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The shape attribute for numpy arrays returns the dimensions of the array Here's a look back at the case. If y has n rows and m columns, then y.shape is (n,m)
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3 in python shape [0] returns the dimension but in this code it is returning total number of set Morgan geyser, who stabbed classmate payton leutner at age 12, will remain at a psychiatric hospital for treatment Please can someone tell me work of shape [0] and shape [1]
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For context, this code contains numpy, seaborn, pandas and matplotlib
Below is the line of code Is this a specific feature, or just a quirk? X[0].shape will give the length of 1st row of an array X.shape[0] will give the number of rows in an array
In your case it will give output 10 If you will type x.shape[1], it will print out the number of columns i.e 1024 Print(x.shape, x.dtype, x) however, if x is a long expression, this becomes awkward (obviously, one can create a custom function but i hope to avoid this.)
180 i am trying to find out the size/shape of a dataframe in pyspark
I do not see a single function that can do this In python, i can do this: I'm trying to print the shape of the dataframe using.format in python tried using print statement incorporating.format and.shape commands df_shape = df.shape print (the data has rows {}, col. A tuple is not determined by the parentheses, they are not part of it, but by the comma
X=4, assigns a tuple, x=(4) assigns an int, creating a usual confusion (r,) and (r,1) just add (useless) parentheses but still express respectively 1d and 2d array shapes, parentheses around a tuple force the evaluation order and prevent it to be read as a list of values (e.g It's impossible to answer your question absolutely correctly without knowledge about red_df I could only suppose that it's a pandas.dataframe of unknown shape and data
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