Simplified README Examples (#15338)

Pandas will automatically perform fetches for paths detected as URLs. No need for `requests` and `StringIO`. A marginal change, but this makes the docs a bit simpler.

Authors:
  - William Kaiser (https://github.com/wkaisertexas)
  - Vyas Ramasubramani (https://github.com/vyasr)

Approvers:
  - Vyas Ramasubramani (https://github.com/vyasr)

URL: #15338

README.md

@@ -14,13 +14,8 @@ You can import `cudf` directly and use it like `pandas`:
 
 ```python
 import cudf
-import requests
-from io import StringIO
 
-url = "https://github.com/plotly/datasets/raw/master/tips.csv"
-content = requests.get(url).content.decode("utf-8")
-
-tips_df = cudf.read_csv(StringIO(content))
+tips_df = cudf.read_csv("https://github.com/plotly/datasets/raw/master/tips.csv")
 tips_df["tip_percentage"] = tips_df["tip"] / tips_df["total_bill"] * 100
 
 # display average tip by dining party size
@@ -36,13 +31,8 @@ supported operations and falling back to pandas when needed:
 %load_ext cudf.pandas  # pandas operations now use the GPU!
 
 import pandas as pd
-import requests
-from io import StringIO
-
-url = "https://github.com/plotly/datasets/raw/master/tips.csv"
-content = requests.get(url).content.decode("utf-8")
 
-tips_df = pd.read_csv(StringIO(content))
+tips_df = pd.read_csv("https://github.com/plotly/datasets/raw/master/tips.csv")
 tips_df["tip_percentage"] = tips_df["tip"] / tips_df["total_bill"] * 100
 
 # display average tip by dining party size