Every line of 'pandas agg' code snippets is scanned for vulnerabilities by our powerful machine learning engine that combs millions of open source libraries, ensuring your Python code is secure.
291 def runAgg(spark, df): 292 df.agg(max("amount"), min("price")).show() 293 df.agg({"amount": "max", "price": "min"}).show()
237 def agg_to_year(self, df, func='sum'): 238 """ 239 Aggregate a DataFrame (cells x months) to (cells x years). 240 241 The groups are defined by an array the length of the number of columns, 242 where identical values are grouped. Integer division by 12 on the 243 column index gives sequential groups of length 12. 244 245 :param df: DataFrame with months in columns 246 :param func: Function to use for aggregation [default sum] 247 """ 248 return df.groupby(np.arange(len(df.columns)) // NMONTHS, axis=1).agg(func)
137 def test_aggregate_no_groups(): 138 df = pd.DataFrame({ 139 'df.g': [0, 0, 1, 1], 140 'df.a': [4, 5, 6, 7], 141 }) 142 143 def _scalar_df(values): 144 return pd.DataFrame(values, index=[0]) 145 146 def perform(q): 147 node = Aggregate(Literal(df), [DerivedColumn.parse(q)]) 148 149 ex = PandasExecutor() 150 return ex.evaluate(node, None) 151 152 pdt.assert_frame_equal(perform('SUM(a) as c'), _scalar_df({'$0.c': 22})) 153 pdt.assert_frame_equal(perform('AVG(a) as c'), _scalar_df({'$0.c': 22 / 4.0})) 154 pdt.assert_frame_equal(perform('MIN(a) as c'), _scalar_df({'$0.c': 4})) 155 pdt.assert_frame_equal(perform('MAX(a) as c'), _scalar_df({'$0.c': 7})) 156 pdt.assert_frame_equal(perform('COUNT(a) as c'), _scalar_df({'$0.c': 4}))