<jupyter_start><jupyter_text>retrive data from a table<jupyter_code>import pandas as pd
from matplotlib import pyplot as plt
sample_data = pd.read_csv("c_table_dataset.csv")
print(sample_data)
print(type(sample_data))
print(sample_data.columns)
print(sample_data.column_a)
print(type(sample_data.column_a))<jupyter_output><class 'pandas.core.series.Series'><jupyter_text>retrive data from column_a location 2<jupyter_code>print(sample_data.column_a.iloc[2])<jupyter_output>4<jupyter_text>ploting the co-ordinates using dot<jupyter_code>plt.plot(sample_data.column_a, sample_data.column_b, "o")
plt.plot(sample_data.column_a, sample_data.column_c, "s")
plt.xlabel("x")
plt.ylabel("y")
plt.show()<jupyter_output><empty_output><jupyter_text>ploting the co-ordinates using dot and line<jupyter_code>plt.plot(sample_data.column_a, sample_data.column_b)
plt.plot(sample_data.column_a, sample_data.column_c)
plt.plot(sample_data.column_a, sample_data.column_b, "o")
plt.plot(sample_data.column_a, sample_data.column_c, "s")
plt.xlabel("x")
plt.ylabel("y")
plt.show()<jupyter_output><empty_output>
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{'chain_length': '4', 'dir': 'jupyter-structured-clean-dedup', 'id': '432497', 'license': 'MIT', 'n_tokens_mistral': 448, 'n_tokens_neox': 434, 'n_words': 57, 'path': '1. Simple Data vizulization/c_tableData_ploting.ipynb', 'repo_name': 'shahin-cuet/Data-Vizulization-Practice', 'size': '1089'}