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pandasCommand.py
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"""
Pandas Objects Command
"""
def _vp_get_rows_list(df):
"""
Get Rows List with Detail Information
"""
rowList = []
indexType = str(df.index.dtype)
for i, r in enumerate(df.index):
rInfo = { 'label': r, 'value': r, 'location': i }
# value
if type(r).__name__ == 'str':
rInfo['value'] = "'{}'".format(r)
rInfo['index_dtype'] = indexType # object
elif type(r).__name__ == 'Timestamp':
rInfo['label'] = str(r)
rInfo['value'] = "'{}'".format(r)
rInfo['index_dtype'] = indexType # datetime64[ns] TODO: exception consideration needed
rowList.append(rInfo)
return rowList
def _vp_get_columns_list(df):
"""
Get Columns List with Detail Information
"""
colList = []
for i, c in enumerate(df.columns):
cInfo = { 'label': c, 'value': c, 'dtype': str(df[c].dtype), 'array': str(df[c].array), 'location': i }
# value
if type(c).__name__ == 'str':
cInfo['value'] = "'{}'".format(c)
elif type(r).__name__ == 'Timestamp':
cInfo['value'] = str(c)
# category - iopub data rate limit issue...
if str(df[c].dtype) == 'object':
uniqValues = df[c].dropna().unique()
if len(uniqValues) <= 20:
cInfo['category'] = [{ "value": "'{}'".format(u) if type(u) == str else u, "label": u } for u in uniqValues]
else:
cInfo['category'] = []
else:
cInfo['category'] = []
colList.append(cInfo)
return colList
def _vp_get_column_category(df, col):
"""
Get Column's Uniq values(Categrical data only, limit 20)
"""
uniqValues = df[col].dropna().unique()
category = []
if len(uniqValues) <= 20:
category = [{ "value": "{}".format(u) if type(u) == str else u, "label": u } for u in uniqValues]
return category
def _vp_get_dataframe_as_list(df):
"""
Get Dataframe as List
"""
return df.values.tolist()