How do I get rid of the second indexing column in Pandas? (Python)

Question

I'm trying to make a graph of pay against time. Here's what I've got:

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv('Pay051118_1.csv')
df.to_csv("Newcsv", columns = ['Dates worked', 'Pay'])
df = pd.read_csv('Newcsv', parse_dates = True, index_col = 0)

df = df.fillna(0)

df = ((df[['Dates worked','Pay']])[df.Pay > 1])
print (df)

df.plot()
plt.show()

Line 5 of the code got rid of one of the indexing columns for me. Without putting in the parse_dates and index_col parameter, I will get 2 columns of indexes. When I print (df), this is what I get:

                   Dates worked   Pay
0       Monday, 5 November 2018  44.5
2    Wednesday, 7 November 2018  44.5
3     Thursday, 8 November 2018  44.5
4       Friday, 9 November 2018  44.5
6      Sunday, 11 November 2018  50.5
7      Monday, 12 November 2018  62.0
8     Tuesday, 13 November 2018  38.5
9   Wednesday, 14 November 2018  65.5
10   Thursday, 15 November 2018  62.0
16  Wednesday, 21 November 2018  65.5
17   Thursday, 22 November 2018  62.0
18     Friday, 23 November 2018  65.5
20     Sunday, 25 November 2018  62.5
21     Monday, 26 November 2018  58.5
22    Tuesday, 27 November 2018  42.0
23  Wednesday, 28 November 2018  65.5
25     Friday, 30 November 2018  62.0

As you can see, the indexing column is still there. How can I get rid of it?

Data frames always have an index, what you can do is to reset it to something else, for example the dates. This can be achieved by `df.set_index`. — a_guest, Dec 04 '18 at 01:19
Hi, you don't need to import, export, and re-import your CSV. You can select columns on import. See pandas.pydata.org/pandas-docs/stable/io.html#io-read-csv-table. After that, see https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.set_index.html. We don't have access to your csv. — Evan, Dec 04 '18 at 01:25
Possible duplicate of [Could pandas use column as index?](https://stackoverflow.com/questions/38542419/could-pandas-use-column-as-index) — Evan, Dec 04 '18 at 01:28

score 1 · Accepted Answer · answered Dec 04 '18 at 01:29

1

Use below one.This will print without left most row of numbers which you dont want to see.

print df.to_string(index=False)

answered Dec 04 '18 at 01:29

LOrD_ARaGOrN

3,884
3
27
49

Thanks, it worked. But by I way why must we just the df.to_string code? What does converting it to string do? – koifish Dec 04 '18 at 01:35
It Render a DataFrame to a console-friendly tabular output. You can refer below link. https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_string.html – LOrD_ARaGOrN Dec 04 '18 at 01:39

score 0 · Answer 2 · answered Dec 04 '18 at 01:25

0

Pandas dataframes always have an index but it is not real column, If you want to replace the index with simple sequential numbers, use df.reset_index().

answered Dec 04 '18 at 01:25

Aditya Lahiri

409
3
11

Hi this doesn't seem to work. I inserted your line into the line of code after df.Pay > 1, but I still get the same output, with the indexes not resetted. – koifish Dec 04 '18 at 01:34
Assign it to df. That is df=df.reset_index() – Aditya Lahiri Dec 04 '18 at 01:36

score -1 · Answer 3 · answered Dec 04 '18 at 01:28

"""
Dates worked,Pay
Monday 5 November 2018,44.5
Wednesday 7 November 2018,44.5
Thursday 8 November 2018,44.5
Friday 9 November 2018,44.5
"""
import pandas as pd
pd.read_clipboard(sep=",").set_index("Dates worked")

If you don't want an auto-generated index, you'll need to set some other column as the index.

How do I get rid of the second indexing column in Pandas? (Python)

3 Answers3