],
4:['1','3','5'],
5:[5,3,6],
6:['7','4','3']})
print (df)
1 2 3 4 5 6
0 1 4 7 1 5 7
1 2 5 8 3 3 4
2 3 6 9 5 6 3
print (df.dtypes)
1 object
2 int64
3 int64
4 object
5 int64
6 object
dtype: object
print (df.columns)
Int64Index([1, 2, 3, 4, 5, 6], dtype='int64')
cols = [1,4,6]
df.iloc[:, cols] = df.iloc[:, cols].apply(pd.to_numeric)
print (df)
1 2 3 4 5 6
0 1 4 7 1 5 7
1 2 5 8 3 3 4
2 3 6 9 5 6 3
print (df.dtypes)
1 int64
2 int64
3 int64
4 int64
5 int64
6 int64
dtype: object
If columns are strings, not int (but it looks like int) add '' to numbers in list cols:
import pandas as pd
df = pd.DataFrame({'1':['1','2','3'],
'2':[4,5,6],
'3':[7,8,9],
'4':['1','3','5'],
'5':[5,3,6],
'6':['7','4','3']})
#print (df)
#print (df.dtypes)
print (df.columns)
Index(['1', '2', '3', '4', '5', '6'], dtype='object')
#add `''`
cols = ['1','4','6']
#1. loc: only label based access
# df.loc[:, cols] = df.loc[:, cols].apply(pd.to_numeric)
#2. iloc: for index based access
# cols = [1,4,6]
# df.iloc[:, cols].apply(pd.to_numeric)
print (df)
1 2 3 4 5 6
0 1 4 7 1 5 7
1 2 5 8 3 3 4
2 3 6 9 5 6 3
print (df.dtypes)
1 int64
2 int64
3 int64
4 int64
5 int64
6 int64
dtype: object