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 18 58 1 35
4 19 54 2 70
I want to write this data to a text file that looks like this:
18 55 1 70
18 55 2 67
18 57 2 75
18 58 1 35
19 54 2 70
I have tried something like
f = open(writePath, 'a')
f.writelines(['\n', str(data['X']), ' ', str(data['Y']), ' ', str(data['Z']), ' ', str(data['Value'])])
f.close()
but it's not working. How to do this?
You can use pandas.DataFrame.to_csv(), and setting both index
and header
to False
:
In [97]: print df.to_csv(sep=' ', index=False, header=False)
18 55 1 70
18 55 2 67
18 57 2 75
18 58 1 35
19 54 2 70
pandas.DataFrame.to_csv
can write to a file directly, for more info you can refer to the docs linked above.
@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')
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
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.
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.
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.
Source: Stackoverflow.com