def __convert_to_df(self, data):
"""
NAME: __convert_to_df
"""
tid = []
item = []
cur_id = 0
for trans in data: # for each transaction in data
for trans_it in trans: # for each item in each transaction
tid.append(cur_id)
item.append(trans_it)
cur_id = cur_id + 1
tid = np.asarray(tid, dtype=np.int32)
item = np.asarray(item, dtype=np.int32)
df_t = pd.DataFrame({'trans_id': tid, 'item': item}, \
columns=['trans_id', 'item'])
return FrovedisDataframe(df_t)
import os
import numpy as np
import pandas as pd
from frovedis.exrpc.server import FrovedisServer
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
FrovedisServer.initialize(argvs[1])
peopleDF = {
'Ename': ['Michael', 'Andy', 'Tanaka', 'Raul', 'Yuta'],
'Age': [29, 30, 27, 19, 31],
'Country': ['USA', 'England', 'Japan', 'France', 'Japan']
}
countryDF = {
'Ccode': [1, 2, 3, 4],
'Country': ['USA', 'England', 'Japan', 'France']
}
pdf1 = pd.DataFrame(peopleDF)
pdf2 = pd.DataFrame(countryDF)
fdf1 = FrovedisDataframe(pdf1)
fdf2 = FrovedisDataframe(pdf2)
# displaying created frovedis dataframes
fdf1.show()
fdf2.show()
# select demo
fdf1["Ename"].show() # single column
fdf1[["Ename", "Age"]].show() # multiple column
# filter demo
fdf1[fdf1.Age > 19].show()
fdf1[fdf1.Age > 19 and fdf1.Country == 'Japan'].show()
# sort demo
FrovedisServer.initialize(argvs[1])
peopleDF = {
'Ename': ['Michael', 'Andy', 'Tanaka', 'Raul', 'Yuta'],
'Age': [29, 30, 27, 19, 31],
'Country': ['USA', 'England', 'Japan', 'France', 'Japan']
}
countryDF = {
'Ccode': [1, 2, 3, 4],
'Country': ['USA', 'England', 'Japan', 'France']
}
pdf1 = pd.DataFrame(peopleDF)
pdf2 = pd.DataFrame(countryDF)
fdf1 = FrovedisDataframe(pdf1)
fdf2 = FrovedisDataframe(pdf2)
# displaying created frovedis dataframes
fdf1.show()
fdf2.show()
# select demo
fdf1["Ename"].show() # single column
fdf1[["Ename", "Age"]].show() # multiple column
# filter demo
fdf1[fdf1.Age > 19].show()
fdf1[fdf1.Age > 19 and fdf1.Country == 'Japan'].show()
# sort demo
FrovedisServer.initialize("mpirun -np 2 {}".format(os.environ['FROVEDIS_SERVER']))
peopleDF = {
'Ename' : ['Michael', 'Andy', 'Tanaka', 'Raul', 'Yuta'],
'Age' : [29, 30, 27, 19, 31],
'Country' : ['USA', 'England', 'Japan', 'France', 'Japan']
}
countryDF = {
'Ccode' : [1, 2, 3, 4],
'Country' : ['USA', 'England', 'Japan', 'France']
}
pdf1 = pd.DataFrame(peopleDF)
pdf2 = pd.DataFrame(countryDF)
fdf1 = FrovedisDataframe(pdf1)
fdf2 = FrovedisDataframe(pdf2)
# display created frovedis dataframes
print ("* print Frovedis DataFrame")
fdf1.show()
fdf2.show()
# select demo
print ("* select Ename and Age")
fdf1[["Ename","Age"]].show()
# filter demo
print ("* filter by Age > 19 and Contry == 'Japan'")
fdf1[fdf1.Age > 19 and fdf1.Country == 'Japan'].show()