<jupyter_start><jupyter_text>To read csv file from storage<jupyter_code>df = pd.read_csv("data/survey_results_public.csv")<jupyter_output><empty_output><jupyter_text>Printing just data frame<jupyter_code>df<jupyter_output><empty_output><jupyter_text>Printing head section (first rows) of fata-frame (default n=5)<jupyter_code>df.head()<jupyter_output><empty_output><jupyter_text>Printing head section (first rows) with varible no of rows (n) of fata-frame<jupyter_code>df.head(10)<jupyter_output><empty_output><jupyter_text>Printing tail section (last rows) of fata-frame (default n=5)<jupyter_code>df.tail()<jupyter_output><empty_output><jupyter_text>Printing tail section (last rows) with varible no of rows (n) of fata-frame<jupyter_code>df.tail(10)
df.shape<jupyter_output><empty_output><jupyter_text>display column names and their respective data types<jupyter_code>df.info()<jupyter_output><class 'pandas.core.frame.DataFrame'>
RangeIndex: 88883 entries, 0 to 88882
Data columns (total 85 columns):
 #   Column                  Non-Null Count  Dtype  
---  ------                  --------------  -----  
 0   Respondent              88883 non-null  int64  
 1   MainBranch              88331 non-null  object 
 2   Hobbyist                88883 non-null  object 
 3   OpenSourcer             88883 non-null  object 
 4   OpenSource              86842 non-null  object 
 5   Employment              87181 non-null  object 
 6   Country                 88751 non-null  object 
 7   Student                 87014 non-null  object 
 8   EdLevel                 86390 non-null  object 
 9   UndergradMajor          75614 non-null  object 
 10  EduOther                84260 non-null  object 
 11  OrgSize                 71791 non-null  object 
 12  DevType                 81335 non-null  object 
 13  YearsCode               87938 non-null  object 
 14  Age1stCode              87634 non-null[...]<jupyter_text>Set maximum columns to show when to display dataframe<jupyter_code>pd.set_option('display.max_columns', 85)<jupyter_output><empty_output><jupyter_text>Set maximum rows to show when to display dataframe<jupyter_code>pd.set_option('display.max_rows', 100)
schema_df = pd.read_csv("data/survey_results_schema.csv")
schema_df<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.08914386584289496, 'fraction_numerical': 0.05383936451897617, 'mean_word_length': 2.984182776801406, 'pattern_counts': {'":': 0, '<': 37, '<?xml version=': 0, '>': 37, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '9', 'dir': 'jupyter-structured-clean-dedup', 'id': '619522', 'license': 'MIT', 'n_tokens_mistral': 837, 'n_tokens_neox': 727, 'n_words': 169, 'path': 'pandas basics/Pandas Demo 1.ipynb', 'repo_name': 'ikaushikpal/ML_Prerequisite', 'size': '2266'}