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df to file fully implemented and working

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Signed-off-by: Dipti <dipti.dhond@candelatech.com>
This commit is contained in:
Dipti
2021-02-17 01:36:24 -08:00
parent 336241ff77
commit 9db0c32b38
3 changed files with 15 additions and 42 deletions
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49
py-json/LANforge/lfcli_base.py
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@@ -16,6 +16,8 @@ from LANforge import LFRequest
import LANforge.LFRequest
import csv
import pandas as pd
import tables
import pyarrow as pa
#import xlsxwriter
class LFCliBase:
@@ -599,55 +601,28 @@ class LFCliBase:
abgnAX : 12,
bgnAX : 13
"""
# def write_to_csv_file(self,new_data_list=None, num_cols=0, csvwriter=None,debug=False):
# if num_cols == 0:
# raise ValueError("Number of columns cannot be zero. Exiting script.")
# exit(1)
# if type(new_data_list) is not list:
# raise ValueError("Data type passed to write into CSV is not a list. Exiting script.")
# exit(1)
# if debug:
# print("Writing data : ")
# print(new_data_list)
# indiv_data_line=[]
# col_counter_per_line=0
# for data_value in new_data_list:
# if col_counter_per_line >= num_cols:
# if debug:
# print(indiv_data_line)
# csvwriter.writerow(indiv_data_line)
# col_counter_per_line=0
# indiv_data_line.clear()
# indiv_data_line.append(data_value)
# col_counter_per_line += 1
#================ Pandas Dataframe Functions ======================================
#takes any dataframe and returns the specified file extension of it
def df_to_file(self, output_f=None,dataframe=None, save_path=None):
df = dataframe
#pd.set_option("display.max_rows", None, "display.max_columns", None)
#print(df)
if output_f.lower() == 'hdf':
df.to_hdf(save_path, 'table', append=True)
if output_f.lower() == 'hdf':
dataframe.to_hdf(save_path.replace('csv','h5',1), 'table', append=True)
if output_f.lower() == 'parquet':
df.to_parquet(save_path, engine='pyarrow')
dataframe.to_parquet(save_path.replace('csv','parquet',1), engine='pyarrow')
if output_f.lower() == 'png':
fig = df.plot().get_figure()
fig.savefig(save_path)
fig = dataframe.plot().get_figure()
fig.savefig(save_path.replace('csv','png',1))
if output_f.lower() == 'xlsx':
df.to_excel(save_path)
if output_f.lower() == 'df':
df
dataframe.to_excel(save_path.replace('csv','xlsx',1))
if output_f.lower() == 'json':
df.to_json(save_path)
dataframe.to_json(save_path.replace('csv','json',1))
if output_f.lower() == 'stata':
df.to_stata(save_path)
dataframe.to_stata(save_path.replace('csv','dta',1))
if output_f.lower() == 'pickle':
df.to_pickle(save_path)
dataframe.to_pickle(save_path.replace('csv','pkl',1))
if output_f.lower() == 'html':
df.to_html(save_path)
dataframe.to_html(save_path.replace('csv','html',1))
#takes any format of a file and returns a dataframe of it
def file_to_df(self,file_name):