In [32]: %%time ...: files = pathlib.Path("data/timeseries/").glob("ts*.parquet") ...: counts = pd.Series(dtype=int) ...: for path in files: ...: df = pd.read_parquet(path) ...: counts = counts.add(df["name"].value_counts(), fill_value=0) ...: counts.astype(in...
# Random integersarray = np.random.randint(20, size=12)arrayarray([ 0, 1, 8, 19, 16, 18, 10, 11, 2, 13, 14, 3])# Divide by 2 and check if remainder is 1cond = np.mod(array, 2)==1condarray([False, True, False, True, False, ...
(self, key, value) 1284 ) 1285 1286 check_dict_or_set_indexers(key) 1287 key = com.apply_if_callable(key, self) -> 1288 cacher_needs_updating = self._check_is_chained_assignment_possible() 1289 1290 if key is Ellipsis: 1291 key = slice(None) ~/work/pandas/pandas/pandas/core/seri...
in Series.__getitem__(self, key) 1118 return self._values[key] 1120 elif key_is_scalar: -> 1121 return self._get_value(key) 1123 # Convert generator to list before going through hashable part 1124 # (We will iterate through the generator there to check for slices) 1125 if is_iterato...
How to handle indexes on other axis (or axes).ignore_index : bool, default FalseIf True, do not use the index values along the concatenation axis. Theresulting axis will be labeled 0, ..., n - 1. This is useful if you areconcatenating objects where the concatenation axis does not ...
In [8]: pd.Series(d) Out[8]: b1a0c2dtype: int64 如果传递了索引,则将从数据中与索引中的标签对应的值提取出来。 In [9]: d = {"a":0.0,"b":1.0,"c":2.0} In [10]: pd.Series(d) Out[10]: a0.0b1.0c2.0dtype: float64
dt2 = np.dtype('i8')# np.float32, np.float64#np.float64占用64个bits,每个字节长度为8,所以64/8,占用8个字节f = np.array([1,2,3,4,5], dtype=np.float64)# 在pandas中若不考虑存储空间和方式的问题,可以简单使用int,float,str即可forcol_nameindata.columns:ifcol_nameinfloat_col_list: ...
// eg. getcwd, see: https://man7.org/linux/man-pages/man3/getcwd.3.html // so we need to check if the buffer is allocated by jemalloc // if not, we need to free it by glibc free arena_ind = je_mallctl("arenas.lookup", NULL, NULL, &ptr, sizeof(ptr)); if (unlikely(arena...
我利用pivot和set_index,把不需要处理的columns先暂时设置成index,这样仅仅留下来两列作为新生成的列的column name和value,完成后在reset_index即可。 # 下面是把行转成列 # 提取保持不变的列,未来要暂时作为index index_col = [item for item in df_Tableau.keys() if item not in ['Measurement', 'Data...
# Random integersarray = np.random.randint(20, size=12)arrayarray([ 0, 1, 8, 19, 16, 18, 10, 11, 2, 13, 14, 3])# Divide by 2 and check if remainder is 1cond = np.mod(array, 2)==1condarray([False, True, False, True, False, False, False, True, False, ...