Panda Dataframe 中的随机行大写

Question

I'm making a reverse denoisng autoencoder and I have a dataset but it's all lowercased, but I want 80% of the rows the source entry to be capitalized and only 60% of the target entries to be capitalized. I wrote this

import pandas as pd
import torch

df = pd.read_csv('Data/fb_moe.csv')

for i in range(len(df)):
    sample = int(torch.distributions.Bernoulli(torch.FloatTensor([.8])).sample())

    if sample == 1:
        df.iloc[i].y = str(df.iloc[i].y).capitalize()

        sample_1 = int(torch.distributions.Bernoulli(torch.FloatTensor([.6])).sample())

        if sample_1 == 1:
            df.iloc[i].x = str(df.iloc[i].x).capitalize()

df.to_csv('Data/fb_moe2.csv')

But this is pretty slow cause my csv is like 8 million rows is there a faster way to do this?

Part of the Dataframe

x,y
jon,jun
an,jun
ju,jun
jin,jun
nun,jun
un,jun
jon,jun
jin,jun
nen,jun
ju,jun
jn,jun
jul,jun
jen,jun
hun,jun
ju,jun
hun,jun
hun,jun
jon,jun
jin,jun
un,jun
eun,jun
jhn,jun

Answer 1

Try adding some boolean mask and some apply functions, pandas does not behave quickly in for loops

n = len(df)
source = np.random.binomial(1, p=.8, size=n) ==  1
target = source.copy()

total_source_true = np.sum(source)
target[source] = np.random.binomial(1, p=.6, size=total_source_true) == 1

df.loc[source, 'x'] = df.loc[source, 'x'].str.capitalize()
df.loc[target, 'y'] = df.loc[source, 'y'].str.capitalize()