diff --git a/doc/source/getting_started/comparison/comparison_with_sas.rst b/doc/source/getting_started/comparison/comparison_with_sas.rst
index 4e284fe7b5968..a29c9ec1c3842 100644
--- a/doc/source/getting_started/comparison/comparison_with_sas.rst
+++ b/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()
 
diff --git a/doc/source/getting_started/comparison/comparison_with_sql.rst b/doc/source/getting_started/comparison/comparison_with_sql.rst
index 6a03c06de3699..2efd3b1854491 100644
--- a/doc/source/getting_started/comparison/comparison_with_sql.rst
+++ b/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()
 
diff --git a/doc/source/getting_started/comparison/comparison_with_stata.rst b/doc/source/getting_started/comparison/comparison_with_stata.rst
index fec6bae1e0330..31cb76eea5b46 100644
--- a/doc/source/getting_started/comparison/comparison_with_stata.rst
+++ b/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()
 
diff --git a/doc/source/user_guide/visualization.rst b/doc/source/user_guide/visualization.rst
index 39051440e9d9a..4fde053a2070f 100644
--- a/doc/source/user_guide/visualization.rst
+++ b/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
 
diff --git a/pandas/conftest.py b/pandas/conftest.py
index 9eb2db19064c1..0b5efdc654cb5 100644
--- a/pandas/conftest.py
+++ b/pandas/conftest.py
@@ -401,7 +401,7 @@ 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"))
 
 
 @pytest.fixture(params=["nlargest", "nsmallest"])
diff --git a/pandas/tests/data/iris.csv b/pandas/tests/data/iris.csv
deleted file mode 100644
index c19b9c3688515..0000000000000
--- a/pandas/tests/data/iris.csv
+++ /dev/null
@@ -1,151 +0,0 @@
-SepalLength,SepalWidth,PetalLength,PetalWidth,Name
-5.1,3.5,1.4,0.2,Iris-setosa
-4.9,3.0,1.4,0.2,Iris-setosa
-4.7,3.2,1.3,0.2,Iris-setosa
-4.6,3.1,1.5,0.2,Iris-setosa
-5.0,3.6,1.4,0.2,Iris-setosa
-5.4,3.9,1.7,0.4,Iris-setosa
-4.6,3.4,1.4,0.3,Iris-setosa
-5.0,3.4,1.5,0.2,Iris-setosa
-4.4,2.9,1.4,0.2,Iris-setosa
-4.9,3.1,1.5,0.1,Iris-setosa
-5.4,3.7,1.5,0.2,Iris-setosa
-4.8,3.4,1.6,0.2,Iris-setosa
-4.8,3.0,1.4,0.1,Iris-setosa
-4.3,3.0,1.1,0.1,Iris-setosa
-5.8,4.0,1.2,0.2,Iris-setosa
-5.7,4.4,1.5,0.4,Iris-setosa
-5.4,3.9,1.3,0.4,Iris-setosa
-5.1,3.5,1.4,0.3,Iris-setosa
-5.7,3.8,1.7,0.3,Iris-setosa
-5.1,3.8,1.5,0.3,Iris-setosa
-5.4,3.4,1.7,0.2,Iris-setosa
-5.1,3.7,1.5,0.4,Iris-setosa
-4.6,3.6,1.0,0.2,Iris-setosa
-5.1,3.3,1.7,0.5,Iris-setosa
-4.8,3.4,1.9,0.2,Iris-setosa
-5.0,3.0,1.6,0.2,Iris-setosa
-5.0,3.4,1.6,0.4,Iris-setosa
-5.2,3.5,1.5,0.2,Iris-setosa
-5.2,3.4,1.4,0.2,Iris-setosa
-4.7,3.2,1.6,0.2,Iris-setosa
-4.8,3.1,1.6,0.2,Iris-setosa
-5.4,3.4,1.5,0.4,Iris-setosa
-5.2,4.1,1.5,0.1,Iris-setosa
-5.5,4.2,1.4,0.2,Iris-setosa
-4.9,3.1,1.5,0.1,Iris-setosa
-5.0,3.2,1.2,0.2,Iris-setosa
-5.5,3.5,1.3,0.2,Iris-setosa
-4.9,3.1,1.5,0.1,Iris-setosa
-4.4,3.0,1.3,0.2,Iris-setosa
-5.1,3.4,1.5,0.2,Iris-setosa
-5.0,3.5,1.3,0.3,Iris-setosa
-4.5,2.3,1.3,0.3,Iris-setosa
-4.4,3.2,1.3,0.2,Iris-setosa
-5.0,3.5,1.6,0.6,Iris-setosa
-5.1,3.8,1.9,0.4,Iris-setosa
-4.8,3.0,1.4,0.3,Iris-setosa
-5.1,3.8,1.6,0.2,Iris-setosa
-4.6,3.2,1.4,0.2,Iris-setosa
-5.3,3.7,1.5,0.2,Iris-setosa
-5.0,3.3,1.4,0.2,Iris-setosa
-7.0,3.2,4.7,1.4,Iris-versicolor
-6.4,3.2,4.5,1.5,Iris-versicolor
-6.9,3.1,4.9,1.5,Iris-versicolor
-5.5,2.3,4.0,1.3,Iris-versicolor
-6.5,2.8,4.6,1.5,Iris-versicolor
-5.7,2.8,4.5,1.3,Iris-versicolor
-6.3,3.3,4.7,1.6,Iris-versicolor
-4.9,2.4,3.3,1.0,Iris-versicolor
-6.6,2.9,4.6,1.3,Iris-versicolor
-5.2,2.7,3.9,1.4,Iris-versicolor
-5.0,2.0,3.5,1.0,Iris-versicolor
-5.9,3.0,4.2,1.5,Iris-versicolor
-6.0,2.2,4.0,1.0,Iris-versicolor
-6.1,2.9,4.7,1.4,Iris-versicolor
-5.6,2.9,3.6,1.3,Iris-versicolor
-6.7,3.1,4.4,1.4,Iris-versicolor
-5.6,3.0,4.5,1.5,Iris-versicolor
-5.8,2.7,4.1,1.0,Iris-versicolor
-6.2,2.2,4.5,1.5,Iris-versicolor
-5.6,2.5,3.9,1.1,Iris-versicolor
-5.9,3.2,4.8,1.8,Iris-versicolor
-6.1,2.8,4.0,1.3,Iris-versicolor
-6.3,2.5,4.9,1.5,Iris-versicolor
-6.1,2.8,4.7,1.2,Iris-versicolor
-6.4,2.9,4.3,1.3,Iris-versicolor
-6.6,3.0,4.4,1.4,Iris-versicolor
-6.8,2.8,4.8,1.4,Iris-versicolor
-6.7,3.0,5.0,1.7,Iris-versicolor
-6.0,2.9,4.5,1.5,Iris-versicolor
-5.7,2.6,3.5,1.0,Iris-versicolor
-5.5,2.4,3.8,1.1,Iris-versicolor
-5.5,2.4,3.7,1.0,Iris-versicolor
-5.8,2.7,3.9,1.2,Iris-versicolor
-6.0,2.7,5.1,1.6,Iris-versicolor
-5.4,3.0,4.5,1.5,Iris-versicolor
-6.0,3.4,4.5,1.6,Iris-versicolor
-6.7,3.1,4.7,1.5,Iris-versicolor
-6.3,2.3,4.4,1.3,Iris-versicolor
-5.6,3.0,4.1,1.3,Iris-versicolor
-5.5,2.5,4.0,1.3,Iris-versicolor
-5.5,2.6,4.4,1.2,Iris-versicolor
-6.1,3.0,4.6,1.4,Iris-versicolor
-5.8,2.6,4.0,1.2,Iris-versicolor
-5.0,2.3,3.3,1.0,Iris-versicolor
-5.6,2.7,4.2,1.3,Iris-versicolor
-5.7,3.0,4.2,1.2,Iris-versicolor
-5.7,2.9,4.2,1.3,Iris-versicolor
-6.2,2.9,4.3,1.3,Iris-versicolor
-5.1,2.5,3.0,1.1,Iris-versicolor
-5.7,2.8,4.1,1.3,Iris-versicolor
-6.3,3.3,6.0,2.5,Iris-virginica
-5.8,2.7,5.1,1.9,Iris-virginica
-7.1,3.0,5.9,2.1,Iris-virginica
-6.3,2.9,5.6,1.8,Iris-virginica
-6.5,3.0,5.8,2.2,Iris-virginica
-7.6,3.0,6.6,2.1,Iris-virginica
-4.9,2.5,4.5,1.7,Iris-virginica
-7.3,2.9,6.3,1.8,Iris-virginica
-6.7,2.5,5.8,1.8,Iris-virginica
-7.2,3.6,6.1,2.5,Iris-virginica
-6.5,3.2,5.1,2.0,Iris-virginica
-6.4,2.7,5.3,1.9,Iris-virginica
-6.8,3.0,5.5,2.1,Iris-virginica
-5.7,2.5,5.0,2.0,Iris-virginica
-5.8,2.8,5.1,2.4,Iris-virginica
-6.4,3.2,5.3,2.3,Iris-virginica
-6.5,3.0,5.5,1.8,Iris-virginica
-7.7,3.8,6.7,2.2,Iris-virginica
-7.7,2.6,6.9,2.3,Iris-virginica
-6.0,2.2,5.0,1.5,Iris-virginica
-6.9,3.2,5.7,2.3,Iris-virginica
-5.6,2.8,4.9,2.0,Iris-virginica
-7.7,2.8,6.7,2.0,Iris-virginica
-6.3,2.7,4.9,1.8,Iris-virginica
-6.7,3.3,5.7,2.1,Iris-virginica
-7.2,3.2,6.0,1.8,Iris-virginica
-6.2,2.8,4.8,1.8,Iris-virginica
-6.1,3.0,4.9,1.8,Iris-virginica
-6.4,2.8,5.6,2.1,Iris-virginica
-7.2,3.0,5.8,1.6,Iris-virginica
-7.4,2.8,6.1,1.9,Iris-virginica
-7.9,3.8,6.4,2.0,Iris-virginica
-6.4,2.8,5.6,2.2,Iris-virginica
-6.3,2.8,5.1,1.5,Iris-virginica
-6.1,2.6,5.6,1.4,Iris-virginica
-7.7,3.0,6.1,2.3,Iris-virginica
-6.3,3.4,5.6,2.4,Iris-virginica
-6.4,3.1,5.5,1.8,Iris-virginica
-6.0,3.0,4.8,1.8,Iris-virginica
-6.9,3.1,5.4,2.1,Iris-virginica
-6.7,3.1,5.6,2.4,Iris-virginica
-6.9,3.1,5.1,2.3,Iris-virginica
-5.8,2.7,5.1,1.9,Iris-virginica
-6.8,3.2,5.9,2.3,Iris-virginica
-6.7,3.3,5.7,2.5,Iris-virginica
-6.7,3.0,5.2,2.3,Iris-virginica
-6.3,2.5,5.0,1.9,Iris-virginica
-6.5,3.0,5.2,2.0,Iris-virginica
-6.2,3.4,5.4,2.3,Iris-virginica
-5.9,3.0,5.1,1.8,Iris-virginica
\ No newline at end of file
diff --git a/pandas/tests/data/tips.csv b/pandas/tests/data/tips.csv
deleted file mode 100644
index 856a65a69e647..0000000000000
--- a/pandas/tests/data/tips.csv
+++ /dev/null
@@ -1,245 +0,0 @@
-total_bill,tip,sex,smoker,day,time,size
-16.99,1.01,Female,No,Sun,Dinner,2
-10.34,1.66,Male,No,Sun,Dinner,3
-21.01,3.5,Male,No,Sun,Dinner,3
-23.68,3.31,Male,No,Sun,Dinner,2
-24.59,3.61,Female,No,Sun,Dinner,4
-25.29,4.71,Male,No,Sun,Dinner,4
-8.77,2.0,Male,No,Sun,Dinner,2
-26.88,3.12,Male,No,Sun,Dinner,4
-15.04,1.96,Male,No,Sun,Dinner,2
-14.78,3.23,Male,No,Sun,Dinner,2
-10.27,1.71,Male,No,Sun,Dinner,2
-35.26,5.0,Female,No,Sun,Dinner,4
-15.42,1.57,Male,No,Sun,Dinner,2
-18.43,3.0,Male,No,Sun,Dinner,4
-14.83,3.02,Female,No,Sun,Dinner,2
-21.58,3.92,Male,No,Sun,Dinner,2
-10.33,1.67,Female,No,Sun,Dinner,3
-16.29,3.71,Male,No,Sun,Dinner,3
-16.97,3.5,Female,No,Sun,Dinner,3
-20.65,3.35,Male,No,Sat,Dinner,3
-17.92,4.08,Male,No,Sat,Dinner,2
-20.29,2.75,Female,No,Sat,Dinner,2
-15.77,2.23,Female,No,Sat,Dinner,2
-39.42,7.58,Male,No,Sat,Dinner,4
-19.82,3.18,Male,No,Sat,Dinner,2
-17.81,2.34,Male,No,Sat,Dinner,4
-13.37,2.0,Male,No,Sat,Dinner,2
-12.69,2.0,Male,No,Sat,Dinner,2
-21.7,4.3,Male,No,Sat,Dinner,2
-19.65,3.0,Female,No,Sat,Dinner,2
-9.55,1.45,Male,No,Sat,Dinner,2
-18.35,2.5,Male,No,Sat,Dinner,4
-15.06,3.0,Female,No,Sat,Dinner,2
-20.69,2.45,Female,No,Sat,Dinner,4
-17.78,3.27,Male,No,Sat,Dinner,2
-24.06,3.6,Male,No,Sat,Dinner,3
-16.31,2.0,Male,No,Sat,Dinner,3
-16.93,3.07,Female,No,Sat,Dinner,3
-18.69,2.31,Male,No,Sat,Dinner,3
-31.27,5.0,Male,No,Sat,Dinner,3
-16.04,2.24,Male,No,Sat,Dinner,3
-17.46,2.54,Male,No,Sun,Dinner,2
-13.94,3.06,Male,No,Sun,Dinner,2
-9.68,1.32,Male,No,Sun,Dinner,2
-30.4,5.6,Male,No,Sun,Dinner,4
-18.29,3.0,Male,No,Sun,Dinner,2
-22.23,5.0,Male,No,Sun,Dinner,2
-32.4,6.0,Male,No,Sun,Dinner,4
-28.55,2.05,Male,No,Sun,Dinner,3
-18.04,3.0,Male,No,Sun,Dinner,2
-12.54,2.5,Male,No,Sun,Dinner,2
-10.29,2.6,Female,No,Sun,Dinner,2
-34.81,5.2,Female,No,Sun,Dinner,4
-9.94,1.56,Male,No,Sun,Dinner,2
-25.56,4.34,Male,No,Sun,Dinner,4
-19.49,3.51,Male,No,Sun,Dinner,2
-38.01,3.0,Male,Yes,Sat,Dinner,4
-26.41,1.5,Female,No,Sat,Dinner,2
-11.24,1.76,Male,Yes,Sat,Dinner,2
-48.27,6.73,Male,No,Sat,Dinner,4
-20.29,3.21,Male,Yes,Sat,Dinner,2
-13.81,2.0,Male,Yes,Sat,Dinner,2
-11.02,1.98,Male,Yes,Sat,Dinner,2
-18.29,3.76,Male,Yes,Sat,Dinner,4
-17.59,2.64,Male,No,Sat,Dinner,3
-20.08,3.15,Male,No,Sat,Dinner,3
-16.45,2.47,Female,No,Sat,Dinner,2
-3.07,1.0,Female,Yes,Sat,Dinner,1
-20.23,2.01,Male,No,Sat,Dinner,2
-15.01,2.09,Male,Yes,Sat,Dinner,2
-12.02,1.97,Male,No,Sat,Dinner,2
-17.07,3.0,Female,No,Sat,Dinner,3
-26.86,3.14,Female,Yes,Sat,Dinner,2
-25.28,5.0,Female,Yes,Sat,Dinner,2
-14.73,2.2,Female,No,Sat,Dinner,2
-10.51,1.25,Male,No,Sat,Dinner,2
-17.92,3.08,Male,Yes,Sat,Dinner,2
-27.2,4.0,Male,No,Thur,Lunch,4
-22.76,3.0,Male,No,Thur,Lunch,2
-17.29,2.71,Male,No,Thur,Lunch,2
-19.44,3.0,Male,Yes,Thur,Lunch,2
-16.66,3.4,Male,No,Thur,Lunch,2
-10.07,1.83,Female,No,Thur,Lunch,1
-32.68,5.0,Male,Yes,Thur,Lunch,2
-15.98,2.03,Male,No,Thur,Lunch,2
-34.83,5.17,Female,No,Thur,Lunch,4
-13.03,2.0,Male,No,Thur,Lunch,2
-18.28,4.0,Male,No,Thur,Lunch,2
-24.71,5.85,Male,No,Thur,Lunch,2
-21.16,3.0,Male,No,Thur,Lunch,2
-28.97,3.0,Male,Yes,Fri,Dinner,2
-22.49,3.5,Male,No,Fri,Dinner,2
-5.75,1.0,Female,Yes,Fri,Dinner,2
-16.32,4.3,Female,Yes,Fri,Dinner,2
-22.75,3.25,Female,No,Fri,Dinner,2
-40.17,4.73,Male,Yes,Fri,Dinner,4
-27.28,4.0,Male,Yes,Fri,Dinner,2
-12.03,1.5,Male,Yes,Fri,Dinner,2
-21.01,3.0,Male,Yes,Fri,Dinner,2
-12.46,1.5,Male,No,Fri,Dinner,2
-11.35,2.5,Female,Yes,Fri,Dinner,2
-15.38,3.0,Female,Yes,Fri,Dinner,2
-44.3,2.5,Female,Yes,Sat,Dinner,3
-22.42,3.48,Female,Yes,Sat,Dinner,2
-20.92,4.08,Female,No,Sat,Dinner,2
-15.36,1.64,Male,Yes,Sat,Dinner,2
-20.49,4.06,Male,Yes,Sat,Dinner,2
-25.21,4.29,Male,Yes,Sat,Dinner,2
-18.24,3.76,Male,No,Sat,Dinner,2
-14.31,4.0,Female,Yes,Sat,Dinner,2
-14.0,3.0,Male,No,Sat,Dinner,2
-7.25,1.0,Female,No,Sat,Dinner,1
-38.07,4.0,Male,No,Sun,Dinner,3
-23.95,2.55,Male,No,Sun,Dinner,2
-25.71,4.0,Female,No,Sun,Dinner,3
-17.31,3.5,Female,No,Sun,Dinner,2
-29.93,5.07,Male,No,Sun,Dinner,4
-10.65,1.5,Female,No,Thur,Lunch,2
-12.43,1.8,Female,No,Thur,Lunch,2
-24.08,2.92,Female,No,Thur,Lunch,4
-11.69,2.31,Male,No,Thur,Lunch,2
-13.42,1.68,Female,No,Thur,Lunch,2
-14.26,2.5,Male,No,Thur,Lunch,2
-15.95,2.0,Male,No,Thur,Lunch,2
-12.48,2.52,Female,No,Thur,Lunch,2
-29.8,4.2,Female,No,Thur,Lunch,6
-8.52,1.48,Male,No,Thur,Lunch,2
-14.52,2.0,Female,No,Thur,Lunch,2
-11.38,2.0,Female,No,Thur,Lunch,2
-22.82,2.18,Male,No,Thur,Lunch,3
-19.08,1.5,Male,No,Thur,Lunch,2
-20.27,2.83,Female,No,Thur,Lunch,2
-11.17,1.5,Female,No,Thur,Lunch,2
-12.26,2.0,Female,No,Thur,Lunch,2
-18.26,3.25,Female,No,Thur,Lunch,2
-8.51,1.25,Female,No,Thur,Lunch,2
-10.33,2.0,Female,No,Thur,Lunch,2
-14.15,2.0,Female,No,Thur,Lunch,2
-16.0,2.0,Male,Yes,Thur,Lunch,2
-13.16,2.75,Female,No,Thur,Lunch,2
-17.47,3.5,Female,No,Thur,Lunch,2
-34.3,6.7,Male,No,Thur,Lunch,6
-41.19,5.0,Male,No,Thur,Lunch,5
-27.05,5.0,Female,No,Thur,Lunch,6
-16.43,2.3,Female,No,Thur,Lunch,2
-8.35,1.5,Female,No,Thur,Lunch,2
-18.64,1.36,Female,No,Thur,Lunch,3
-11.87,1.63,Female,No,Thur,Lunch,2
-9.78,1.73,Male,No,Thur,Lunch,2
-7.51,2.0,Male,No,Thur,Lunch,2
-14.07,2.5,Male,No,Sun,Dinner,2
-13.13,2.0,Male,No,Sun,Dinner,2
-17.26,2.74,Male,No,Sun,Dinner,3
-24.55,2.0,Male,No,Sun,Dinner,4
-19.77,2.0,Male,No,Sun,Dinner,4
-29.85,5.14,Female,No,Sun,Dinner,5
-48.17,5.0,Male,No,Sun,Dinner,6
-25.0,3.75,Female,No,Sun,Dinner,4
-13.39,2.61,Female,No,Sun,Dinner,2
-16.49,2.0,Male,No,Sun,Dinner,4
-21.5,3.5,Male,No,Sun,Dinner,4
-12.66,2.5,Male,No,Sun,Dinner,2
-16.21,2.0,Female,No,Sun,Dinner,3
-13.81,2.0,Male,No,Sun,Dinner,2
-17.51,3.0,Female,Yes,Sun,Dinner,2
-24.52,3.48,Male,No,Sun,Dinner,3
-20.76,2.24,Male,No,Sun,Dinner,2
-31.71,4.5,Male,No,Sun,Dinner,4
-10.59,1.61,Female,Yes,Sat,Dinner,2
-10.63,2.0,Female,Yes,Sat,Dinner,2
-50.81,10.0,Male,Yes,Sat,Dinner,3
-15.81,3.16,Male,Yes,Sat,Dinner,2
-7.25,5.15,Male,Yes,Sun,Dinner,2
-31.85,3.18,Male,Yes,Sun,Dinner,2
-16.82,4.0,Male,Yes,Sun,Dinner,2
-32.9,3.11,Male,Yes,Sun,Dinner,2
-17.89,2.0,Male,Yes,Sun,Dinner,2
-14.48,2.0,Male,Yes,Sun,Dinner,2
-9.6,4.0,Female,Yes,Sun,Dinner,2
-34.63,3.55,Male,Yes,Sun,Dinner,2
-34.65,3.68,Male,Yes,Sun,Dinner,4
-23.33,5.65,Male,Yes,Sun,Dinner,2
-45.35,3.5,Male,Yes,Sun,Dinner,3
-23.17,6.5,Male,Yes,Sun,Dinner,4
-40.55,3.0,Male,Yes,Sun,Dinner,2
-20.69,5.0,Male,No,Sun,Dinner,5
-20.9,3.5,Female,Yes,Sun,Dinner,3
-30.46,2.0,Male,Yes,Sun,Dinner,5
-18.15,3.5,Female,Yes,Sun,Dinner,3
-23.1,4.0,Male,Yes,Sun,Dinner,3
-15.69,1.5,Male,Yes,Sun,Dinner,2
-19.81,4.19,Female,Yes,Thur,Lunch,2
-28.44,2.56,Male,Yes,Thur,Lunch,2
-15.48,2.02,Male,Yes,Thur,Lunch,2
-16.58,4.0,Male,Yes,Thur,Lunch,2
-7.56,1.44,Male,No,Thur,Lunch,2
-10.34,2.0,Male,Yes,Thur,Lunch,2
-43.11,5.0,Female,Yes,Thur,Lunch,4
-13.0,2.0,Female,Yes,Thur,Lunch,2
-13.51,2.0,Male,Yes,Thur,Lunch,2
-18.71,4.0,Male,Yes,Thur,Lunch,3
-12.74,2.01,Female,Yes,Thur,Lunch,2
-13.0,2.0,Female,Yes,Thur,Lunch,2
-16.4,2.5,Female,Yes,Thur,Lunch,2
-20.53,4.0,Male,Yes,Thur,Lunch,4
-16.47,3.23,Female,Yes,Thur,Lunch,3
-26.59,3.41,Male,Yes,Sat,Dinner,3
-38.73,3.0,Male,Yes,Sat,Dinner,4
-24.27,2.03,Male,Yes,Sat,Dinner,2
-12.76,2.23,Female,Yes,Sat,Dinner,2
-30.06,2.0,Male,Yes,Sat,Dinner,3
-25.89,5.16,Male,Yes,Sat,Dinner,4
-48.33,9.0,Male,No,Sat,Dinner,4
-13.27,2.5,Female,Yes,Sat,Dinner,2
-28.17,6.5,Female,Yes,Sat,Dinner,3
-12.9,1.1,Female,Yes,Sat,Dinner,2
-28.15,3.0,Male,Yes,Sat,Dinner,5
-11.59,1.5,Male,Yes,Sat,Dinner,2
-7.74,1.44,Male,Yes,Sat,Dinner,2
-30.14,3.09,Female,Yes,Sat,Dinner,4
-12.16,2.2,Male,Yes,Fri,Lunch,2
-13.42,3.48,Female,Yes,Fri,Lunch,2
-8.58,1.92,Male,Yes,Fri,Lunch,1
-15.98,3.0,Female,No,Fri,Lunch,3
-13.42,1.58,Male,Yes,Fri,Lunch,2
-16.27,2.5,Female,Yes,Fri,Lunch,2
-10.09,2.0,Female,Yes,Fri,Lunch,2
-20.45,3.0,Male,No,Sat,Dinner,4
-13.28,2.72,Male,No,Sat,Dinner,2
-22.12,2.88,Female,Yes,Sat,Dinner,2
-24.01,2.0,Male,Yes,Sat,Dinner,4
-15.69,3.0,Male,Yes,Sat,Dinner,3
-11.61,3.39,Male,No,Sat,Dinner,2
-10.77,1.47,Male,No,Sat,Dinner,2
-15.53,3.0,Male,Yes,Sat,Dinner,2
-10.07,1.25,Male,No,Sat,Dinner,2
-12.6,1.0,Male,Yes,Sat,Dinner,2
-32.83,1.17,Male,Yes,Sat,Dinner,2
-35.83,4.67,Female,No,Sat,Dinner,3
-29.03,5.92,Male,No,Sat,Dinner,3
-27.18,2.0,Female,Yes,Sat,Dinner,2
-22.67,2.0,Male,Yes,Sat,Dinner,2
-17.82,1.75,Male,No,Sat,Dinner,2
-18.78,3.0,Female,No,Thur,Dinner,2
diff --git a/pandas/tests/io/parser/data/iris.csv b/pandas/tests/io/parser/data/iris.csv
deleted file mode 100644
index c19b9c3688515..0000000000000
--- a/pandas/tests/io/parser/data/iris.csv
+++ /dev/null
@@ -1,151 +0,0 @@
-SepalLength,SepalWidth,PetalLength,PetalWidth,Name
-5.1,3.5,1.4,0.2,Iris-setosa
-4.9,3.0,1.4,0.2,Iris-setosa
-4.7,3.2,1.3,0.2,Iris-setosa
-4.6,3.1,1.5,0.2,Iris-setosa
-5.0,3.6,1.4,0.2,Iris-setosa
-5.4,3.9,1.7,0.4,Iris-setosa
-4.6,3.4,1.4,0.3,Iris-setosa
-5.0,3.4,1.5,0.2,Iris-setosa
-4.4,2.9,1.4,0.2,Iris-setosa
-4.9,3.1,1.5,0.1,Iris-setosa
-5.4,3.7,1.5,0.2,Iris-setosa
-4.8,3.4,1.6,0.2,Iris-setosa
-4.8,3.0,1.4,0.1,Iris-setosa
-4.3,3.0,1.1,0.1,Iris-setosa
-5.8,4.0,1.2,0.2,Iris-setosa
-5.7,4.4,1.5,0.4,Iris-setosa
-5.4,3.9,1.3,0.4,Iris-setosa
-5.1,3.5,1.4,0.3,Iris-setosa
-5.7,3.8,1.7,0.3,Iris-setosa
-5.1,3.8,1.5,0.3,Iris-setosa
-5.4,3.4,1.7,0.2,Iris-setosa
-5.1,3.7,1.5,0.4,Iris-setosa
-4.6,3.6,1.0,0.2,Iris-setosa
-5.1,3.3,1.7,0.5,Iris-setosa
-4.8,3.4,1.9,0.2,Iris-setosa
-5.0,3.0,1.6,0.2,Iris-setosa
-5.0,3.4,1.6,0.4,Iris-setosa
-5.2,3.5,1.5,0.2,Iris-setosa
-5.2,3.4,1.4,0.2,Iris-setosa
-4.7,3.2,1.6,0.2,Iris-setosa
-4.8,3.1,1.6,0.2,Iris-setosa
-5.4,3.4,1.5,0.4,Iris-setosa
-5.2,4.1,1.5,0.1,Iris-setosa
-5.5,4.2,1.4,0.2,Iris-setosa
-4.9,3.1,1.5,0.1,Iris-setosa
-5.0,3.2,1.2,0.2,Iris-setosa
-5.5,3.5,1.3,0.2,Iris-setosa
-4.9,3.1,1.5,0.1,Iris-setosa
-4.4,3.0,1.3,0.2,Iris-setosa
-5.1,3.4,1.5,0.2,Iris-setosa
-5.0,3.5,1.3,0.3,Iris-setosa
-4.5,2.3,1.3,0.3,Iris-setosa
-4.4,3.2,1.3,0.2,Iris-setosa
-5.0,3.5,1.6,0.6,Iris-setosa
-5.1,3.8,1.9,0.4,Iris-setosa
-4.8,3.0,1.4,0.3,Iris-setosa
-5.1,3.8,1.6,0.2,Iris-setosa
-4.6,3.2,1.4,0.2,Iris-setosa
-5.3,3.7,1.5,0.2,Iris-setosa
-5.0,3.3,1.4,0.2,Iris-setosa
-7.0,3.2,4.7,1.4,Iris-versicolor
-6.4,3.2,4.5,1.5,Iris-versicolor
-6.9,3.1,4.9,1.5,Iris-versicolor
-5.5,2.3,4.0,1.3,Iris-versicolor
-6.5,2.8,4.6,1.5,Iris-versicolor
-5.7,2.8,4.5,1.3,Iris-versicolor
-6.3,3.3,4.7,1.6,Iris-versicolor
-4.9,2.4,3.3,1.0,Iris-versicolor
-6.6,2.9,4.6,1.3,Iris-versicolor
-5.2,2.7,3.9,1.4,Iris-versicolor
-5.0,2.0,3.5,1.0,Iris-versicolor
-5.9,3.0,4.2,1.5,Iris-versicolor
-6.0,2.2,4.0,1.0,Iris-versicolor
-6.1,2.9,4.7,1.4,Iris-versicolor
-5.6,2.9,3.6,1.3,Iris-versicolor
-6.7,3.1,4.4,1.4,Iris-versicolor
-5.6,3.0,4.5,1.5,Iris-versicolor
-5.8,2.7,4.1,1.0,Iris-versicolor
-6.2,2.2,4.5,1.5,Iris-versicolor
-5.6,2.5,3.9,1.1,Iris-versicolor
-5.9,3.2,4.8,1.8,Iris-versicolor
-6.1,2.8,4.0,1.3,Iris-versicolor
-6.3,2.5,4.9,1.5,Iris-versicolor
-6.1,2.8,4.7,1.2,Iris-versicolor
-6.4,2.9,4.3,1.3,Iris-versicolor
-6.6,3.0,4.4,1.4,Iris-versicolor
-6.8,2.8,4.8,1.4,Iris-versicolor
-6.7,3.0,5.0,1.7,Iris-versicolor
-6.0,2.9,4.5,1.5,Iris-versicolor
-5.7,2.6,3.5,1.0,Iris-versicolor
-5.5,2.4,3.8,1.1,Iris-versicolor
-5.5,2.4,3.7,1.0,Iris-versicolor
-5.8,2.7,3.9,1.2,Iris-versicolor
-6.0,2.7,5.1,1.6,Iris-versicolor
-5.4,3.0,4.5,1.5,Iris-versicolor
-6.0,3.4,4.5,1.6,Iris-versicolor
-6.7,3.1,4.7,1.5,Iris-versicolor
-6.3,2.3,4.4,1.3,Iris-versicolor
-5.6,3.0,4.1,1.3,Iris-versicolor
-5.5,2.5,4.0,1.3,Iris-versicolor
-5.5,2.6,4.4,1.2,Iris-versicolor
-6.1,3.0,4.6,1.4,Iris-versicolor
-5.8,2.6,4.0,1.2,Iris-versicolor
-5.0,2.3,3.3,1.0,Iris-versicolor
-5.6,2.7,4.2,1.3,Iris-versicolor
-5.7,3.0,4.2,1.2,Iris-versicolor
-5.7,2.9,4.2,1.3,Iris-versicolor
-6.2,2.9,4.3,1.3,Iris-versicolor
-5.1,2.5,3.0,1.1,Iris-versicolor
-5.7,2.8,4.1,1.3,Iris-versicolor
-6.3,3.3,6.0,2.5,Iris-virginica
-5.8,2.7,5.1,1.9,Iris-virginica
-7.1,3.0,5.9,2.1,Iris-virginica
-6.3,2.9,5.6,1.8,Iris-virginica
-6.5,3.0,5.8,2.2,Iris-virginica
-7.6,3.0,6.6,2.1,Iris-virginica
-4.9,2.5,4.5,1.7,Iris-virginica
-7.3,2.9,6.3,1.8,Iris-virginica
-6.7,2.5,5.8,1.8,Iris-virginica
-7.2,3.6,6.1,2.5,Iris-virginica
-6.5,3.2,5.1,2.0,Iris-virginica
-6.4,2.7,5.3,1.9,Iris-virginica
-6.8,3.0,5.5,2.1,Iris-virginica
-5.7,2.5,5.0,2.0,Iris-virginica
-5.8,2.8,5.1,2.4,Iris-virginica
-6.4,3.2,5.3,2.3,Iris-virginica
-6.5,3.0,5.5,1.8,Iris-virginica
-7.7,3.8,6.7,2.2,Iris-virginica
-7.7,2.6,6.9,2.3,Iris-virginica
-6.0,2.2,5.0,1.5,Iris-virginica
-6.9,3.2,5.7,2.3,Iris-virginica
-5.6,2.8,4.9,2.0,Iris-virginica
-7.7,2.8,6.7,2.0,Iris-virginica
-6.3,2.7,4.9,1.8,Iris-virginica
-6.7,3.3,5.7,2.1,Iris-virginica
-7.2,3.2,6.0,1.8,Iris-virginica
-6.2,2.8,4.8,1.8,Iris-virginica
-6.1,3.0,4.9,1.8,Iris-virginica
-6.4,2.8,5.6,2.1,Iris-virginica
-7.2,3.0,5.8,1.6,Iris-virginica
-7.4,2.8,6.1,1.9,Iris-virginica
-7.9,3.8,6.4,2.0,Iris-virginica
-6.4,2.8,5.6,2.2,Iris-virginica
-6.3,2.8,5.1,1.5,Iris-virginica
-6.1,2.6,5.6,1.4,Iris-virginica
-7.7,3.0,6.1,2.3,Iris-virginica
-6.3,3.4,5.6,2.4,Iris-virginica
-6.4,3.1,5.5,1.8,Iris-virginica
-6.0,3.0,4.8,1.8,Iris-virginica
-6.9,3.1,5.4,2.1,Iris-virginica
-6.7,3.1,5.6,2.4,Iris-virginica
-6.9,3.1,5.1,2.3,Iris-virginica
-5.8,2.7,5.1,1.9,Iris-virginica
-6.8,3.2,5.9,2.3,Iris-virginica
-6.7,3.3,5.7,2.5,Iris-virginica
-6.7,3.0,5.2,2.3,Iris-virginica
-6.3,2.5,5.0,1.9,Iris-virginica
-6.5,3.0,5.2,2.0,Iris-virginica
-6.2,3.4,5.4,2.3,Iris-virginica
-5.9,3.0,5.1,1.8,Iris-virginica
\ No newline at end of file
diff --git a/pandas/tests/io/test_common.py b/pandas/tests/io/test_common.py
index a126f83164ce5..aa9294b016a3f 100644
--- a/pandas/tests/io/test_common.py
+++ b/pandas/tests/io/test_common.py
@@ -202,8 +202,8 @@ def test_read_expands_user_home_dir(
     @pytest.mark.parametrize(
         "reader, module, path",
         [
-            (pd.read_csv, "os", ("data", "iris.csv")),
-            (pd.read_table, "os", ("data", "iris.csv")),
+            (pd.read_csv, "os", ("io", "data", "csv", "iris.csv")),
+            (pd.read_table, "os", ("io", "data", "csv", "iris.csv")),
             (
                 pd.read_fwf,
                 "os",
diff --git a/pandas/tests/io/test_sql.py b/pandas/tests/io/test_sql.py
index 45b3e839a08d1..d0569cd1d0cdf 100644
--- a/pandas/tests/io/test_sql.py
+++ b/pandas/tests/io/test_sql.py
@@ -273,7 +273,7 @@ def _get_exec(self):
         else:
             return self.conn.cursor()
 
-    @pytest.fixture(params=[("data", "iris.csv")])
+    @pytest.fixture(params=[("io", "data", "csv", "iris.csv")])
     def load_iris_data(self, datapath, request):
         import io
 
diff --git a/pandas/tests/util/test_util.py b/pandas/tests/util/test_util.py
index 6a19adef728e4..c9dbcf4798a96 100644
--- a/pandas/tests/util/test_util.py
+++ b/pandas/tests/util/test_util.py
@@ -58,7 +58,7 @@ def test_datapath_missing(datapath):
 
 
 def test_datapath(datapath):
-    args = ("data", "iris.csv")
+    args = ("io", "data", "csv", "iris.csv")
 
     result = datapath(*args)
     expected = os.path.join(os.path.dirname(os.path.dirname(__file__)), *args)