def test_too_big_n_df(self):
df = pd.DataFrame(np.random.randn(100, 10))
df[df > 0] = np.nan
testdf = topper.topn_df(df, 10)
for x in range(len(df)):
correct = df.iloc[x].order(ascending=False).reset_index(drop=True)
test = testdf.iloc[x]
tm.assert_almost_equal(test, correct)
testdf = topper.topn_df(df, 2)
for x in range(len(df)):
correct = df.iloc[x].order(ascending=False).reset_index(
drop=True)[:2]
test = testdf.iloc[x]
tm.assert_almost_equal(test, correct)
# bottom
testdf = topper.topn_df(df, -2)
for x in range(len(df)):
correct = df.iloc[x].order().reset_index(drop=True)[:2]
test = testdf.iloc[x]
tm.assert_almost_equal(test, correct)
# bottom
testdf = topper.topn_df(df, -20)
for x in range(len(df)):
correct = df.iloc[x].order().reset_index(drop=True)[:20]
test = testdf.iloc[x]
tm.assert_almost_equal(test, correct)
def test_too_big_n_df(self):
df = pd.DataFrame(np.random.randn(100, 10))
df[df > 0] = np.nan
testdf = topper.topn_df(df, 10)
for x in range(len(df)):
correct = df.iloc[x].order(ascending=False).reset_index(drop=True)
test = testdf.iloc[x]
tm.assert_almost_equal(test, correct)
testdf = topper.topn_df(df, 2)
for x in range(len(df)):
correct = df.iloc[x].order(ascending=False).reset_index(drop=True)[:2]
test = testdf.iloc[x]
tm.assert_almost_equal(test, correct)
# bottom
testdf = topper.topn_df(df, -2)
for x in range(len(df)):
correct = df.iloc[x].order().reset_index(drop=True)[:2]
test = testdf.iloc[x]
tm.assert_almost_equal(test, correct)
# bottom
testdf = topper.topn_df(df, -20)
for x in range(len(df)):
correct = df.iloc[x].order().reset_index(drop=True)[:20]
test = testdf.iloc[x]
tm.assert_almost_equal(test, correct)
def test_df_topn(self):
# long way of getting the topn
tops = df.apply(lambda s: s.topn(2, ascending=False), axis=1)
correct = pd.DataFrame(tops, index=df.index)
test = topper.topn_df(df, 2, ascending=False)
tm.assert_frame_equal(test, correct)
# sanity check, make sure first value is right
c = df.iloc[0].order()[-1]
t = test.iloc[0][0]
tm.assert_almost_equal(t, c)
# bottom 2
tops = df.apply(lambda s: s.topn(-2), axis=1)
correct = pd.DataFrame(tops, index=df.index)
test = topper.topn_df(df, -2)
tm.assert_frame_equal(test, correct)
# sanity check, make sure first value is right
c = df.iloc[0].order()[0]
t = test.iloc[0][0]
tm.assert_almost_equal(t, c)
def test_df_topn(self):
# long way of getting the topn
tops = df.apply(lambda s: s.topn(2, ascending=False), axis=1)
correct = pd.DataFrame(tops, index=df.index)
test = topper.topn_df(df, 2, ascending=False)
tm.assert_almost_equal(test, correct)
# sanity check, make sure first value is right
c = df.iloc[0].order()[-1]
t = test.iloc[0][0]
tm.assert_almost_equal(t, c)
# bottom 2
tops = df.apply(lambda s: s.topn(-2), axis=1)
correct = pd.DataFrame(tops, index=df.index)
test = topper.topn_df(df, -2)
tm.assert_almost_equal(test, correct)
# sanity check, make sure first value is right
c = df.iloc[0].order()[0]
t = test.iloc[0][0]
tm.assert_almost_equal(t, c)
