Prepending data in Pandas

Question

I am making a site that will allow you to tweet other's messages. Each message will have its tweets in a csv file. I will loop through the csv file, finding all the tweets for the given message and arranging them into a list.

The thing is, when I loop throught the data, the oldest tweets (the ones at the very start of the file) would appear first in the list. Is there a way to either loop through the pandas DataFrame from bottom to top, or when appending the tweets append them to the very start of the file? Here is my code:


current_message_name = 'Draft Message' # This is the name of the message the user is veiwing right now.

tweets = []
df = pd.read_csv('data/tweets.csv')

for index, row in df.iterrows():
    tweets.append({
    'poster':f'{row["poster"]}',
    'date':f'{row["date"]}',
    'message':f'{row["message"]}',
 })

`df.iloc[::-1]` will reverse the order of the rows. – not_speshal Aug 15 '23 at 17:50 — not_speshal, Aug 15 '23 at 17:50
`tweets.pop()` will get the last item in list. – taller_ExcelHome Aug 15 '23 at 17:52 — taller_ExcelHome, Aug 15 '23 at 17:52

Emma · Answer 1 · 2023-08-15T19:00:52.127

3

Try not to loop in pandas. (ref: Does pandas iterrows have performance issues?)

If you need a list of dictionary, use to_dict.

tweets = df.iloc[::-1][['poster', 'date', 'message']].to_dict(orient='records')

edited Aug 15 '23 at 19:00

answered Aug 15 '23 at 17:53

Emma

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score 1 · Accepted Answer · answered Aug 15 '23 at 17:50

Heres how you can approach it:

current_message_name = 'Draft Message'
tweets = []
df = pd.read_csv('data/tweets.csv')

# Reversing the DataFrame
df = df.iloc[::-1]

for index, row in df.iterrows():
    tweets.append({
        'poster':f'{row["poster"]}',
        'date':f'{row["date"]}',
        'message':f'{row["message"]}',
    })

Prepending data in Pandas

2 Answers2