![]() ![]() If NAs are represented by something other than blank cells, set the na argument. ![]() I added double quotes in the Excel file to this string but when i rerun the script i get the same error message.Read_excel ( xlsx_example, n_max = 3 ) #> # A tibble: 3 × 5 #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> #> 1 5.1 3.5 1.4 0.2 setosa #> 2 4.9 3 1.4 0.2 setosa #> 3 4.7 3.2 1.3 0.2 setosa read_excel ( xlsx_example, range = "C1:E4" ) #> # A tibble: 3 × 3 #> Petal.Length Petal.Width Species #> #> 1 1.4 0.2 setosa #> 2 1.4 0.2 setosa #> 3 1.3 0.2 setosa read_excel ( xlsx_example, range = cell_rows ( 1 : 4 ) ) #> # A tibble: 3 × 5 #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> #> 1 5.1 3.5 1.4 0.2 setosa #> 2 4.9 3 1.4 0.2 setosa #> 3 4.7 3.2 1.3 0.2 setosa read_excel ( xlsx_example, range = cell_cols ( "B:D" ) ) #> # A tibble: 150 × 3 #> Sepal.Width Petal.Length Petal.Width #> #> 1 3.5 1.4 0.2 #> 2 3 1.4 0.2 #> 3 3.2 1.3 0.2 #> # ℹ 147 more rows read_excel ( xlsx_example, range = "mtcars!B1:D5" ) #> # A tibble: 4 × 3 #> cyl disp hp #> #> 1 6 160 110 #> 2 6 160 110 #> 3 4 108 93 #> # ℹ 1 more row Apparently it has to do with the fact that certain json data in line 1 column 2 (char 1) is not between double quotes. I read the traceback that states the specific lines of code were the problem occurs. : Expecting property name enclosed in double quotes: line 1 column 2 (char 1) ![]() Obj, end = self.raw_decode(s, idx=_w(s, 0).end())įile "C:\Users\Madink\Desktop\Lib\json\decoder.py", line 353, in raw_decode Return SeriesApply(self, func, convert_dtype, args, kwargs).apply()įile "C:\Users\Maardink\Desktop\Lib\site-packages\pandas\core\apply.py", line 1025, in applyįile "C:\Users\Maardink\Desktop\Lib\site-packages\pandas\core\apply.py", line 1076, in apply_standardįile "pandas\_libs\lib.pyx", line 2834, in pandas._inferįile "C:\Users\Maaerdink\Desktop\Lib\json\_init_.py", line 346, in loadsįile "C:\Users\Maartdink\Desktop\Lib\json\decoder.py", line 337, in decode I get this error: Traceback (most recent call last):įile "C:/Users/Maarerdink/Desktop/file_data_columns_split.py", line 9, in įile "C:\Users\Maarteerdink\Desktop\Lib\site-packages\pandas\core\series.py", line 4630, in apply ' Merge the normalized data with the original DataFrameĭf = pd.concat(, axis=1) ' Use the 'pandas.json_normalize()' functionĭf_normalized = pd.json_normalize(df) Export Data to Excel With the DataFrame.toexcel () Function in Python If we want to write tabular data to an Excel sheet in Python, we can use the toexcel () function in Pandas DataFrame. ' Assuming te JSON data contains nested dictionaries and you want to split them into separate ' ' ' columns Python Export to Excel This tutorial will demonstrate different methods to write tabular data to an excel file in Python. ' Use the 'json.loads()' function to convert the JSON strings to Python dictionariesĭf = df.apply(json.loads) ![]() ' Assuming the JSON data is stored in a column named 'conversations' ' Replace 'your_file.xlsx' with the actual path to your Excel fileĭf = pd.read_excel('file_data_columns_split.xlsx') The problem is that one of the columns contains dictionaries and as a result the data is not displayed in nice rows and columns. Then from Excel, click on Refresh under data tab to get the latest data from. I used a python script to convert json data into an Excel file. Just export the List Export to Spreadsheet option from SharePoint list. ![]()
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