Python, Pandas : write content of DataFrame into text File

Question

I have pandas DataFrame like this

        X    Y  Z    Value 
0      18   55  1      70   
1      18   55  2      67 
2      18   57  2      75     
3      1         


        

Answer 1

I used a slightly modified version:

with open(file_name, 'w', encoding = 'utf-8') as f:
    for rec_index, rec in df.iterrows():
        f.write(rec['<field>'] + '\n')

I had to write the contents of a dataframe field (that was delimited) as a text file.

Answer 2

Late to the party: Try this>

base_filename = 'Values.txt'
with open(os.path.join(WorkingFolder, base_filename),'w') as outfile:
    df.to_string(outfile)
#Neatly allocate all columns and rows to a .txt file

Answer 3

The current best way to do this is to use df.to_string() :

with open(writePath, 'a') as f:
    f.write(
        df.to_string(header = False, index = False)
    )

Will output the following

18 55 1 70   
18 55 2 67 
18 57 2 75     
18 58 1 35  
19 54 2 70 

This method also lets you easily choose which columns to print with the columns attribute, lets you keep the column, index labels if you wish, and has other attributes for spacing ect.

Answer 4

@AHegde - To get the tab delimited output use separator sep='\t'.

For df.to_csv:

df.to_csv(r'c:\data\pandas.txt', header=None, index=None, sep='\t', mode='a')

For np.savetxt:

np.savetxt(r'c:\data\np.txt', df.values, fmt='%d', delimiter='\t')

Answer 5

You can just use np.savetxt and access the np attribute .values:

np.savetxt(r'c:\data\np.txt', df.values, fmt='%d')

yields:

18 55 1 70
18 55 2 67
18 57 2 75
18 58 1 35
19 54 2 70

or to_csv:

df.to_csv(r'c:\data\pandas.txt', header=None, index=None, sep=' ', mode='a')

Note for np.savetxt you'd have to pass a filehandle that has been created with append mode.

Answer 6

Way to get Excel data to text file in tab delimited form. Need to use Pandas as well as xlrd.

import pandas as pd
import xlrd
import os

Path="C:\downloads"
wb = pd.ExcelFile(Path+"\\input.xlsx", engine=None)
sheet2 = pd.read_excel(wb, sheet_name="Sheet1")
Excel_Filter=sheet2[sheet2['Name']=='Test']
Excel_Filter.to_excel("C:\downloads\\output.xlsx", index=None)
wb2=xlrd.open_workbook(Path+"\\output.xlsx")
df=wb2.sheet_by_name("Sheet1")
x=df.nrows
y=df.ncols

for i in range(0,x):
    for j in range(0,y):
        A=str(df.cell_value(i,j))
        f=open(Path+"\\emails.txt", "a")
        f.write(A+"\t")
        f.close()
    f=open(Path+"\\emails.txt", "a")
    f.write("\n")
    f.close()
os.remove(Path+"\\output.xlsx")
print(Excel_Filter)

We need to first generate the xlsx file with filtered data and then convert the information into a text file.

Depending on requirements, we can use \n \t for loops and type of data we want in the text file.