Discuss various preliminary adjustments that are necessary to do before analysing a time series data. 

Analyzing time series data requires careful consideration of various factors and preliminary adjustments to ensure the accuracy and reliability of the results. Time series data is a sequence of observations recorded at regular intervals over time, and it often exhibits specific patterns and characteristics that need to be addressed before diving into the analysis. Here are some key preliminary adjustments to consider:

1. Data Cleaning: The first step in any data analysis is data cleaning. Remove or impute missing values, handle outliers, and address any data entry errors. Missing data can significantly impact the analysis, and imputing values should be done carefully, considering the nature of the time series.

2. Sampling Frequency: Check the sampling frequency ______ _______ _____ ___ _________.
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