CODEWITHSUNDEEP
pythonpandascsvreadfiledask
Yingqiang Gao
Yingqiang Gao

Reputation: 999

python: how can I read and process a 18GB csv file?

I have a 18GB csv file from measurement and want to do some calculation based on it. I tried to do it with pandas but seems like it takes forever just to read this file.

Following codes are what I did:

df=pd.read_csv('/Users/gaoyingqiang/Desktop/D989_Leistung.csv',usecols=[1,2],sep=';',encoding='gbk',iterator=True,chunksize=1000000)
df=pd.concat(df,ignore_index=True)

U1=df['Kanal 1-1 [V]']
I1=df['Kanal 1-2 [V]']

c=[]
for num in range(0,16333660,333340):
    lu=sum(U1[num:num+333340]*U1[num:num+333340])/333340
    li=sum(I1[num:num+333340]*I1[num:num+333340])/333340
    lui=sum(I1[num:num+333340]*U1[num:num+333340])/333340
    c.append(180*mt.acos(2*lui/mt.sqrt(4*lu*li))/np.pi)
    lu=0
    li=0
    lui=0

phase=pd.DataFrame(c)
phase.to_excel('/Users/gaoyingqiang/Desktop/Phaseverschiebung_1.xlsx',sheet_name='Sheet1')

Is there anyway to accelerate the process?

Upvotes: 0

Views: 230

Answers (1)

jezrael
jezrael

Reputation: 863481

df is a TextFileReader, not DataFrame, so need concat:

df = pd.concat(df, ignore_index=True)

Sample:

import pandas as pd
from pandas.compat import StringIO

temp=u"""id,col1,col2,col3
1,13,15,14
1,13,15,14
1,12,15,13
2,18,15,13
2,18,15,13
2,18,15,13
2,18,15,13
2,18,15,13
2,18,15,13
3,14,15,13
3,14,15,13
3,14,185,213"""
df = pd.read_csv(StringIO(temp), chunksize=3)
print (df)
<pandas.io.parsers.TextFileReader object at 0x000000000D6E2EF0>

df = pd.concat(df, ignore_index=True)
print (df)
    id  col1  col2  col3
0    1    13    15    14
1    1    13    15    14
2    1    12    15    13
3    2    18    15    13
4    2    18    15    13
5    2    18    15    13
6    2    18    15    13
7    2    18    15    13
8    2    18    15    13
9    3    14    15    13
10   3    14    15    13
11   3    14   185   213

Upvotes: 3

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