Dec 22, 2017 · You can get the unique values in the whole df with this one-liner: pd.Series(df.values.flatten()).unique() You basically transform your df to a numpy array, flatten and come back to a pandas Series, so you can use unique(). However, types might be transformed along the way if you have multiple types in your original df, so be careful.

Sep 7, 2012 · This is wrong. drop_duplicates acts on the values only (at least in my version). You need to reset_index if you want to drop on index and values or just work with the index if you want to have a unique index. Maybe there is another way besides groupby to enforce unique index? –

param = [] for _, group in df[df.param.notnull()].groupby('group'): param.append(group.param.unique()[0]) print(pd.DataFrame({'param': param}).param.value_counts()) # a 2 # b 1 I'm sure there's a way to do this more cleanly and without using a loop, but I just can't seem to work it out. Any help would be much appreciated.

Aug 18, 2015 · The reason is because unique() returns a numpy.ndarray, so sort() is actually numpy.ndarray.sort() method. That's why the behavior is unexpected. That's why the behavior is unexpected. drop_duplicates() returns a pandas series or dataframe, allowing use of sort_values() .

pd.unique returns the unique values from an input array, or DataFrame column or index. The input to this function needs to be one-dimensional, so multiple columns will need to be combined. The simplest way is to select the columns you want and then view the values in …

May 26, 2019 · I have a big DF with 10 millions rows and I need to find the unique number for each column. I wrote the function below: (need to return a series) def count_unique_values(df): return pd.Series(df.nunique()) and I get this output: Area 210 Item 436 Element 4 Year 53 Unit 2 Value 313640 dtype: int64

Feb 8, 2016 · Placing @EdChum's very nice answer into a function count_unique_index. The unique method only works on pandas series, not on data frames. The function below reproduces the behavior of the unique function in R: unique returns a vector, data frame or array like x but with duplicate elements/rows removed.

Jan 28, 2014 · I want to filter the dataframe so that I have a unique occurrence of "type" attrybute (e.g. A appears only once), and if there are more rows that have the same value for "type" I want to choose the one with higher value. I want to get something like: ID type value 1 A 8 3 B 11 4 C 12 6 D 22 How do I do this with pandas?

May 29, 2015 · I'm looking for a way to do the equivalent to the SQL SELECT DISTINCT col1, col2 FROM dataframe_table The pandas sql comparison doesn't have anything about distinct. .unique() only works for a ...

Dec 2, 2014 · We simply want the counts of all unique values in the DataFrame. A simple solution is: df.stack().value_counts() However: 1. It looks like stack returns a copy, not a view, which is memory prohibitive in this case. Is this correct? 2. I want to group the DataFrame by rows, and then get the different histograms for each grouping.