CLN: Clean csv files in test data GH34427 (#34458)

Author: najann

doc/source/getting_started/comparison/comparison_with_sas.rst

@@ -115,7 +115,7 @@ Reading external data
 
 Like SAS, pandas provides utilities for reading in data from
 many formats.  The ``tips`` dataset, found within the pandas
-tests (`csv <https://raw.github.com/pandas-dev/pandas/master/pandas/tests/data/tips.csv>`_)
+tests (`csv <https://raw.github.com/pandas-dev/pandas/master/pandas/tests/io/data/csv/tips.csv>`_)
 will be used in many of the following examples.
 
 SAS provides ``PROC IMPORT`` to read csv data into a data set.
@@ -131,7 +131,7 @@ The pandas method is :func:`read_csv`, which works similarly.
 .. ipython:: python
 
    url = ('https://raw.github.com/pandas-dev/'
-          'pandas/master/pandas/tests/data/tips.csv')
+          'pandas/master/pandas/tests/io/data/csv/tips.csv')
    tips = pd.read_csv(url)
    tips.head()
 

doc/source/getting_started/comparison/comparison_with_sql.rst

@@ -25,7 +25,7 @@ structure.
 .. ipython:: python
 
     url = ('https://raw.github.com/pandas-dev'
-           '/pandas/master/pandas/tests/data/tips.csv')
+           '/pandas/master/pandas/tests/io/data/csv/tips.csv')
     tips = pd.read_csv(url)
     tips.head()
 

doc/source/getting_started/comparison/comparison_with_stata.rst

@@ -112,7 +112,7 @@ Reading external data
 
 Like Stata, pandas provides utilities for reading in data from
 many formats.  The ``tips`` data set, found within the pandas
-tests (`csv <https://raw.github.com/pandas-dev/pandas/master/pandas/tests/data/tips.csv>`_)
+tests (`csv <https://raw.github.com/pandas-dev/pandas/master/pandas/tests/io/data/csv/tips.csv>`_)
 will be used in many of the following examples.
 
 Stata provides ``import delimited`` to read csv data into a data set in memory.
@@ -128,7 +128,7 @@ the data set if presented with a url.
 .. ipython:: python
 
    url = ('https://raw.github.com/pandas-dev'
-          '/pandas/master/pandas/tests/data/tips.csv')
+          '/pandas/master/pandas/tests/io/data/csv/tips.csv')
    tips = pd.read_csv(url)
    tips.head()
 

doc/source/user_guide/visualization.rst

@@ -865,7 +865,7 @@ for more information. By coloring these curves differently for each class
 it is possible to visualize data clustering. Curves belonging to samples
 of the same class will usually be closer together and form larger structures.
 
-**Note**: The "Iris" dataset is available `here <https://raw.github.com/pandas-dev/pandas/master/pandas/tests/data/iris.csv>`__.
+**Note**: The "Iris" dataset is available `here <https://raw.github.com/pandas-dev/pandas/master/pandas/tests/io/data/csv/iris.csv>`__.
 
 .. ipython:: python
 
@@ -1025,7 +1025,7 @@ be colored differently.
 See the R package `Radviz <https://cran.r-project.org/package=Radviz/>`__
 for more information.
 
-**Note**: The "Iris" dataset is available `here <https://raw.github.com/pandas-dev/pandas/master/pandas/tests/data/iris.csv>`__.
+**Note**: The "Iris" dataset is available `here <https://raw.github.com/pandas-dev/pandas/master/pandas/tests/io/data/csv/iris.csv>`__.
 
 .. ipython:: python
 

pandas/conftest.py

@@ -813,7 +813,7 @@ def iris(datapath):
     """
     The iris dataset as a DataFrame.
     """
-    return pd.read_csv(datapath("data", "iris.csv"))
+    return pd.read_csv(datapath("io", "data", "csv", "iris.csv"))
 
 
 # ----------------------------------------------------------------

pandas/plotting/_misc.py

@@ -263,7 +263,7 @@ def andrews_curves(
 
         >>> df = pd.read_csv(
         ...     'https://raw.github.com/pandas-dev/'
-        ...     'pandas/master/pandas/tests/data/iris.csv'
+        ...     'pandas/master/pandas/tests/io/data/csv/iris.csv'
         ... )
         >>> pd.plotting.andrews_curves(df, 'Name')
     """
@@ -387,7 +387,7 @@ def parallel_coordinates(
 
         >>> df = pd.read_csv(
         ...     'https://raw.github.com/pandas-dev/'
-        ...     'pandas/master/pandas/tests/data/iris.csv'
+        ...     'pandas/master/pandas/tests/io/data/csv/iris.csv'
         ... )
         >>> pd.plotting.parallel_coordinates(
         ...     df, 'Name', color=('#556270', '#4ECDC4', '#C7F464')