<jupyter_start><jupyter_text>MSFT Dataset Cleaning Part<jupyter_code># Reading Data file
df2=pd.read_csv(r"C:\Users\Priti\Downloads\Technocolabs Internship Program\MSFT.csv")
#For checking shape of dataset
print(df2.shape)
# To print top 5 lines of the dataset
df2.head()
# Checking the dataset contain missing values or not 
df2.isnull().values.any()
# finding sum of missing values
df2.isnull().sum()
# To finding the basic information about the dataset
df2.info()
# To checking the dataset contain any duplicated values or not
df2[df2.duplicated()]
# To find Descriptive of the dataset
df2.describe()
# To ploting the distribution of profit or loss 
sns.distplot(df2['Volume'],kde=False,bins=50) # safe to ignore the warnings
# To plot the pairplot of Dataset
sns.pairplot(df2)
# Plotting Heatmap of dataset
sns.heatmap(df2.corr())<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.09837962962962964, 'fraction_numerical': 0.017361111111111112, 'mean_word_length': 5.865079365079365, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '436452', 'license': 'Apache-2.0', 'n_tokens_mistral': 293, 'n_tokens_neox': 284, 'n_words': 93, 'path': '.ipynb_checkpoints/Data Cleaning Task-checkpoint.ipynb', 'repo_name': 'deepikagoel1/TeamA', 'size': '864'}