Dataframe format :
ID party test MRK Bundle Entity
0 16069518 Australia 4538 4508329.38 abc
1 15907047 India 7595 -24646.59 cbd
2 1890070 Canada 3481 21556268.87 xyz
3 10978227 America 7595 -258747.70 yac
4 13968376 Italy 6310 146648.45 gbc
While transferring the above dataframe to txt, the txt should be in the below format
Required format in txt with spacing:
ID party test MRK Bundle ID Entity
16069518 Australia 4538 4508329.38 abc
15907047 India 7595 -24646.59 cbd
1890070 Canada 3481 21556268.87 xyz
10978227 America 7595 -258747.70 yac
13968376 Italy 6310 146648.45 gbc
The column space width between ID and party -> I in ID should start from 1st position and y in party should end at 42nd position), plus the data in the ID and party column should align as mentioned above.
The column space width between ID and test, t in test should end at 93rd position
The column space width between ID and MRK, K in MRK should end at 114th position)
The column space width between ID and Bundle ID -> D in Bundle ID should end at 134th position
The column space width between ID and Entity -> y in Entity should end at 151st position
The data in ID column should be left aligned and for the other columns it should be right aligned.
Can you help me to generate the python code to reflect the data in the above txt format? Thanks a lot for your help
Dataframe: Required txt Format enter image description here
CodePudding user response：
The C %-style formatting is discouraged, but it still makes some sense when doing columnar formats like this.
import pandas as pd
columns = ["ID","party","test","MRK","Bundle","Entity"]
data = [
[ 16069518, "Australia", 4538,4508329.38,"","abc"],
[ 15907047, "India", 7595,-24646.59, "","cbd"],
[ 1890070, "Canada", 3481,21556268.87,"","xyz"],
[ 10978227, "America", 7595,-258747.70 ,"","yac"],
[ 13968376, "Italy", 6310,146648.45, "","gbc"],
]
df = pd.DataFrame(data, columns=columns)
print(df)
fmth = "%-10s2sPs!s ss"
fmt = "%-10d2sPd!.2f ss"
with open('outfile.txt','w') as out:
print(fmth % tuple(columns), file=out)
for n,row in df.iterrows():
print(fmt % (row['ID'],row['party'],row['test'],row['MRK'],row['Bundle'],row['Entity']), file=out)
Output:
ID party test MRK Bundle Entity
0 16069518 Australia 4538 4508329.38 abc
1 15907047 India 7595 -24646.59 cbd
2 1890070 Canada 3481 21556268.87 xyz
3 10978227 America 7595 -258747.70 yac
4 13968376 Italy 6310 146648.45 gbc
ID party test MRK Bundle Entity
16069518 Australia 4538 4508329.38 abc
15907047 India 7595 -24646.59 cbd
1890070 Canada 3481 21556268.87 xyz
10978227 America 7595 -258747.70 yac
13968376 Italy 6310 146648.45 gbc
CodePudding user response：
Thank you Tim, below is the script to transfer the data to the txt file
fmth = "%-10s2sPs!s ss"
fmt = "%-10s2sPs!s ss"
columns = ["ID","party","test","MRK","Bundle","Entity"]
column=fmth % tuple(columns)
text_file = open(r"C:\data.txt", "w")
text_file.write(column)
text_file.close()
for n,row in df_decomposed.iterrows():
cleanedList = fmt % (row['ID'], row['party'], row['test'], row['MRK'], row['Bundle'], row['Entity'])
with open(r"C:\data.txt", "a ") as file_object:
file_object.seek(0)
data = file_object.read(100)
if len(data) > 0 :
file_object.write("\n")
file_object.write(cleanedList)