def test_to_datetime():
# DataFrame input for to_datetime
modin_df = pd.DataFrame({
"year": [2015, 2016],
"month": [2, 3],
"day": [4, 5]
})
pandas_df = pandas.DataFrame({
"year": [2015, 2016],
"month": [2, 3],
"day": [4, 5]
})
df_equals(pd.to_datetime(modin_df), pandas.to_datetime(pandas_df))
# Series input for to_datetime
modin_s = pd.Series(["3/11/2000", "3/12/2000", "3/13/2000"] * 1000)
pandas_s = pandas.Series(["3/11/2000", "3/12/2000", "3/13/2000"] * 1000)
df_equals(pd.to_datetime(modin_s), pandas.to_datetime(pandas_s))
# Other inputs for to_datetime
value = 1490195805
assert pd.to_datetime(value, unit="s") == pandas.to_datetime(value,
unit="s")
value = 1490195805433502912
assert pd.to_datetime(value, unit="ns") == pandas.to_datetime(value,
unit="ns")
value = [1, 2, 3]
assert pd.to_datetime(
value, unit="D", origin=pd.Timestamp("2000-01-01")).equals(
pandas.to_datetime(value,
unit="D",
origin=pandas.Timestamp("2000-01-01")))
def test_to_numeric(data, errors, downcast):
modin_series = pd.Series(data)
pandas_series = pandas.Series(data)
modin_result = pd.to_numeric(modin_series,
errors=errors,
downcast=downcast)
pandas_result = pandas.to_numeric(pandas_series,
errors=errors,
downcast=downcast)
df_equals(modin_result, pandas_result)
def test_notnull(data):
pandas_df = pandas.DataFrame(data)
modin_df = pd.DataFrame(data)
pandas_result = pandas.notnull(pandas_df)
modin_result = pd.notnull(modin_df)
df_equals(modin_result, pandas_result)
modin_result = pd.notnull(pd.Series([1, np.nan, 2]))
pandas_result = pandas.notnull(pandas.Series([1, np.nan, 2]))
df_equals(modin_result, pandas_result)
assert pd.isna(np.nan) == pandas.isna(np.nan)
def test_merge():
frame_data = {
"col1": [0, 1, 2, 3],
"col2": [4, 5, 6, 7],
"col3": [8, 9, 0, 1],
"col4": [2, 4, 5, 6],
}
modin_df = pd.DataFrame(frame_data)
pandas_df = pandas.DataFrame(frame_data)
frame_data2 = {"col1": [0, 1, 2], "col2": [1, 5, 6]}
modin_df2 = pd.DataFrame(frame_data2)
pandas_df2 = pandas.DataFrame(frame_data2)
join_types = ["outer", "inner"]
for how in join_types:
# Defaults
modin_result = pd.merge(modin_df, modin_df2, how=how)
pandas_result = pandas.merge(pandas_df, pandas_df2, how=how)
df_equals(modin_result, pandas_result)
# left_on and right_index
modin_result = pd.merge(modin_df,
modin_df2,
how=how,
left_on="col1",
right_index=True)
pandas_result = pandas.merge(pandas_df,
pandas_df2,
how=how,
left_on="col1",
right_index=True)
df_equals(modin_result, pandas_result)
# left_index and right_on
modin_result = pd.merge(modin_df,
modin_df2,
how=how,
left_index=True,
right_on="col1")
pandas_result = pandas.merge(pandas_df,
pandas_df2,
how=how,
left_index=True,
right_on="col1")
df_equals(modin_result, pandas_result)
# left_on and right_on col1
modin_result = pd.merge(modin_df,
modin_df2,
how=how,
left_on="col1",
right_on="col1")
pandas_result = pandas.merge(pandas_df,
pandas_df2,
how=how,
left_on="col1",
right_on="col1")
df_equals(modin_result, pandas_result)
# left_on and right_on col2
modin_result = pd.merge(modin_df,
modin_df2,
how=how,
left_on="col2",
right_on="col2")
pandas_result = pandas.merge(pandas_df,
pandas_df2,
how=how,
left_on="col2",
right_on="col2")
df_equals(modin_result, pandas_result)
# left_index and right_index
modin_result = pd.merge(modin_df,
modin_df2,
how=how,
left_index=True,
right_index=True)
pandas_result = pandas.merge(pandas_df,
pandas_df2,
how=how,
left_index=True,
right_index=True)
df_equals(modin_result, pandas_result)
s = pd.Series(frame_data.get("col1"))
with pytest.raises(ValueError):
pd.merge(s, modin_df2)
with pytest.raises(TypeError):
pd.merge("Non-valid type", modin_df2)
