How to append the result from each iteration into the CSV file?

I am sending the numerical field into for loop and calculating the max, min and percentile. I want to store each result (last print statement) into the csv file. I am literally struck here.

Each iteration in the for loop prints result like below:

emp_id, 10, 23, 45.4

I want to save these results in a csv file.

import pandas as pd

import numpy as np



data = pd.read_csv(r'C:Usersspanda031Downloadstest_19.csv')

#abc=data.dtypes

#print(abc)

df = data.select_dtypes(include='number')

cols = df.columns.values

print(cols)

arr = df.values

#print("new array ", arr)

#with open(r'C:Usersspanda031Downloadstest_19.csv') as f:

#    d_reader = csv.DictReader(f)



    #get fieldnames from DictReader object and store in list

#    headers = d_reader.fieldnames

#    print(headers)

for line in cols:

        #print value in MyCol1 for each row

        #print(line)        

        v3=np.array(data[line])

        #print(v3)        

        print(line,",",v3.min(),",",v3.max(),",",np.percentile(v3, 25))

edited Nov 15 '18 at 18:01

martineau

69.1k1092186

asked Nov 15 '18 at 17:07

Shankar Panda

1741115

1

You're probably looking for either the csv module or the numpy tofile functionality

– G. Anderson
Nov 15 '18 at 17:13

You can use python your_script.py >> your_file.csv to append to an existing file.

– Austin Salonen
Nov 15 '18 at 17:19

Actually i am going to run the python script as standalone resource and i will create hive table on top of that csv file

– Shankar Panda
Nov 15 '18 at 17:20

add a comment |

I am sending the numerical field into for loop and calculating the max, min and percentile. I want to store each result (last print statement) into the csv file. I am literally struck here.

Each iteration in the for loop prints result like below:

emp_id, 10, 23, 45.4

I want to save these results in a csv file.

import pandas as pd

import numpy as np



data = pd.read_csv(r'C:Usersspanda031Downloadstest_19.csv')

#abc=data.dtypes

#print(abc)

df = data.select_dtypes(include='number')

cols = df.columns.values

print(cols)

arr = df.values

#print("new array ", arr)

#with open(r'C:Usersspanda031Downloadstest_19.csv') as f:

#    d_reader = csv.DictReader(f)



    #get fieldnames from DictReader object and store in list

#    headers = d_reader.fieldnames

#    print(headers)

for line in cols:

        #print value in MyCol1 for each row

        #print(line)        

        v3=np.array(data[line])

        #print(v3)        

        print(line,",",v3.min(),",",v3.max(),",",np.percentile(v3, 25))

edited Nov 15 '18 at 18:01

martineau

69.1k1092186

asked Nov 15 '18 at 17:07

Shankar Panda

1741115

1

You're probably looking for either the csv module or the numpy tofile functionality

– G. Anderson
Nov 15 '18 at 17:13

You can use python your_script.py >> your_file.csv to append to an existing file.

– Austin Salonen
Nov 15 '18 at 17:19

Actually i am going to run the python script as standalone resource and i will create hive table on top of that csv file

– Shankar Panda
Nov 15 '18 at 17:20

add a comment |

I am sending the numerical field into for loop and calculating the max, min and percentile. I want to store each result (last print statement) into the csv file. I am literally struck here.

Each iteration in the for loop prints result like below:

emp_id, 10, 23, 45.4

I want to save these results in a csv file.

import pandas as pd

import numpy as np



data = pd.read_csv(r'C:Usersspanda031Downloadstest_19.csv')

#abc=data.dtypes

#print(abc)

df = data.select_dtypes(include='number')

cols = df.columns.values

print(cols)

arr = df.values

#print("new array ", arr)

#with open(r'C:Usersspanda031Downloadstest_19.csv') as f:

#    d_reader = csv.DictReader(f)



    #get fieldnames from DictReader object and store in list

#    headers = d_reader.fieldnames

#    print(headers)

for line in cols:

        #print value in MyCol1 for each row

        #print(line)        

        v3=np.array(data[line])

        #print(v3)        

        print(line,",",v3.min(),",",v3.max(),",",np.percentile(v3, 25))

edited Nov 15 '18 at 18:01

martineau

69.1k1092186

asked Nov 15 '18 at 17:07

Shankar Panda

1741115

I am sending the numerical field into for loop and calculating the max, min and percentile. I want to store each result (last print statement) into the csv file. I am literally struck here.

Each iteration in the for loop prints result like below:

emp_id, 10, 23, 45.4

I want to save these results in a csv file.

import pandas as pd

import numpy as np



data = pd.read_csv(r'C:Usersspanda031Downloadstest_19.csv')

#abc=data.dtypes

#print(abc)

df = data.select_dtypes(include='number')

cols = df.columns.values

print(cols)

arr = df.values

#print("new array ", arr)

#with open(r'C:Usersspanda031Downloadstest_19.csv') as f:

#    d_reader = csv.DictReader(f)



    #get fieldnames from DictReader object and store in list

#    headers = d_reader.fieldnames

#    print(headers)

for line in cols:

        #print value in MyCol1 for each row

        #print(line)        

        v3=np.array(data[line])

        #print(v3)        

        print(line,",",v3.min(),",",v3.max(),",",np.percentile(v3, 25))

python pandas dataframe

edited Nov 15 '18 at 18:01

martineau

69.1k1092186

asked Nov 15 '18 at 17:07

Shankar Panda

1741115

edited Nov 15 '18 at 18:01

martineau

69.1k1092186

asked Nov 15 '18 at 17:07

Shankar Panda

1741115

edited Nov 15 '18 at 18:01

martineau

69.1k1092186

edited Nov 15 '18 at 18:01

martineau

69.1k1092186

edited Nov 15 '18 at 18:01

martineau

69.1k1092186

asked Nov 15 '18 at 17:07

Shankar Panda

1741115

asked Nov 15 '18 at 17:07

Shankar Panda

1741115

asked Nov 15 '18 at 17:07

Shankar Panda

1741115

1

You're probably looking for either the csv module or the numpy tofile functionality

– G. Anderson
Nov 15 '18 at 17:13

You can use python your_script.py >> your_file.csv to append to an existing file.

– Austin Salonen
Nov 15 '18 at 17:19

Actually i am going to run the python script as standalone resource and i will create hive table on top of that csv file

– Shankar Panda
Nov 15 '18 at 17:20

add a comment |

1

You're probably looking for either the csv module or the numpy tofile functionality

– G. Anderson
Nov 15 '18 at 17:13

You can use python your_script.py >> your_file.csv to append to an existing file.

– Austin Salonen
Nov 15 '18 at 17:19

Actually i am going to run the python script as standalone resource and i will create hive table on top of that csv file

– Shankar Panda
Nov 15 '18 at 17:20

You're probably looking for either the csv module or the numpy tofile functionality

– G. Anderson
Nov 15 '18 at 17:13

You can use python your_script.py >> your_file.csv to append to an existing file.

– Austin Salonen
Nov 15 '18 at 17:19

Actually i am going to run the python script as standalone resource and i will create hive table on top of that csv file

– Shankar Panda
Nov 15 '18 at 17:20

add a comment |

1 Answer
1

active

oldest

votes

This way i could resolve it.

res_df=line,v3.min(),v3.max(),np.percentile(v3, 25),np.std(v3)      

    with open('C:\Users\spanda031\Downloads\abccc.csv', 'a', newline='') as csvfile:

        writerows = csv.writer(csvfile, delimiter=',',

                        quotechar='"', quoting=csv.QUOTE_MINIMAL)

        writerows.writerow(map(lambda x: x, res_df))

answered Nov 15 '18 at 17:59

Shankar Panda

1741115

add a comment |

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1 Answer
1

active

oldest

votes

1 Answer
1

active

oldest

votes

This way i could resolve it.

res_df=line,v3.min(),v3.max(),np.percentile(v3, 25),np.std(v3)      

    with open('C:\Users\spanda031\Downloads\abccc.csv', 'a', newline='') as csvfile:

        writerows = csv.writer(csvfile, delimiter=',',

                        quotechar='"', quoting=csv.QUOTE_MINIMAL)

        writerows.writerow(map(lambda x: x, res_df))

answered Nov 15 '18 at 17:59

Shankar Panda

1741115

add a comment |

This way i could resolve it.

res_df=line,v3.min(),v3.max(),np.percentile(v3, 25),np.std(v3)      

    with open('C:\Users\spanda031\Downloads\abccc.csv', 'a', newline='') as csvfile:

        writerows = csv.writer(csvfile, delimiter=',',

                        quotechar='"', quoting=csv.QUOTE_MINIMAL)

        writerows.writerow(map(lambda x: x, res_df))

answered Nov 15 '18 at 17:59

Shankar Panda

1741115

add a comment |

This way i could resolve it.

res_df=line,v3.min(),v3.max(),np.percentile(v3, 25),np.std(v3)      

    with open('C:\Users\spanda031\Downloads\abccc.csv', 'a', newline='') as csvfile:

        writerows = csv.writer(csvfile, delimiter=',',

                        quotechar='"', quoting=csv.QUOTE_MINIMAL)

        writerows.writerow(map(lambda x: x, res_df))

answered Nov 15 '18 at 17:59

Shankar Panda

1741115

This way i could resolve it.

res_df=line,v3.min(),v3.max(),np.percentile(v3, 25),np.std(v3)      

    with open('C:\Users\spanda031\Downloads\abccc.csv', 'a', newline='') as csvfile:

        writerows = csv.writer(csvfile, delimiter=',',

                        quotechar='"', quoting=csv.QUOTE_MINIMAL)

        writerows.writerow(map(lambda x: x, res_df))

answered Nov 15 '18 at 17:59

Shankar Panda

1741115

answered Nov 15 '18 at 17:59

Shankar Panda

1741115

answered Nov 15 '18 at 17:59

Shankar Panda

1741115

answered Nov 15 '18 at 17:59

Shankar Panda

1741115

add a comment |

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