On Thursday, May 28, 2020 at 11:20:05 AM UTC+5:30, Rahul Gupta wrote:
> I am having a Ubuntu system which has 125 Gb of RAM. I executed few python
> scripts on that system. Those scripts uses numpy arrays and pandas. Now
> execution was over but still 50 gb of RAM and 2 Gb cache and
I am having a Ubuntu system which has 125 Gb of RAM. I executed few python
scripts on that system. Those scripts uses numpy arrays and pandas. Now
execution was over but still 50 gb of RAM and 2 Gb cache and 8.4 Gb of swap is
occupied. At this moment nothing is running on the system. I have go
@peter Otten thanks
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consider the following code
import csv
import numpy as np
with open("D:\PHD\obranking\\demo.csv", mode='r') as csv_file1,
open("D:\PHD\obranking\\demo.csv", mode='r') as csv_file2:
csv_reader1 = csv.DictReader(csv_file1)
csv_reader2 = csv.DictReader(csv_file2)
filename = "cell_split
FOLLWOING IS MY CODE
import pandas as pd
import csv
from sklearn.preprocessing import LabelEncoder
from sklearn.feature_selection import chi2
with open("D:\PHD\obranking\\test_chi.csv", 'w') as csvfilew1:
fields = ['index', 'feature name', 'p_value']
csvwriter1 = csv.DictWriter(csvfilew1, f
chi value for 10th column but for most of the columns it
is behaving like below "C:\Users\Rahul
Gupta\PycharmProjects\CSVLearn\venv\Scripts\python.exe" "C:/Users/Rahul
Gupta/PycharmProjects/CSVLearn/ChiSq_learn.py" (array([nan]), array([nan]))
Process finished with exit c
i wanted to implement incremental PCA.
Got this code for stack overflow but i am wondering what y = chunk.pop("y")
does and what is this argument "y" to pop
from sklearn.decomposition import IncrementalPCA
import csv
import sys
import numpy as np
import pandas as pd
dataset = sys.argv[1]
chunksiz
64 bit version
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Hello all, i have a csv of 1 gb which consists of 25000 columns and 2 rows.
I want to apply pca so i have seen sciki-learn had inbuilt fucntionality to use
that. But i have seen to do eo you have to load data in data frame. But my
machine is i5 with 8 gb of ram which fails to load all this d
@Peter Thanks alot
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import csv
import numpy as np
with open("D:\PHD\obranking\\cell_split_demo.csv", mode='r') as csv_file:
csv_reader = csv.DictReader(csv_file)
print(csv_reader.fieldnames)
col_count = print(len(csv_reader.fieldnames))
#print(sum(1 for row in csv_file))
row_count = 0
On Sunday, April 12, 2020 at 1:35:10 PM UTC+5:30, Rahul Gupta wrote:
> the cells in my csv that i wrote looks likes this
> ['82#201#426#553#602#621#811#908#1289#1342#1401#1472#1593#1641#1794#2290#2341#2391#3023#3141#3227#3240#3525#3529#3690#3881#4406#4421#4497#4719#4722#4920#505
the cells in my csv that i wrote looks likes this
['82#201#426#553#602#621#811#908#1289#1342#1401#1472#1593#1641#1794#2290#2341#2391#3023#3141#3227#3240#3525#3529#3690#3881#4406#4421#4497#4719#4722#4920#5053#5146#5433']
and the cells which are empty looks like ['']
i have tried the following code
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