Given a Pandas DataFrame, we have to select distinct across multiple columns.ByPranit SharmaLast updated : September 22, 2023 Distinct elements are those elements that are not similar to other elements, in other words, we can say that distinct elements are those elements that have their occurrenc...
现在在Pandas中使用drop_duplicates和keep参数时，这就容易多了。
现在在Pandas中使用drop_duplicates和keep参数时，这就容易多了。
# SQL SELECT DISTINCT column_a FROM table_df # Pandas table_df['column_a'].drop_duplicates() SELECT a as b 如果要重命名列,请使用 .rename(): # SQL SELECT column_a as Apple, column_b as Banana FROM table_df # Pandas table_df[['column_a', 'column_b']].rename(columns={'column...
# SQLSELECTDISTINCTcolumn_aFROMtable_df# Pandastable_df['column_a'].drop_duplicates() 1. 2. 3. 4. 5. SELECT a as b 如果要重命名列,请使用 .rename(): 复制 # SQLSELECTcolumn_aasApple, column_basBananaFROMtable_df# Pandastable_df[['column_a','column_b']].rename(columns={'column_...
A step-by-step illustrated guide on how to select distinct across multiple DataFrame columns in Pandas.
You can also usenunique,counton multiple columns to get a distinct count on multiple columns. # Use .nunique() for multiple columns to count(distinct) equivalent df2 = df.groupby('Date').agg({'Date': ['nunique', 'count'],'Fee': ['nunique', 'count']}) ...
# Grouping by multiple columns decade_rain = df.groupby([df.year // 10 * 10, df.rain_octsep // 1000 * 1000])[['outflow_octsep', 'outflow_decfeb', 'outflow_junaug']].mean() decade_rain 1. 2. 3. 接下来是 unstack ,它可以将一列数据设置为列标签。最好还是看看实际的操作: ...
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Note that Uniques are returned in order of appearance. if you want to sort, usesort()function tosort single or multiple columns of DataFrame. Key Points – Theunique()method returns the unique values in a column as a NumPy array, which is useful for quickly identifying distinct entries. ...