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adds robustness to create_dataframe() and couple of other places #211

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merged 2 commits into from
Jun 3, 2024
Merged

adds robustness to create_dataframe() and couple of other places #211

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ada7b0e
adds robustness to create_datafram
jim-smith Jun 3, 2024
552b3b5
linting
jim-smith Jun 3, 2024
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4 changes: 4 additions & 0 deletions acro/acro_stata_parser.py
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Original file line number Diff line number Diff line change
Expand Up @@ -138,6 +138,7 @@ def parse_table_details(
>> table rowvar [colvar [supercolvar] [if] [in] [weight] [, options].
"""
details: dict = {"errmsg": "", "rowvars": list([]), "colvars": list([])}
contents_found, content = False, []

if stata_version == "16":
details["rowvars"] = [varlist.pop(0)]
Expand Down Expand Up @@ -326,6 +327,7 @@ def extract_var_within_parentheses(input_string):
"""Given a string, this function extracts the words within the first parentheses
from a string.
"""
string = ""
string_match = re.match(r"\((.*?)\)", input_string)
if string_match:
string = string_match.group(1).strip()
Expand All @@ -335,6 +337,7 @@ def extract_var_within_parentheses(input_string):

def extract_var_before_parentheses(input_string):
"""Given a string, this function extracts the words before the first parentheses."""
string = ""
string_match = re.match(r"^(.*?)\(", input_string)
if string_match:
string = string_match.group(1).strip()
Expand All @@ -346,6 +349,7 @@ def extract_table_var(input_string):
"""Given a string, this function extracts the words within the parentheses.
If there are no parentheses the string is returned.
"""
string = ""
# If the string starts with parentheses
if input_string.startswith("("):
string, _ = extract_var_within_parentheses(input_string)
Expand Down
50 changes: 33 additions & 17 deletions acro/acro_tables.py
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Original file line number Diff line number Diff line change
Expand Up @@ -555,13 +555,13 @@ def hist( # pylint: disable=too-many-arguments,too-many-locals
self,
data,
column,
by=None,
by_val=None,
grid=True,
xlabelsize=None,
xrot=None,
ylabelsize=None,
yrot=None,
ax=None,
axis=None,
sharex=False,
sharey=False,
figsize=None,
Expand All @@ -586,7 +586,7 @@ def hist( # pylint: disable=too-many-arguments,too-many-locals
The pandas object holding the data.
column : str
The column that will be used to plot the histogram.
by : object, optional
by_val : object, optional
If passed, then used to form histograms for separate groups.
grid : bool, default True
Whether to show axis grid lines.
Expand All @@ -600,7 +600,7 @@ def hist( # pylint: disable=too-many-arguments,too-many-locals
yrot : float, default None
Rotation of y axis labels. For example, a value of 90 displays
the y labels rotated 90 degrees clockwise.
ax : Matplotlib axes object, default None
axis : Matplotlib axes object, default None
The axes to plot the histogram on.
sharex : bool, default True if ax is None else False
In case subplots=True, share x axis and set some x axis labels to invisible;
Expand Down Expand Up @@ -662,13 +662,13 @@ def hist( # pylint: disable=too-many-arguments,too-many-locals
else: # pragma: no cover
data.hist(
column=column,
by=by,
by=by_val,
grid=grid,
xlabelsize=xlabelsize,
xrot=xrot,
ylabelsize=ylabelsize,
yrot=yrot,
ax=ax,
ax=axis,
sharex=sharex,
sharey=sharey,
figsize=figsize,
Expand All @@ -682,13 +682,13 @@ def hist( # pylint: disable=too-many-arguments,too-many-locals
status = "review"
data.hist(
column=column,
by=by,
by=by_val,
grid=grid,
xlabelsize=xlabelsize,
xrot=xrot,
ylabelsize=ylabelsize,
yrot=yrot,
ax=ax,
ax=axis,
sharex=sharex,
sharey=sharey,
figsize=figsize,
Expand Down Expand Up @@ -1364,15 +1364,31 @@ def create_dataframe(index, columns) -> DataFrame:
Dataframe
Table of the index and columns combined.
"""
if isinstance(index, list):
index_df = pd.concat(index, axis=1)
elif isinstance(index, pd.Series):
index_df = pd.DataFrame({index.name: index})
if isinstance(columns, list):
columns_df = pd.concat(columns, axis=1)
elif isinstance(columns, pd.Series):
columns_df = pd.DataFrame({columns.name: columns})
data = pd.concat([index_df, columns_df], axis=1)
empty_dataframe = pd.DataFrame([])

index_df = empty_dataframe
try:
if isinstance(index, list):
index_df = pd.concat(index, axis=1)
elif isinstance(index, pd.Series):
index_df = pd.DataFrame({index.name: index})
except ValueError:
index_df = empty_dataframe

columns_df = empty_dataframe
try:
if isinstance(columns, list):
columns_df = pd.concat(columns, axis=1)
elif isinstance(columns, pd.Series):
columns_df = pd.DataFrame({columns.name: columns})
except ValueError:
columns_df = empty_dataframe

try:
data = pd.concat([index_df, columns_df], axis=1)
except ValueError:
data = empty_dataframe

return data


Expand Down
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