读取csv时删除熊猫中的索引列

I have the following code which imports a CSV file. There are 3 columns and I want to set the first two of them to variables. When I set the second column to the variable “efficiency” the index column is also tacked on. How can I get rid of the index column?

df = pd.DataFrame.from_csv('Efficiency_Data.csv', header=0, parse_dates=False)
energy = df.index
efficiency = df.Efficiency
print efficiency

I tried using

del df['index']

after I set

energy = df.index

which I found in another post but that results in “KeyError: ‘index’ “

DataFrames and Series always have an index. Although it displays alongside the column(s), it is not a column, which is why del df['index'] did not work.

If you want to replace the index with simple sequential numbers, use df.reset_index().

To get a sense for why the index is there and how it is used, see e.g. 10 minutes to Pandas.

When reading to and from your CSV file include the argument index=False so for example:

 df.to_csv(filename, index=False)

and to read from the csv

df.read_csv(filename, index=False)  

This should prevent the issue so you don’t need to fix it later.

df.reset_index(drop=True, inplace=True)

You can set one of the columns as an index in case it is an “id” for example. In this case the index column will be replaced by one of the columns you have chosen.

df.set_index('id', inplace=True)

If your problem is same as mine where you just want to reset the column headers from 0 to column size. Do

df = pd.DataFrame(df.values);

EDIT:

Not a good idea if you have heterogenous data types. Better just use

df.columns = range(len(df.columns))

you can specify which column is an index in your csv file by using index_col parameter of from_csv function if this doesn’t solve you problem please provide example of your data

One thing that i do is df=df.reset_index() then df=df.drop(['index'],axis=1)