10 examples of 'convert dataframe to csv file python' in Python

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57def _dataframe_to_txt(writer, dataframe):
58 encoding_writer = codecs.getwriter('utf-8')(writer)
59 for row in dataframe.iterrows():
60 encoding_writer.write("".join(row[1].tolist()))
61 encoding_writer.write('\n')
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35def csvToDataFrame(self, sqlCtx, rdd, columns=None, sep=",", parseDate=True):
36 """Converts CSV plain text RDD into SparkSQL DataFrame (former SchemaRDD)
37 using PySpark. If columns not given, assumes first row is the header.
38 If separator not given, assumes comma separated
39 """
40 if self.py_version < 3:
41 def toRow(line):
42 return self.toRowSep(line.encode('utf-8'), sep)
43 else:
44 def toRow(line):
45 return self.toRowSep(line, sep)
46
47 rdd_array = rdd.map(toRow)
48 rdd_sql = rdd_array
49
50 if columns is None:
51 columns = rdd_array.first()
52 rdd_sql = rdd_array.zipWithIndex().filter(
53 lambda r_i: r_i[1] > 0).keys()
54 column_types = self.evaluateType(rdd_sql, parseDate)
55
56 def toSqlRow(row):
57 return self.toSqlRowWithType(row, column_types)
58
59 schema = self.makeSchema(zip(columns, column_types))
60
61 return sqlCtx.createDataFrame(rdd_sql.map(toSqlRow), schema=schema)
290def dict_to_csv(data=None, filename='test.csv'):
291 r'''
292 Utility function to write a dictionary to a csv file
293 Uses dictionary keys as column headers
294 Data should all be same length
295 '''
296 data_list = [data[key] for key in data.keys()]
297 zipper = list(zip(*data_list))
298 with open(filename, 'w') as f:
299 w = csv.writer(f, lineterminator='\n')
300 w.writerow(data.keys())
301 w.writerows(zipper)
53def row2_dict2csv(raw_dict = {}, csv_file = ""):
54 with open(csv_file,'w') as f:
55 w = csv.writer(f)
56 for k,v in raw_dict.items():
57 w.writerows([k,v])
37def readcsv(filename, header=True):
38 return pd.read_csv(filename, header=None) if not header else pd.read_csv(filename)
8def convert(csv_path):
9 with open(csv_path) as f:
10 data = Data(f)
11
12 table = Table()
13 table.set_header(["procedure", "time [s]", "speedup", ""])
14
15 reference_time = None
16 for name, time in data:
17 if reference_time is None:
18 reference_time = time
19
20 speedup = reference_time/time
21
22 time = '%0.5f' % time
23 bar = unicode_bar(speedup * 10)
24 speedup = '%0.2f' % speedup
25 table.add_row([name, time, speedup, bar])
26
27 def get_path():
28 basename = os.path.splitext(os.path.basename(csv_path))[0]
29 return basename + ".txt"
30
31 path = get_path()
32 with open(path, 'wt', encoding='utf-8') as f:
33 f.write(unicode(table))
34
35 print "%s created" % path
554def _csv_to_pandas_df(filepath,
555 separator=DEFAULT_SEPARATOR,
556 quote_char=DEFAULT_QUOTE_CHARACTER,
557 escape_char=DEFAULT_ESCAPSE_CHAR,
558 contain_headers=True,
559 lines_to_skip=0,
560 date_columns=None,
561 rowIdAndVersionInIndex=True):
562 test_import_pandas()
563 import pandas as pd
564
565 # DATEs are stored in csv as unix timestamp in milliseconds
566 def datetime_millisecond_parser(milliseconds): return pd.to_datetime(milliseconds, unit='ms', utc=True)
567
568 if not date_columns:
569 date_columns = []
570
571 line_terminator = str(os.linesep)
572
573 df = pd.read_csv(filepath,
574 sep=separator,
575 lineterminator=line_terminator if len(line_terminator) == 1 else None,
576 quotechar=quote_char,
577 escapechar=escape_char,
578 header=0 if contain_headers else None,
579 skiprows=lines_to_skip,
580 parse_dates=date_columns,
581 date_parser=datetime_millisecond_parser)
582 if rowIdAndVersionInIndex and "ROW_ID" in df.columns and "ROW_VERSION" in df.columns:
583 # combine row-ids (in index) and row-versions (in column 0) to
584 # make new row labels consisting of the row id and version
585 # separated by a dash.
586 zip_args = [df["ROW_ID"], df["ROW_VERSION"]]
587 if "ROW_ETAG" in df.columns:
588 zip_args.append(df['ROW_ETAG'])
589
590 df.index = row_labels_from_id_and_version(zip(*zip_args))
591 del df["ROW_ID"]
592 del df["ROW_VERSION"]
593 if "ROW_ETAG" in df.columns:
594 del df['ROW_ETAG']
595
596 return df
1153def to_csv(self, file_name, sep=',', encoding=None):
1154 start = time.time()
1155 init = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss
1156
1157 self._data.to_csv(file_name, sep, encoding)
1158
1159 finish = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss
1160 self._last_operation_dict['time'] = time.time() - start
1161 self._last_operation_dict['name'] = 'to_csv'
1162 self._last_operation_dict['mem_usage'] = finish - init
305def to_csv(self, f):
306 is_path = False
307 if isinstance(f, str):
308 is_path = True
309 f = open(f, mode='w')
310 writer = csv.DictWriter(f, self.columns)
311 writer.writerows(self._data)
312 if is_path:
313 f.close()
75def writecsv(filename, rows, separator="\t", encoding="utf-8-sig"):
76 """Write the rows to the file.
77
78 :param filename: (str)
79 :param rows: (list)
80 :param separator: (str):
81 :param encoding: (str):
82
83 """
84 with codecs.open(filename, "w+", encoding) as f:
85 for row in rows:
86 tmp = []
87 for s in row:
88 if isinstance(s, (float, int)):
89 s = str(s)
90 else:
91 s = '"%s"' % s
92 tmp.append(s)
93 f.write('%s\n' % separator.join(tmp))

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