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Pandas data frame not allowing me to drop first empty column in python?

I have read in some data from a csv, and there were a load of spare columns and rows that were not needed. I've managed to get rid of most of them, but the first column is showing as an NaN and will not drop despite several attempts. This means I cannot promote the titles in row 0 to headers. I have tried the below:
df = pd.read_csv(("List of schools.csv"))
df = df.iloc[3:]
df.dropna(how='all', axis=1, inplace =True)
df.head()
But I am still getting this returned:
Any help please? I'm a newbie

You can improve your read_csv() operation.
Avloss can tell your "columns" are indices because they are bold. Looking at your output, there are two things of note.
The "columns" are bold implying that pandas read them in as part of the index of the DataFrame rather than as values
There is no information above the horizontal line at the top indicating there are currently no column names. The top row of the csv file that contains the column names is being read in as values.
To solve your column deletion problem, you should first improve your read_csv() operation by being more explicit. Your current code is placing column headers in the data and placing some of the data in the indicies. Since you have the operation df = df.iloc[3:] in your code, I'm assuming the data in your csv file doesn't start until the 4th row. Try this:
header_row = 3 #or 4 - I am bad at zero-indexing
df = pd.read_csv('List of schools.csv', header=header_row, index_col=False)
df.dropna(how='all', axis=1, inplace =True)
This code should read the column names in as column names and not index any of the columns, giving you a cleaner DataFrame to work from when dropping NA values.

those aren't columns, those are indices. You can convert them to columns by doing
df = df.reset_index()

i've a dataframe and i want to get values from a column called requester i'm getting an extra column along with requester column

in my data frame, I have a column called requester when I want to get data of requester column I'm getting another column data along with it, how to remove the extra column
the data frame i've
and the code I'm trying here is
names = pd.DataFrame(report['Requester'])
and the output I'm getting is
I want to remove SLA resol column from daataframe.

Problem is first column is converted to index.
So possible solution is first add DataFrame.reset_index for default index and then for one column DataFrame add [[]] with column name:
report = report.reset_index()
names = report[['Requester']]
Another idea is create DataFrame with default index by read_csv or read_excel with index=False:
df = pd.read_csv(file, index=False)
df = pd.read_excel(file1, index=False)
Last if need write DataFrame without default index:
df.to_csv(file2, index=False)
df.to_excel(file12, index=False)

Cant drop columns with pandas if index_col = 0 is used while reading csv's [duplicate]

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' "

When writing to and reading from a CSV file include the argument index=False and index_col=False, respectively. Follows an example:
To write:
df.to_csv(filename, index=False)
and to read from the csv
df.read_csv(filename, index_col=False)
This should prevent the issue so you don't need to fix it later.

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

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.

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)

To remove or not to create the default index column, you can set the index_col to False and keep the header as Zero. Here is an example of how you can do it.
recording = pd.read_excel("file.xls",
sheet_name= "sheet1",
header= 0,
index_col= False)
The header = 0 will make your attributes to headers and you can use it later for calling the column.

It works for me this way:
Df = data.set_index("name of the column header to start as index column" )

Pandas dataframe read_excel does not consider blank upper left cells as columns?

I'm trying to read an Excel or CSV file into pandas dataframe. The file will read the first two columns only, and the top row of the first two columns will be the column names. The problem is when I have the first column of the top row empty in the Excel file.
IDs
2/26/2010 2
3/31/2010 4
4/31/2010 2
5/31/2010 2
Then, the last line of the following code fails:
uploaded_file = request.FILES['file-name']
if uploaded_file.name.endswith('.csv'):
df = pd.read_csv(uploaded_file, usecols=[0,1])
else:
df = pd.read_excel(uploaded_file, usecols=[0,1])
ref_date = 'ref_date'
regime_tag = 'regime_tag'
df.columns = [ref_date, regime_tag]
Apparently, it only reads one column (i.e. the IDs). However, with read_csv, it reads both column, with the first column being unnamed. I want it to behave that way and read both columns regardless of whether the top cells are empty or filled. How do I go about doing that?

What's happening is the first "column" in the Excel file is being read in as an index, while in the CSV file it's being treated as a column / series.
I recommend you work the other way and amend pd.read_csv to read the first column as an index. Then use reset_index to elevate the index to a series:
if uploaded_file.name.endswith('.csv'):
df = pd.read_csv(uploaded_file, usecols=[0,1], index_col=0)
else:
df = pd.read_excel(uploaded_file, header=[0,1], usecols=[0,1])
df = df.reset_index() # this will elevate index to a column called 'index'
This will give consistent output, i.e. first series will have label 'index' and the index of the dataframe will be the regular pd.RangeIndex.
You could potentially use a dispatcher to get rid of the unwieldy if / else construct:
file_flag = {True: pd.read_csv, False: pd.read_excel}
read_func = file_flag[uploaded_file.name.endswith('.csv')]
df = read_func(uploaded_file, usecols=[0,1], index_col=0).reset_index()

How to delete or drop the column labelled "index" from a dataframe when using to_csv() to save as csv

I am reading a csv file, cleaning it up a little, and then saving it back to a new csv file. The problem is that the new csv file has a new column (first column in fact), labelled as index. Now this is not the row index, as I have turned that off in the to_csv() function as you can see in the code. Plus row index doesn't have a column label as well.
df = pd.read_csv('D1.csv', na_values=0, nrows = 139) # Read csv, with 0 values converted to NaN
df = df.dropna(axis=0, how='any') # Delete any rows containing NaN
df = df.reset_index()
df.to_csv('D1Clean.csv', index=False)
Any ideas where this phantom column is coming from and how to get rid of it?

I think you need add parameter drop=True to reset_index:
df = df.reset_index(drop=True)
drop : boolean, default False
Do not try to insert index into dataframe columns. This resets the index to the default integer index.