问题
I have a DataFrame with two indices and would like to reindex it by one of the indices.
from pandas_datareader import data
import matplotlib.pyplot as plt
import pandas as pd
# Instruments to download
tickers = ['AAPL']
# Online source one should use
data_source = 'yahoo'
# Data range
start_date = '2000-01-01'
end_date = '2018-01-09'
# Load the desired data
panel_data = data.DataReader(tickers, data_source, start_date, end_date).to_frame()
panel_data.head()
The reindexing goes as follows:
# Get just the adjusted closing prices
adj_close = panel_data['Adj Close']
# Gett all weekdays between start and end dates
all_weekdays = pd.date_range(start=start_date, end=end_date, freq='B')
# Align the existing prices in adj_close with our new set of dates
adj_close = adj_close.reindex(all_weekdays, method="ffill")
The last line gives the following error:
TypeError: '<' not supported between instances of 'tuple' and 'int'
This is because the DataFrame index is a list of tuples:
panel_data.index[0]
(Timestamp('2018-01-09 00:00:00'), 'AAPL')
Is it possible to reindex adj_close
? By the way, if I don't convert the Panel object to a DataFrame using to_frame()
, the reindexing works as it is. But it seems that Panel objects are deprecated...
回答1:
If you're looking to reindex on a certain level, then reindex
accepts a level
argument you can pass -
adj_close.reindex(all_weekdays, level=0)
When passing a level
argument, you cannot pass a method
argument at the same time (reindex
throws a TypeError
), so you can chain a ffill
call after -
adj_close.reindex(all_weekdays, level=0).ffill()
来源:https://stackoverflow.com/questions/48179297/reindexing-a-specific-level-of-a-multiindex-dataframe