pandas-4. read_csv, unique, to_csv, file upload, file download

• read_csv

- sep : Separator

- names : List of column names to use.

- header : To use as the column names, and the start of the data. If column names are passed explicitly then the behavior is identical to header=None.

- low_memory : It results mixed type inference, so set False to ensure no mixed type.

columns=['user_id', 'item_id', 'rating', 'timestamp']
df=pd.read_csv('./u.data',sep='\t', names=columns, low_memory=False)
df.head()
>>>
	user_id	item_id	rating	timestamp
0	196	242	3	881250949
1	186	302	3	891717742
2	22	377	1	878887116

 

• unique

Return unique values.

pd.unique(pd.Series([1,3,1,5]))
>>>
array([1, 3, 5])

 

• to_csv

Write object to a csv file.

1. First way, using colab : download it to my local via colab.

import pandas as pd
from google.colab import files
uploaded = files.upload()

df_100=df[:100]
df_100.to_csv('df_100.csv')
files.download('df_100.csv')

 

2. Second way

df_result=df.to_csv('df.csv')