@@ -118,8 +118,8 @@ def get_csv(self, output_dir: os.PathLike) -> os.PathLike:
118118 vmstat_df ["Time" ].dt .tz_convert ("UTC" ).astype ("int64" ) // 10 ** 9
119119 )
120120
121- pidstat_df : pd . DataFrame = pd .read_csv (
122- self .pidstat .get_csv (output_dir ), sep = ";" , enginge = "pyarrow"
121+ pidstat_df = pd .read_csv (
122+ self .pidstat .get_csv (output_dir ), sep = ";" , engine = "pyarrow"
123123 )
124124 agg_dict = {col : "sum" for col in pidstat_df .columns if col != "Time" }
125125 pidstat_df = pidstat_df .groupby (["Time" ], as_index = False ).agg (agg_dict )
@@ -129,7 +129,7 @@ def get_csv(self, output_dir: os.PathLike) -> os.PathLike:
129129 vmstat_df = vmstat_df .add_prefix ("vmstat_" )
130130 pidstat_df = pidstat_df .add_prefix ("pidstat_" )
131131 mpstat_df .rename (columns = {"mpstat_Time" : "Time" }, inplace = True )
132- vmstat_df .rename (columns = {"vmtat_Time " : "Time" }, inplcae = True )
132+ vmstat_df .rename (columns = {"vmstat_Time " : "Time" }, inplace = True )
133133 pidstat_df .rename (columns = {"pidstat_Time" : "Time" }, inplace = True )
134134
135135 df : pd .DataFrame = ft .reduce (
@@ -151,7 +151,7 @@ def get_csv(self, output_dir: os.PathLike) -> os.PathLike:
151151 )
152152
153153 df = df .sort_values ("Time" ).reset_index (drop = True )
154- df .fillna ( method = " ffill" , inplace = True )
154+ df .ffill ( inplace = True )
155155
156156 self .local_file = os .path .join (output_dir , "merged_stats.csv" )
157157 df .to_csv (self .local_file , index = False , sep = ";" )
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