@@ -110,31 +110,31 @@ This function returns an integer indicating the total number of elements in the
110110
111111 In this example, the `num_elements ` column will contain `3 ` for both rows.
112112
113- To concatenate two arrays, you can use the function :py:func: `datafusion.functions.list_cat  ` or :py:func: `datafusion.functions.list_concat  `.
113+ To concatenate two arrays, you can use the function :py:func: `datafusion.functions.array_cat  ` or :py:func: `datafusion.functions.array_concat  `.
114114These functions return a new array that is the concatenation of the input arrays.
115115
116116.. ipython :: python 
117117
118118    from  datafusion import  SessionContext, col 
119-     from  datafusion.functions import  list_cat, list_concat  
119+     from  datafusion.functions import  array_cat, array_concat  
120120
121121    ctx =  SessionContext() 
122122    df =  ctx.from_pydict({" a"  : [[1 , 2 , 3 ]], " b"  : [[4 , 5 , 6 ]]}) 
123-     df.select(list_cat (col(" a"  ), col(" b"  )).alias(" concatenated_array"  )) 
123+     df.select(array_cat (col(" a"  ), col(" b"  )).alias(" concatenated_array"  )) 
124124
125125 In this example, the `concatenated_array ` column will contain `[1, 2, 3, 4, 5, 6] `.
126126
127- To repeat the elements of an array a specified number of times, you can use the function :py:func: `datafusion.functions.list_repeat  `.
127+ To repeat the elements of an array a specified number of times, you can use the function :py:func: `datafusion.functions.array_repeat  `.
128128This function returns a new array with the elements repeated.
129129
130130.. ipython :: python 
131131
132132    from  datafusion import  SessionContext, col, literal 
133-     from  datafusion.functions import  list_repeat  
133+     from  datafusion.functions import  array_repeat  
134134
135135    ctx =  SessionContext() 
136136    df =  ctx.from_pydict({" a"  : [[1 , 2 , 3 ]]}) 
137-     df.select(list_repeat (col(" a"  ), literal(2 )).alias(" repeated_array"  )) 
137+     df.select(array_repeat (col(" a"  ), literal(2 )).alias(" repeated_array"  )) 
138138
139139 In this example, the `repeated_array ` column will contain `[[1, 2, 3], [1, 2, 3]] `.
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