# NumPy Tutorial: NumPy Tile | tile – Part 7

numpy tile
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Hey hello welcome to my seventh video of number tutorial series in this video we are going to talk about the function tile so what is Tyler Tyler is a number function which creates and you know by original your input and make a rehabilitation of it based on the input you give so lets see how it works this V and the CD parameters for shift tap-tap so this will give you the overview of explanation like what the input is required and how you put those things you can see from this combination okay first off it is array or array like or tuple input you can reputation how many want so lets say create a first a and B load a range Ill say five now my array will have three elements 0 1 2 ok so Ill make the exact copy of it by then first parameter is your array which you want to make a copy of then number of rehabilitation so in this case I am giving two so yes if you see two set of the same values I have good so thats what tile is all about so this function is like handling one dimensional it will be faster I will say three and you might ask if this can be done for multi-dimensional arrays yes it is possible lets create a 2d or two dimensional array and see how it works on multi-dimensional lets say B n P dot a range create three random values and we create six random values and lets reshape it to three per reshape it to three by two array and P is notified now B has 3 rows and 2 columns lets lets do a reputation using this impede or tile pass the variable P and then lets say 2 copies we want and as you can see it has created made a copy of the same array across so thats how it works by default the copies are made originally like added as a new column so if you want Row is operation or downwards you want to make a copy that also you can do lets say in P dot tile be and I want to make downloads three copies and to copy a cross so as you can see I have three set of values downwards and one cert across so thats all about non PIs tile function thank you all for watching see you on the next video bye tags:
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