Idx = _tuples()ĭf1 = pandas.DataFrame(np.random.normal(size=(5,2)), index=idx, columns=) Here's simple example for posterity: import numpy as np
In the case where I have a fairly complex MultiIndex, I think I prefer the groupby approach. This is actually so simple! grouped = df3.groupby(level=0) It should also be noted that this method works with MultiIndex as well (using df1 as specified in Paul's example): > %timeit df1.groupby(level=).last() df.duplicated () not exactly removes duplicates from the dataframe but it identifies them. One such function is df.duplicated () and the other function is df.dropduplicates (). Drop duplicate rows in pandas python dropduplicates() Delete or Drop duplicate rows in pandas python using dropduplicate() function Drop the duplicate rows. Note that you can keep the last element by changing the keep argument to 'last'. Solution There are certain functions available to remove duplicates or identify duplicated in the dataframe in Pandas. Using the sample data provided: > %timeit df3.reset_index().drop_duplicates(subset='index', keep='first').set_index('index') Furthermore, while the groupby method is only slightly less performant, I find the duplicated method to be more readable. drop_duplicates is by far the least performant for the provided example. I would suggest using the duplicated method on the Pandas Index itself: df3 = df3 I thought that adding a column of row numbers ( df3 = range(df3.shape)) would help me select the bottom-most row for any value of the DatetimeIndex, but I am stuck on figuring out the group_by or pivot (or ?) statements to make that work. Index = pd.date_range(start=startdate, end=enddate, freq='H')ĭata2 = ĭf1 = pd.DataFrame(data=data1, index=index)ĭf2 = pd.DataFrame(data=data2, index=index)Īnd so I need df3 to eventually become: A B I'm reading some automated weather data from the web (observations occur every 5 minutes, and compiled into monthly files for each weather station.) After parsing a file, the DataFrame looks like: Sta Precip1hr Precip5min Temp DewPnt WindSpd WindDir AtmPressĮxample of a duplicate case: import pandas as pd In the weather DataFrame below, sometimes a scientist goes back and corrects observations - not by editing the erroneous rows, but by appending a duplicate row to the end of a file.
#PANDAS DATAFRAME REMOVE DUPLICATE ROWS HOW TO#
How to remove rows with duplicate index values?
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