# Function to convert 3D polygons to 2D polygons def convert_3d_to_2d(multipolygon): polygons_2d = [] for polygon in list(multipolygon.geoms): polygons_2d.append(Polygon([(x, y) for x, y, z in polygon.exterior.coords])) return MultiPolygon(polygons_2d) # Convert 3D multipolygons ...
Anyone know how to convert a single-element list to a number? Sort by date Sort by votes Jun 16, 2006 #2 ZaSter Technical User Dec 20, 2001 195 US Maybe. Please explain a bit more what you are trying to do. Upvote 0 Downvote Jun 16, 2006 Thread starter #3 varocho Progra...
Importing images from a directory (Python) to list or dictionary from PIL import Image import glob image_list = [] for filename in glob.glob('yourpath/*.gif'): #assuming gif im=Image.open(filename) image_list.append(im) content_copy ...
Internally the data is stored in a Pandas DataFrame, which can be accessed directly. For example, this can be used to filter countries for membership organisations (per year). Note: for this, an instance of CountryConverter is required. ...
For the parsing of EC-Lab ASCII files (.mpt/.mps) you add a function with alistof parameter names intechniques.pyin the order they appear in the text files. See_wait_params()to get an idea. If the technique has a changing number of parameters in these ASCII files, e.g. it contains...
df = pd.DataFrame(data = count_vektor, columns = count_vector.get_feature_names()) df.index = text df Good news! The documents are converted to numbers. But, a close look shows that “Harry Potter and the Order of the Phoenix” is similar to “Indiana Jones and the Raiders of the ...
Convert string date to numeric for all values in column using pandas python, Speed up date columns conversion (pandas) from string to datetime, Converting List string or string to dataframe python, Convert string date column to int column for merge in py
shap_values_df = pd.DataFrame(shap_values) To obtain the names of the features, a similar action needs to be performed (provided thatdata_for_predictionis a dataframe). feature_names = data_for_prediction.columns.tolist() shap_df = pd.DataFrame(shap_values.values, columns=feature_names) ...
def table_cells_to_dataframe( cells: List[dict], nrows: int = 1, ncols: int = 1, header=None ) -> DataFrame: """convert table-transformer's cells data into a pandas dataframe""" arr = np.empty((nrows, ncols), dtype=object) ...
the resulting value will be a numpy value (such as int64, int32, etc). However, if you desire a standard int (not a numpy int), there is a solution that I have discovered. By converting the list to a string first, and then converting it back to a list, you can achieve the desir...