How to add multiple columns in reset_index from a pandas- series - python-3.x

Question

Am having a pandas series & i need to show it's elements in columnar fashion embedded in an email body with HTML.Hence tried below snippet. It worked for me initially with two columns, but now i have three columns to display. Here is code-
a = max_compare.rename_axis('Metric').reset_index(name='Yesterday').to_html()
Here max_compare is series with below output-
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>Metric</th>
<th>Yesterday</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>GSV</td>
<td>4424180.0</td>
</tr>
<tr>
<th>1</th>
<td>Units</td>
<td>7463.0</td>
</tr>
</tbody>
</table>
Now i am having another element to be shown in column. Tried below code snippet, but got exception.
a =max_compare.rename_axis('Metric').reset_index(name=['Yesterday'],[L30 average]).to_html()
Current Output in HTML
Output-

Answer 1

Since you do not provide any data sample nor expected result, I do not know exactly what you want to do. However, this is how to reset a MultiIndex.
level : int, str, tuple, or list, default None
Only remove the given levels from the index. Removes all levels by default
Link to the documentation
import pandas as pd
import io
# Paste the text by using of triple-quotes to span String literals on multiple lines
zz = """index grade class numgrade numyear
0 A Senior 12 4
1 A Junior 12 3
2 A Junior 12 3
3 A Senior 12 4
4 A Junior 12 3
"""
df = pd.read_table(io.StringIO(zz), delim_whitespace=True)
df.set_index(['index', 'grade'], inplace=True)
# Reset the two levels
df.reset_index(level=(0,1))
Edit
The same method can be used with Series. But Reseting a MultiIndex of a Series will convert it back to a DataFrame since Series, by definition, have only one column (a value) and an index. In consequence, I think you should use DataFrame if you want to deal with more than one column.
# Paste the text by using of triple-quotes to span String literals on multiple lines
zz = """index grade class
0 A Senior
1 A Junior
2 A Junior
3 A Senior
4 A Junior
"""
df = pd.read_table(io.StringIO(zz), delim_whitespace=True)
df.set_index(['index', 'grade'], inplace=True)
# Creating a series with a multiIndex
se = df.iloc[:,0]
print(type(se))
# Reseting index also works for Series.
# In case of MultiIndex, Series will be converted back
# to a DataFrame since Series, by definition, have
# only one column and an index
se.reset_index(level=(0,1))
# <class 'pandas.core.series.Series'>
# index grade class
# 0 0 A Senior
# 1 1 A Junior
# 2 2 A Junior
# 3 3 A Senior
# 4 4 A Junior