from frovedis.dataframe.df import FrovedisDataframe
FrovedisServer.initialize("mpirun -np 2 {}".format(
os.environ['FROVEDIS_SERVER']))
data = {
'A': [10, 12, 13, 15],
'B': [10.23, 12.20, 34.90, 100.12],
'C': ['male', 'female', 'female', 'male'],
}
pdf = pd.DataFrame(data)
df = FrovedisDataframe(pdf)
print(pdf)
print
row_mat = df.to_frovedis_rowmajor_matrix(['A', 'B'], dtype=np.float64)
print(row_mat.to_numpy_matrix())
print
#col_mat = df.to_frovedis_colmajor_matrix(['A', 'B'], dtype=np.float64)
#print (col_mat.to_numpy_matrix())
crs_mat, info = df.to_frovedis_crs_matrix(['A', 'B', 'C'], ['C'],
need_info=True)
crs_mat.debug_print()
print
data2 = {
'A': [12, 13],
'B': [34.56, 78.9],
'C': ['male', 'male'],
'one': [10, 12, 13, 15],
'two': [10.23, 12.20, 34.90, 100.12],
'three': ['F', 'F', 'D', 'A'],
'four': [0, 0, 1, 2]
}
pdf = pd.DataFrame(data)
print(pdf.describe())
print("\n")
df = FrovedisDataframe(pdf)
print(df.describe())
print("\n") # prints count, mean, std, sum, min, max
# matrix conversion demo
df.show()
row_mat = df.to_frovedis_rowmajor_matrix(['one', 'two'], dtype=np.float64)
row_mat.debug_print()
col_mat = df.to_frovedis_colmajor_matrix(['one',
'two']) # default dtype = float32
col_mat.debug_print()
crs_mat, info = df.to_frovedis_crs_matrix(
['one', 'two', 'four'], ['four'],
need_info=True) # default dtype = float32
crs_mat.debug_print()
crs_mat2 = df.to_frovedis_crs_matrix_using_info(info)
crs_mat2.debug_print()
df.release()