<p>如果您的代理和活动有单独的行,您可以创建一个多索引,如下所示:</p>
<pre><code>import pandas as pd
# This is the dataframe data with activities you got from a single agent
agent_1 = [['Phone', 'Phone', 'Coffee', 'Lunch', 'Phone', 'Phone', 'Lunch', 'Lunch'],
['04:00', '08:30', '10:30', '04:00', '10:30', '04:00', '08:30', '10:30']]
# This is the dataframe data from a second agent
agent_2 = [['Phone', 'Pooping', 'Coffee', 'Lunch', 'Phone', 'Meeting', 'Lunch', 'Lunch'],
['08:45', '08:50', '10:30', '04:00', '10:30', '04:00', '08:30', '10:30']]
# We create the dataframe for agent 1
df1 = pd.DataFrame(agent_1).T
df1.columns = ['activity', 'time']
# We create the dataframe for agent 2
df2 = pd.DataFrame(agent_2).T
df2.columns = ['activity', 'time']
# Now we have to dataframes we can't really put together
print(df1)
print(" ")
print(df2)
print(" ")
# So we should give each dataframe a column with its agent.
df1['agent'] = "Agent_1"
df2['agent'] = "Agent_2"
# Now each dataframe has data on its agent
print(df1)
print(" ")
print(df2)
print(" ")
# Let's combine them
overview = pd.concat([df1, df2])
print(overview)
print(" ")
# To make it even better, we could make a multi-index so we can index both agents AND activities
overview.set_index(['agent', 'activity'], inplace=True)
print(overview)
</code></pre>
<p>输出:</p>
^{pr2}$